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How MoEngage used Nektar to Increase Opportunity Multithreading by 131%

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How MoEngage used Nektar to Increase Opportunity Multithreading by 131% INDUSTRY Enterprise Software HEADQUARTERS San Francisco, California WEBSITE https://www.moengage.com/ Book a Demo See Nektar in Action 131% increase in multithreading score 318+ relevant leads identified & added (QoQ) $932k+ added to qualified pipeline QoQ As sales organizations scale, one challenge becomes harder to ignore: maintaining complete and accurate CRM data. MoEngage was growing quickly, and measuring sales performance had become critical to improving rep productivity and accelerating revenue. But the data needed to understand pipeline health, buyer engagement, and sales execution was not fully available in Salesforce. Critical customer interactions were scattered across sales reps’ emails and calendars. Many contacts, activities, and engagement signals never made it into Salesforce. As a result, sales leaders did not have a complete view of which stakeholders reps were engaging, whether opportunities were properly multithreaded, or what was driving successful deals. That challenge made one thing clear: if MoEngage wanted better pipeline visibility and stronger sales coaching, it first needed a more reliable data foundation. The Challenge: Incomplete CRM data was limiting pipeline visibility MoEngage lacked the Salesforce data needed to accurately measure pipeline performance and understand whether sales reps were engaging the right stakeholders throughout the buying journey. A significant portion of customer interactions remained siloed in sales reps’ emails and calendars, leaving Salesforce incomplete and difficult to trust. As the sales team expanded, inconsistent CRM updates and process adherence made it increasingly challenging to: Measure the strength and depth of buyer relationships Identify whether opportunities were properly multithreaded Correlate seller activities with deal outcomes Coach reps based on objective engagement data instead of verbal updates Before switching to Nektar, MoEngage used a plugin-based solution that missed capturing ~75% of their data into Salesforce. It also did not attach contacts or activities to the opportunity level, only to the account. That made it difficult for the team to understand which opportunities reps were spending time on, whether deals were single-threaded, and the quality and frequency of interactions happening across active opportunities. MoEngage’s approach relied heavily on correlating data from spreadsheets, incomplete Salesforce records, and verbal updates from reps. For a fast-scaling sales organization, that was not sustainable. Why opportunity-level engagement data mattered For MoEngage, the problem was not just missing data. It was missing context. AEs were engaging with multiple prospects and stakeholders, but only a portion of those contacts were being added to Salesforce. This meant key buyers, decision-makers, and influencers were often missing from opportunity records. As Karthik R, Sales Ops Manager at MoEngage, explained: Karthik RajaramSales Ops Manager AEs engage with a lot of prospects, but sometimes they end up adding just one contact to an opportunity or a lead. They do not have the time or bandwidth to add every contact they’re speaking to. These were key contacts we were missing out on and Nektar helped us to automate this data capture, which enabled us to target our prospects with campaigns and tailored messaging. MoEngage partnered with Nektar to solve three immediate priorities: Add missing contacts into Salesforce Identify execution gaps across active opportunities​ Understand key indicators of successful sales execution The Solution: Turning fragmented GTM activity into structured Salesforce data Nektar helped MoEngage capture and structure GTM activity that was previously hidden across emails and calendars. With more than 50 reps, MoEngage had a significant number of contacts hidden in sales reps’ inboxes. Nektar mined these inboxes to identify missing buyers, decision-makers, and key influencers, and brought that data into Salesforce at the opportunity level. By leveraging Nektar’s data, including 3.6K Opportunity Contact Roles, MoEngage was able to test its hypotheses around buyer engagement, persona coverage, and multithreading. The analysis revealed that: High-performing reps had 3.8x higher multithreading scores compared to others High-performing reps engaged decision-makers in the early stages of the sales cycle Nektar also surfaced 318 leads quarter-over-quarter that reps were already in contact with. These leads were more likely to engage with marketing and sales efforts than cold leads from a third-party database, resulting in an additional qualified pipeline of $932K quarter-over-quarter. Nektar helped MoEngage move from scattered activity to actionable sales insights Automated data capture gave MoEngage a stronger foundation for tracking pipeline health and identifying execution gaps. Instead of relying on spreadsheets and verbal updates, MoEngage used Nektar data and insights to get a comprehensive view of account and opportunity-level engagement, including where reps were spending their time, which people were involved, and why certain deals were stalling. There’s a lot of opportunities, but we only have certain amount of time in the day… Nektar helped in breaking it down to 2 or 3 areas we can coach a rep on, and which deals matter… Nektar flags for me what I should spend my time on. Manohar NandigamSenior Director, Sales Enablement This helped managers focus on the deals and coaching areas that mattered most, instead of spending time chasing updates or manually piecing together activity data. Building sales performance leading indicators With buyer-seller activity tracked through Nektar, MoEngage managers were able to shift from verbal deal updates to objective coaching conversations. Nektar helped establish leading indicator benchmarks such as Multithreading Score and Hustle Score, based on top-performer analysis. These indicators gave managers a quantitative way to understand sales execution, follow-up cadence, stakeholder engagement, and process adherence. The best part of Nektar leaderboards is that it gives quantitative data on how the reps are pushing across deals, what’s their follow-up cadence, sales process adherence. Hastu KshitijSenior Vice President This gave MoEngage a clearer view of how reps were executing across opportunities and where managers could intervene earlier to improve outcomes. The Impact By partnering with Nektar, MoEngage was able to turn fragmented GTM activity into structured Salesforce data that sales leaders could trust. The impact included: 131% increase in opportunity multithreading 3.6K+ missing OCRs added to Salesforce 46K+ sales activities captured in Salesforce $932K in additional qualified pipeline generated QoQ Additionally, Nektar improved visibility into execution gaps and risks across in-flight opportunities, along

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How Nektar Powered Mimecast’s Agentic GTM AI

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How Nektar Powered Mimecast’s Agentic GTM AI with Complete Customer Signals INDUSTRY Cybersecurity HEADQUARTERS London, England WEBSITE https://www.mimecast.com/ Hear directly from Tim about the challenges, decisions, and lessons behind Mimecast’s AI and GTM transformation. Watch Webinar $10M in total expansion revenue $150M+ in additional pipeline identified 2K+ new activities logged through historical data backfill As enterprise AI evolves, one thing is becoming clear: models are getting easier to access, and agent frameworks are becoming easier to build. The real advantage comes from something harder to replicate — proprietary data. Mimecast recognized this early in its AI journey. The company was investing in internal generative AI capabilities to surface better customers and prospect insights across the go-to-market lifecycle. The vision was ambitious: build AI applications that could support teams across acquisition, expansion, retention, renewal, and prospecting. But like many enterprises, Mimecast ran into a familiar challenge. The data needed to power those applications was spread across disconnected systems, inconsistent workflows, and siloed teams. Valuable engagement signals existed, but they were difficult to access, difficult to standardize, and hard to use at the level of granularity required for meaningful AI outcomes. That challenge made one thing clear: if Mimecast wanted AI to create real business value, it first needed a stronger data foundation. The Challenge: AI is only as strong as the data behind it Mimecast had already built its own internal generative AI engine to identify customer and prospect insights. But success depended on capturing and organizing the right GTM data inside its own data model. That was easier said than done. Critical information about customer engagement, buying committee members, and deal influence was spread across multiple processes and systems. Some GTM tools did not provide access to the data Mimecast needed. In other cases, the data was available, but not in a form detailed enough to support the outcomes the team was after. As Tim Seamans, VP of AI Acceleration at Mimecast, explained: Tim SeamansVP, Al Acceleration & Transformation We build our own generative AI engine internally to identify customer and prospect insights. What’s paramount for success is capturing available data and aligning it in operational systems. He added: “It’s really difficult to access data across disparate processes and systems so that we can get the right data, in the right place, at the right time.” Mimecast’s challenge was not a lack of AI ambition. It was the difficulty of bringing together the underlying data required to make AI applications accurate, useful, and scalable. Why proprietary data became central to Mimecast’s AI strategy Mimecast’s approach was rooted in a clear belief: while models and agents continue to improve, proprietary data is what ultimately creates a durable advantage. That thinking shaped the company’s AI roadmap. Mimecast began building 8–10 specialized AI applications and agents across the customer lifecycle, including applications for: Acquisition Expansion Retention Renewal management Prospecting These applications were designed to help teams act on customer and prospect signals more intelligently. But for them to work well, Mimecast needed better access to engagement data and customer context across the business. The priority was not simply generating more output. It was making sure AI systems had the right inputs to produce accurate, trustworthy, and business-relevant outcomes. The Solution: Unlocking the GTM data layer with Nektar Nektar helped Mimecast access the data and metadata it needed to strengthen the foundation behind its AI strategy. By capturing GTM engagement data that had previously been fragmented or unavailable, Nektar helped Mimecast unify important customer signals and make them available downstream. Just as importantly, that data could be delivered into the systems where Mimecast needed it most — including its CRM and data lake. That meant Mimecast could use Nektar not as another destination system, but as a data layer that supported its existing architecture and internal AI applications. Nektar helped us get the data (and metadata) we needed that was previously locked up or not available. And they can pipe it to our CRM or our data lake. Tim SeamansVP, Al Acceleration & Transformation This was a meaningful shift. Instead of relying on incomplete signals or inaccessible information, Mimecast could work with a richer and more structured view of customer engagement. Nektar helped Mimecast turn fragmented GTM data into an AI-ready signal layer Mimecast’s AI strategy depended on one thing: having complete, usable customer and prospect data inside its own systems. Nektar helped make that possible by unlocking and structuring engagement data that had previously been siloed, incomplete, or inaccessible. With Nektar, Mimecast was able to add meaningful scale and depth to the data powering its internal AI applications, including: 24K+ net-new contacts added 200K+ historical and ongoing emails captured and enriched 1K+ hours of manual rep work saved annually That data foundation gave Mimecast a much richer signal layer for customer insights, prospect intelligence, feature engineering, and AI-driven workflows. Instead of working from partial records and missing context, the team could feed its AI applications with complete interaction history across the customer lifecycle. Building for accuracy, not just automation For Mimecast, the goal was never to deploy AI for its own sake. The goal was to make AI outputs reliable enough to drive action. That required more than models. It required structured data, stronger context, and the ability to capture the signals that shape real customer outcomes. With Nektar helping fill those gaps, Mimecast was able to improve the quality of inputs behind its AI applications. That, in turn, supported more accurate insights across critical GTM workflows and spending more time acting on actionable signals and less time finding and structuring the data. This was especially important for a company building specialized applications across the customer lifecycle. Better data meant better context, better context meant better output, and better output made it easier to tie AI efforts to tangible business value. The business results came quickly. In the first 80 days after launching just one of Mimecast’s Proprietary AI tools, “Expansion AI”, the company achieved: The impact: $2M in expansion revenue and

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How Activity Tracking Can Help You Get Better Visibility Into Deals

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How Activity Tracking Can Help You Get Better Visibility Into Deals RevOps 10 min There hasn’t been a time that demanded sustainable revenue growth more than now. Economic headwinds of the last few months have forced businesses to rethink their revenue growth strategies and focus on efficiency. This means getting away with anything that does not make a positive dent in revenue or causes revenue to leak across the sales funnel. But cutting deep costs is not the only way to increase profits. It’s about doubling down on what’s working. And investing time and resources in strategies that help the whole company march towards the same objective – increased revenue.  And there is one sure shot way of achieving this. By knowing exactly what’s happening with your deals. And how can you do that? Activity tracking. Let’s dive deep. What is Activity Tracking? Activity tracking in sales refers to monitoring and recording the various actions and behaviors undertaken by sales professionals as they engage in their sales activities. It involves tracking and measuring the specific activities performed during the sales process, such as the number of calls made, emails sent, meetings scheduled, demos conducted, and deals closed. The purpose of activity tracking in sales is to gain insights into the sales process, assess individual and team performance, and make data-driven decisions to improve sales effectiveness.  What is an Activity Tracking Software? An activity tracking software is designed to monitor and record the various activities performed by sales representatives or teams. These activities typically include interactions with leads and prospects, customer communication, follow-ups, and other sales-related tasks. The primary purpose of activity tracking software is to help sales managers and team leaders assess and improve the productivity and effectiveness of their sales teams. Why Do We Need Activity Tracking? Accurately and comprehensively capturing activity data poses a significant challenge. Despite 67% of businesses utilizing 4 to 10 digital tools, they need to track the activity data generated by these tools completely and precisely. Additionally, 79% of opportunity-related data sales representatives collect never enters the CRM. Moreover, the data recorded in systems like CRM could be more reliable, plagued by issues like outdated, missing, or incomplete entries. This lack of data accuracy is a concern for as many as 70% of revenue leaders, leading to substantial financial losses averaging around $15 million per year for organizations. The presence of accurate and complete activity data in systems like CRM creates misalignment among teams in terms of their technological tools and objectives. When sales teams grapple with questions about updated prospect contact information or the correctness of email IDs in the CRM, their efficiency could improve, positively impacting both businesses and customers. Due to lacking confidence in the data, sales, and marketing teams work in the dark, unable to leverage the full potential of significant investments like CRMs. This situation results in poor returns on investment for such resources. https://www.youtube.com/watch?v=GO6zZpHUoIg&t=1s How Does Poor Activity Data Affect Revenue? Poor data and a lack of activity data in the CRM can harm gaining accurate insights and lead to revenue leakage throughout the customer journey. Here are some key points to consider: 1. Inaccurate or incomplete data When data quality is compromised, it becomes challenging to extract meaningful insights. Only complete or updated information can lead to correct assumptions and flawed decision-making. 2. Missed opportunities Important customer interactions and touchpoints may go undocumented without comprehensive activity data. This lack of visibility can result in missed opportunities to engage prospects, address their needs, and nurture relationships, leading to potential revenue leakage. 3. Ineffective sales strategies The absence of activity data hinders the ability to analyze and optimize sales strategies. Without a clear understanding of which activities drive results, aligning sales efforts with customer preferences and needs becomes difficult, resulting in suboptimal outcomes. 4. Inefficient resource allocation With activity data, it’s easier to assess the productivity and effectiveness of sales teams. This can lead to misallocation of resources, including time, effort, and budget, resulting in revenue leakage and diminished returns on investment. Clean data is essential for Activity Tracking Software as it ensures accurate and error-free information, leading to reliable insights into sales team activities and facilitating better decision-making and performance analysis. With clean data, the software can provide a comprehensive view of sales interactions, prospect engagement, and customer behavior, enabling businesses to identify opportunities, optimize processes, and enhance overall sales efficiency.  Moreover, clean data minimizes the risk of misinterpretation or skewed reporting, fostering greater trust in the software’s output and empowering sales managers and teams to take data-driven actions to achieve their goals. Benefits of Activity Tracking Software Here’s a look at the various advantages of an activity tracking software: 1. Clear visibility into deals Increased visibility into deals serves as a prerequisite for enhancing productivity. When you have comprehensive activity data, you better understand each deal’s status, identify areas that require improvement, and prioritize values that need immediate attention.  Consider the importance of deal reviews in a successful sales process. By utilizing insights derived from unified activity data, deal reviews can evolve from impromptu events to impactful sessions, where sales managers gain clear visibility into the intricacies of every deal.  As activities related to each deal are automatically captured and updated, managers no longer need to remind sales representatives to input data into the CRM constantly. Instead, both reps and managers can access a comprehensive view of contacts and deal specifics within the pipeline, allowing them to focus on urgent matters. 2. Identification of winning rep behaviours Activity data enables you to correlate the productivity of your sales representatives with their performance. For instance, you can obtain crucial insights to answer important questions such as:  Activity data helps map sales reps’ productivity to their performance It provides answers to critical questions such as time allocation, engagement with high-value customers, decision-maker involvement, adherence to best practices, sales target progress, account engagement, and lead follow-up Insights from activity data serve as leading indicators for real-time coaching and decision-making Managers gain visibility into sales reps’

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Evolution of ABM in Modern Demand Generation

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Evolution of ABM in Modern Demand Generation A conversation with Rick Collins, VP of Demand Generation at Connectwise. “We’ve hit what I call the Great Ignore. Everyone’s overwhelmed with messages across channels… even the good ones are getting ignored.”  In the past 12–18 months, pipeline generation has become increasingly challenging. Rising revenue goals and shrinking budgets have pushed marketing teams into a corner. Traditional tactics—especially high-volume lead generation—are no longer effective. In this environment, Account-Based Marketing (ABM) has emerged as a vital strategy. But to truly succeed, teams must rethink how they define ABM, how they align with sales, and how they scale through integrated processes. This blog, based on a Revenue Lounge podcast episode with Rick Collins, VP of Demand Generation at ConnectWise, is your deep dive into: The evolution of ABM in modern demand gen Aligning go-to-market teams Building operational systems for scale Tools, data, and attribution best practices Key lessons Rick learned the hard way Facebook Twitter Youtube From IT to Demand Gen: Rick’s Unconventional Path Rick’s journey began in IT—working in QA, implementation, and CRM systems. Over time, he gravitated toward marketing operations, and eventually demand generation. “I bring a different lens to demand gen. I’ve built the ops side first, which gave me an appreciation of data, systems, and how to scale programs with precision.” He was the first marketing ops hire at ConnectWise, scaled the team through multiple acquisitions, and later took over demand gen during one of the toughest periods for pipeline creation in SaaS. The Death of Traditional Lead Generation Rick calls out three seismic changes that made legacy demand gen ineffective: The Rise of the Empowered Buyer: Buyers now reach 80–90% of the way through the journey before contacting a vendor. Digital Fatigue: Automation misuse has saturated inboxes and weakened outreach quality. Market Competition: More players, more noise, and higher ad costs. “We used to be a lead-gen machine. Now it’s all about understanding signals, providing value, and making every touchpoint count.” https://www.youtube.com/watch?v=bdDbWb-MWwI Strategies That Actually Work Rick’s team has focused on three core strategies to cut through the clutter: 1. Provide Thought Leadership Without Selling Publish content that helps the audience do their job better. Avoid product mentions in early stages. “The more we can help you without asking for anything, the more trust we build.” 2. Respond Fast When Intent is Declared If someone shows intent, ensure a quick, seamless follow-up. Architect systems for real-time handoff to sales. 3. Revive Direct Mail Physical mail cuts through the noise and makes an impact. Combine gifting with value-driven messaging. “You send me a direct mail piece—I’m going to see it. It stands out.” ABM is Not a Tool. It’s a Strategic Motion “Start with the strategy. Don’t buy the tool until you know what you want to achieve.” Too many organizations make the mistake of buying an ABM platform before defining their motion. Rick recommends starting small and proving success manually. MQLs vs Buying Groups: A Nuanced Approach Rick doesn’t claim MQLs are dead—but they are misunderstood. The definition varies drastically across companies. What’s more effective? Tracking buying group signals. “We’re operating under the buying group model in our upmarket motion. One person may raise their hand, but we’re watching the whole committee.” MQL vs Buying Group Comparison: Criteria MQL Buying Group Focus Individual Committee/Swarm Common in SMB Enterprise, Mid-market Trigger Email open, form fill Intent + multiple touchpoints Limitation Ignores influence Holistic engagement Ideal motion Automated lead nurture High-touch ABM Solving Attribution & Measurement Challenges “We use cohort reporting to measure ABM. Attribution is helpful, but it’s directional.” Attribution is complex—especially when sales teams don’t tag every contact or touchpoint in CRM. Rick’s solution is cohort-based reporting: Cohort Reporting Process: Choose a set of 500 target accounts Launch a defined campaign or series of campaigns Measure: Pipeline creation Opportunity conversion Win rates Double-click into successful accounts and identify what worked Aligning with Sales: The Non-Negotiable Element “If sales isn’t bought in, it’s just marketing playing by themselves. It doesn’t work.” Rick emphasizes that sales buy-in is crucial. Here’s his playbook for driving that alignment: Sales Alignment Checklist: Joint Sales-Marketing ABM Execution Plan Phase Action Owner Account Selection Agree on Tier 1 accounts Sales + Marketing Persona Mapping Identify roles & pains Marketing Messaging Customize value stories Marketing + Enablement Outreach Sequence delivery SDRs + Reps Follow-Up Meetings & nurture Sales Reporting Track cohort progress Ops Tech Stack and Data Activation: A Pragmatic View “Tools won’t fix your strategy. They help scale what’s already working.” Rick breaks the ABM tech landscape into three layers: Signal Aggregation – intent data, website visits, email behavior. Activation – digital ads, gifting, outreach. Measurement – pipeline contribution, cohort lift, influence. His recommendation: push data into Salesforce and trigger workflows from there. Otherwise, data sits idle. “We built a prospecting dashboard showing intent scores, untouched accounts, and pipeline priority. Next step: automate the whole motion.” Balancing Short-Term Metrics vs Long-Term Relationship Building “If someone has the answer to balancing short- and long-term pipeline generation, I’m all ears.” Rick’s team avoids meeting-based comp for SDRs. Instead, they’re measured on accepted pipeline and closed-won influence. But this is still a work-in-progress. SDR Measurement: Old vs New Model Meeting-Based Pipeline-Influence-Based Pros Easy to track Aligned with revenue Cons Short-term focus Complex to implement Outcome Flimsy meetings Better qualified pipeline The Power of Insightful Personalization A campaign that stood out to Rick? A vendor targeting ConnectWise built a hyper-personalized series referencing his CMO’s Boston roots and even tied it to Tom Brady. “It wasn’t just clever—it was relevant. And it solved a real pain. That’s what made it stick.” Lesson: Don’t just personalize. Make it insightful and timely. Final Lessons Learned “We made two big mistakes early on: Lack of executive alignment and poor account selection.” What Rick Would Do Differently: Spend more time aligning with sales leadership. Don’t rely only on systems to pick accounts—get sales input early. “Sales will throw out your list if even one account

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From Chaos to Clarity: Building a Unified Revenue Engine at Scale

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From Chaos to Clarity: Building a Unified Revenue Engine A conversation with Alana Kadden Ballon, VP of Revenue Operations at Sprout Social. In a world overflowing with data, what go-to-market teams need most isn’t more information—it’s unified, trusted, and actionable data. But with siloed systems, misaligned incentives, and scattered signals, many revenue organizations face what’s best described as “data chaos.” In this episode of The Revenue Lounge, Alana Ballon, VP of Revenue Operations at Sprout Social, joins the show to talk about cutting through that chaos to build a unified revenue engine—one that aligns teams, connects insights, and drives growth at scale. Facebook Twitter Youtube The Journey from Sales to Strategy Alana’s story begins on the sales floor, grinding through BDR calls before becoming an AE, enablement leader, and finally a RevOps strategist. Her early experience shaped a foundational understanding of customer challenges and cross-functional collaboration—making her uniquely equipped to scale revenue engines in hyper-growth SaaS environments like Salesforce, Wiz, and now Sprout Social. What drew her to Sprout? The opportunity to work with trusted leaders, a public company context, and a product that sits at the intersection of social, AI, and media evolution—all within a team hungry for change. What Is a Unified Revenue Engine? To Alana, a unified revenue engine means more than systems talking to each other—it means people and incentives aligned to a single goal: doing what’s right for the customer and the company. Key takeaway:Alignment starts with incentive structures. When sales, marketing, and customer success are driven by shared metrics—like retention, expansion, and customer health—silos start to dissolve. But the path to unification is often blocked by: Frankenstein tech stacks from years of point solution purchases Poor data governance Disconnected workflows across functions Fixing this isn’t just about buying more tools. It’s about aligning people, processes, and platforms around actionable outcomes. https://www.youtube.com/watch?v=wJcdXXzWY3M&t=399s The Watermelon Analogy: Slicing Beyond Surface Metrics Alana introduces a powerful metaphor: the watermelon pipeline. On the outside, everything looks green. But slice it open, and you’ll find the red spots—underperformance in specific segments, sources, or geos. Tips for slicing your watermelon: Dimension What to Check By Source AE-generated vs. marketing vs. partners By Segment Enterprise vs. commercial By Geography Global vs. regional performance By Funnel Stage Are conversions where they should be?   This granular visibility helps GTM leaders diagnose problems early and apply the right levers—from geo-specific campaigns to product-market fit adjustments. From Volume to Value: A Shift in Sales Strategy Alana warns against the trap of prioritizing volume over value—especially in prospecting. “Generic outbound isn’t working. Buyers want value, not spam,” she explains. How Sprout Social is Shifting to Value: Using AI to personalize outreach with real-time brand and campaign data Equipping reps to lead with insight (e.g., “Here’s how your campaign is performing” vs. “Do you want to see a demo?”) Empowering SDRs to think like marketers and act like advisors RevOps Role:Lead the operational cadence that enables this—daily signal reviews, weekly experiment tracking, and cross-functional feedback loops. Aligning GTM Teams: One Plan, One Voice RevOps isn’t just about analytics—it’s about orchestration. At Sprout, Alana ensures that all GTM functions (sales, marketing, channel) plan together, report together, and adapt together. “If you plan separately, you can’t execute together,” she says. Key Practice:Monthly pipeline reviews aren’t blame games—they’re working sessions to adjust levers and optimize together. The Buying Group Shift: Earlier Multi-Threading Traditional MQLs are fading. Sprout, like many modern GTM orgs, is moving towards buying group-based strategies. “Sales calls it multi-threading. Marketing calls it buying groups. Either way, we’re pulling that motion earlier.” This shift requires: Strong opportunity data Early engagement of multiple stakeholders Alignment between sales, marketing, and product marketing Data Readiness Before AI Alana is clear: AI won’t save you if your data is messy. Clean, connected, and governed data is the foundation of any AI-driven GTM motion. Start with the daisy chain: Identify a business problem (not just a data issue). Trace the data gaps that cause it. Fix one thing. Show value. Scale iteratively. Whether it’s country misclassification or duplicate records, solve what’s blocking execution—not just what looks messy on paper. Enabling the RevOps Seat at the Table Alana’s advice for RevOps professionals who want to be seen as strategic partners? Choose your leadership wisely. Strategic RevOps needs alignment with CROs, CMOs, and customer leaders. Automate to accelerate. Her team’s move to auto-generate retro reports lets analysts focus on insights, not spreadsheet prep. Deliver impact iteratively. Big-bang data projects rarely work. Find tangible business problems and chip away. Looking Ahead: The Future of Sales and AI Alana predicts a future where AI will act as an “operator” for salespeople—pulling data, crafting outreach, and driving next steps autonomously. But the human connection won’t disappear. “Sellers will become more technical, more strategic. AI will augment—but not replace—the relationships at the heart of enterprise sales.” Final Thoughts If you’re a revenue leader navigating the messy middle of disconnected data and siloed teams, Alana’s message is clear: Align around the customer Slice the watermelon Start small, show value, and scale And never forget—clean data is the rocket fuel of RevOps Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources

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Data Before AI: Building a Clean Foundation for Smarter RevOps

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Data Before AI: Building a Clean Foundation for Smarter RevOps A conversation with Olga Traskova, VP of Revenue Operations at Birdeye. The AI boom has hit B2B go-to-market teams hard. Everyone wants to automate, optimize, and accelerate—but few are pausing to address the silent killer of ROI: bad data. In this episode of The Revenue Lounge, we sit down with Olga Traskova, VP of Revenue Operations at Birdeye, to unpack the unglamorous yet crucial reality behind AI success: data quality and readiness. With over 15 years in revenue and marketing operations, Olga shares battle-tested insights into building a strong data foundation, choosing the right AI use cases, and avoiding common traps in AI adoption. “We’re trying to drive a Rolls-Royce without a license—and no garage to park it in.”— Olga Traskova, VP Revenue Operations, Birdeye Facebook Twitter Youtube Olga’s Journey — From Marketing Ops to RevOps Leadership Olga began her career in marketing operations, eventually expanding into RevOps as she tackled more cross-functional business challenges. Her growth wasn’t just vertical but horizontal—across marketing, sales, and customer success. Now, as the VP of RevOps at Birdeye, she leads a global operations team serving the US, UK, and Australia. Her mission? Drive revenue efficiency by integrating people, processes, and tools across the customer lifecycle. Her approach is anti-silo: while team members have domain specialties, everyone is cross-trained. This enables agility and ensures seamless support for any GTM leader who engages with RevOps. Why AI Alone is Not the Answer AI is not a magic wand. If your systems are riddled with bad data, no amount of intelligence—artificial or otherwise—can generate reliable insights. Olga shares a relatable frustration: attempting to implement a call transcription tool that auto-fills Salesforce fields to save sales reps time. But when the tool failed to sync correctly with CRM, the data became misaligned, rendering the AI-generated insights useless. “You’re just placing a shiny object on top of garbage. Fix your foundational processes first.” This experience underscores a key RevOps truth: clean data is not optional. It’s a prerequisite. https://www.youtube.com/watch?v=Q-ZoyfU1o8A Three Common Mistakes in AI Adoption Olga highlights several pitfalls that GTM teams must avoid: No Data Foundation: Jumping into AI without structured, accurate data is like building a house on sand. Undefined Use Case: Many teams chase tools without clearly identifying the problem they’re solving. Tool Fatigue: Over-purchasing tools creates more chaos. Teams must prioritize longevity and ease of use. Mistake Description Solution Data Chaos CRM is inconsistent, fragmented, or siloed. Conduct a full data hygiene audit. Vague Goals Buying AI tools without clarity on business outcomes. Define KPIs and workflows before evaluation. Short-Term Thinking Choosing flashy new tools that lack long-term viability. Vet vendors for stability and integration. A Framework for Evaluating AI in RevOps Olga’s decision-making process is grounded in use-case prioritization and long-term alignment. Here’s how she approaches evaluating new AI technologies: Start with a problem: Identify the business gap (e.g., inaccurate forecasts, time-consuming manual tasks). Map to outcomes: Connect the tool to a measurable objective (e.g., improving forecast accuracy within 5%). Assess adoption impact: Will your reps need major retraining? Is it intuitive? Avoid vendor churn: Choose tools with longevity. Avoid investing in platforms likely to fold or get acquired. “Sometimes you don’t need a new tool. You just need to explore what your current stack can already do.” The Anatomy of a Data-Ready Organization Before AI can thrive, core data elements must be defined, standardized, and consistently used. Olga recommends: Clear object mapping: Standardize definitions for leads, contacts, accounts, and opportunities. Journey alignment: Define lifecycle stages and statuses across marketing, sales, and CS. Field governance: Ensure input fields (titles, stages, reasons) are consistent and readable. CRM integration: All third-party tools (e.g., Gong, Outreach) must sync cleanly into your CRM. Your data model should be simple enough to translate into a plain-language sentence. If AI can’t “read” it clearly, it can’t act effectively. Solving the Silo Problem Despite increasing tech stack integration, most data remains siloed. Tools like sales engagement platforms often retain data internally instead of pushing it into CRM. Olga explains that today, CRM remains the system of record for her team—especially to support forecasting and enforce sales methodologies like MEDDIC. She envisions a near-future where language-model-powered agents aggregate insights across tools seamlessly, eliminating the need for a singular data warehouse. But until that vision is reality, enforcing consistency in CRM remains critical. Measuring AI Success: Beyond Buzzwords One of the most critical, yet often ignored, aspects of AI adoption is ROI measurement. Olga encourages RevOps leaders to think deeply about what success looks like: Is your AI helping reduce CAC? Are sales cycles shortening? Is forecasting accuracy improving? In her experience, AI tools can identify improvement areas (e.g., objection handling, qualification gaps), but execution still depends on humans. That’s where enablement, coaching, and process management come in. “AI can’t execute. You still need to ensure things get done.” Who Owns AI in GTM? A Cross-Functional Responsibility At Birdeye, AI ownership sits across the go-to-market leadership—sales, marketing, CS, solutions engineering, and RevOps. While RevOps leads vendor evaluation and implementation, all stakeholders collaborate on identifying use cases and defining requirements. Security and compliance teams are also critical players, especially as legal concerns about data privacy, training models, and proprietary information increase. “To stay ahead, every GTM leader must go back to the ‘how’ and the ‘what’ of AI. You can’t afford to ignore it.” Olga’s AI Stack: Tools That Work Today While enterprise-wide rollouts are still evolving, Olga and her team leverage several tools to boost productivity: ChatGPT & Claude: For research, data analysis, and ideation Gamma: To turn findings into visual presentations quickly Zoom AI Companion: For call summaries and next steps LinkedIn Sales Nav AI: For prospect intelligence She emphasizes that many AI capabilities already exist within current tools. Leaders should prioritize exploring these features before investing in something new. Final Thoughts: The Human-AI Partnership Olga doesn’t believe AI is here to replace people—not yet. Instead, she sees it as

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From MQLs to Opportunity-Centric Revenue: How Reltio Transformed Its GTM Strategy

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From MQLs to Opportunity-Centric Revenue: How Reltio Transformed Its GTM Strategy A conversation with Joel Jacob, Director of Marketing Operations at Reltio. For years, marketing teams have been evaluated by MQLs (Marketing Qualified Leads). But as B2B buying behavior has evolved—where decisions are made by buying committees and involve longer, more complex journeys—the MQL metric no longer serves its original purpose. One person filling out a form doesn’t indicate true intent, and one lead doesn’t equal one deal. The Shift: From Leads to Opportunities Reltio, a leading B2B SaaS platform that unifies data for enterprise clients, realized this shift early. With a sales cycle averaging nine months and involving multiple stakeholders, their traditional lead-based funnel was no longer sustainable. Joel Jacob, Director of Marketing Operations at Reltio, shares how they transitioned from a legacy MQL-based model to a modern, opportunity-centric buying group strategy. This wasn’t just a process tweak—it was an end-to-end transformation of their go-to-market engine, completed in just 60 days. Facebook Twitter Youtube Why the MQL Model Failed Reltio Joel and his team began by diagnosing the inefficiencies of their MQL-centric process: 1% Conversion Rate: Only 1 out of every 100 MQLs was turning into closed-won revenue. Single-Threaded Opportunities: BDRs would often pursue individual leads without context, while AEs had to manually identify and involve the broader buying group. Misaligned Processes: Marketing, BDRs, and sales were working in silos, tracking separate KPIs and speaking different languages. High Customer Expectations: Their enterprise clients required a tailored, consultative approach, not generic drip campaigns and lead scoring. “We weren’t solving for how we sell. We needed to solve for how our customers buy.” What Changed: The Opportunity-Based Revenue Engine At the heart of Reltio’s new model is the concept of an opportunity container that is tracked from the very start of the buying journey. Key Components: Stage 0 Opportunities: Created proactively for cold target accounts to align all GTM efforts from the get-go. Buying Group Identification: Progress only happens when at least three relevant personas are identified within the opportunity. Unified Funnel Ownership: Marketing, BDRs, and AEs jointly own and advance each opportunity. Real-Time Intent + Historical Data: Powering personalized campaigns and outreach using platforms like 6sense and LeanData. Persona-Based Targeting: Ads and outreach are aligned with opportunity stage and key personas, not just job titles or industries. This model allows for marketing to target ads based on opportunity stage, for BDRs to tailor messaging using real-time insights, and for AEs to focus on qualified, committee-led opportunities.   https://www.youtube.com/watch?v=NPhOjO54wac&t=1s Overcoming Operational Hurdles Implementing this new strategy wasn’t without challenges: Time Constraint: The entire shift had to happen in just 60 days, before the start of the fiscal year. No New Tech: Reltio opted to re-architect their existing stack (Salesforce, Marketo, LeanData, 6sense) rather than buy new tools. Zero Downtime: The transition had to happen without interrupting live sales or BDR workflows. Team Alignment: Joel and team had to overcome deeply entrenched habits and misaligned incentives. “We stopped calling ourselves marketing or sales ops. We were just ‘operations’—unified behind a common goal.” Data Quality: The Real MVP Joel emphasized that none of this would have been possible without clean, connected data across marketing and sales systems. Years before the switch, Reltio had invested in data unification and intent platforms. That foundation paid off. Historical Data: Enabled predictive modeling via 6sense. Account-Centric View: Powered by LeanData and Salesforce to track buying group activity. No More Attribution Wars: Everyone works the same opportunities, making marketing influence clear without the blame game. “60 days gets the headlines, but that was only possible because we invested years into getting our data right.” The Role of AI in a Data-Ready World Joel’s team now uses AI to increase efficiency in key areas: BDR Enablement: Automating research and outreach so reps spend more time engaging and less time preparing. Predictive Signals: Using AI to model when an account is likely to move into an active buying cycle—based on engagement and historical patterns. Campaign Optimization: Automating content and ad delivery based on opportunity stage. But he warns: AI without good data is meaningless. “There is no AI without clean data. If you feed bad data into AI, you’ll just get bad results faster.” The Payoff: Faster Velocity, Better Pipeline Stickiness Reltio’s transformation delivered results fast: Pipeline Stickiness: Opportunities are more likely to progress and less likely to go dark. Faster Velocity: More deals now close within the same fiscal year, despite a 9-month average cycle. Better Alignment: GTM teams operate from the same playbook, improving efficiency and morale. Clear Attribution: Marketing and sales share credit instead of competing for it. Advice for Teams Looking to Make the Shift Joel’s parting advice for RevOps and marketing leaders: Let the Data Lead: Start with facts, not opinions. Use historical conversion rates to make the case for change. Collaborate Cross-Functionally: Ditch the silos. Align Ops, Sales, and Marketing under shared goals. Don’t Wait for Perfection: You don’t need a perfect tech stack. Use what you have and iterate. Train and Align Mindsets: It’s not just a systems change—it’s a mindset shift. Over-communicate and retrain internal teams on the new model. Stay Customer-Centric: Build your process around how your customers actually buy—not around your internal comfort zone. Final Thoughts Reltio’s journey proves that moving beyond MQLs is possible—and impactful. But it requires more than new tools or campaigns. It takes executive buy-in, operational discipline, and a deep commitment to aligning every team around opportunity creation and customer value. “We don’t talk about ABM anymore. We just call it the process. Because it’s how we work now.” Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources

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Winning Buying Groups: Using Data and ABM to Influence Complex B2B Deals ft. Sydney Sloan

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Welcome to The Revenue Lounge How to Influence Buying Groups with Data, Intent, and ABM A conversation with Sydney Sloan, Chief Market Officer at G2. B2B buying has transformed. What was once a one-on-one sales conversation is now a team sport, spanning roles, departments, and even geographies. Today’s buyers are informed, autonomous, and collaborative. They’re forming buying groups long before sales ever enters the conversation. And if your go-to-market (GTM) team isn’t aligned to this reality, you’re already playing catch-up. In this episode of The Revenue Lounge, Randy Likas sits down with Sydney Sloan, Chief Market Officer at G2, to unpack how marketing and sales teams can evolve to influence modern buying groups. She is a 4X CMO, board member and advisor with decades of experience in driving transformative growth and innovation for high-tech companies. Sydney offers a masterclass in using data, intent signals, and segmentation to win complex deals. Here’s a breakdown of the conversation—and why it matters. Facebook Twitter Youtube 🚨 Why Buying Groups Matter More Than Ever The traditional lead-based model is failing. As Sydney puts it, “MQLs are noise.” They flood sales with contacts that aren’t ready to buy—leading to frustration, wasted time, and missed opportunities. Instead, modern revenue teams must focus on identifying buying groups—clusters of stakeholders from the same account showing interest in your solution. These signals can come from downloading content, comparing vendors, visiting your pricing page, or just quietly researching on review platforms. A single lead might lie. But a buying group rarely does. “When you have executive alignment and more than three people in the buying cycle, close rates are 44% higher.”– Sydney Sloan, CMO, G2   🧠 Data Is the Foundation. But it Needs to Be Smart Sydney breaks down three types of intent data: Third-party: Activity across the open web (e.g., searches, keyword trends). Second-party: Data from trusted ecosystems like G2—category views, comparisons, reviews. First-party: Visitor behavior on your own website, CRM engagement history, and sales activity. The magic happens when you triangulate these data sources. For instance, if someone downloaded your whitepaper (first-party), compared your product with a competitor on G2 (second-party), and searched relevant terms online (third-party)—you’ve got a red-hot buying group signal. But here’s the catch: if your CRM is a mess or your systems are siloed, you’ll never connect those dots.   “There’s no excuse not to have tier 1 and 2 accounts built out with clean, up-to-date contacts across buying personas.” https://www.youtube.com/watch?v=NkYTDVKx5Eg 🔁 The New GTM Playbook: From Leads to Stakeholders Moving to a buying group strategy requires more than good data—it requires GTM alignment. Instead of chasing individual MQLs, Sydney recommends: Scoring accounts, not contacts. Tracking signals at the account level to prioritize outreach. Rethinking SDR metrics: focus on meetings with multiple personas, not just any meeting. Partnering marketing, sales, and product around a shared account strategy. Sydney shares how G2 moved to an account-based model where the sales team gets tailored engagement strategies based on segment (SMB, mid-market, enterprise). Every team member—from demand gen to product marketing—knows who their core personas are and how they relate to each other. 🧩 Operationalizing Buying Groups at Scale At Forrester’s recent event, a key theme emerged: evolving from “buying groups” to “buying networks.” This includes partners, peers, analysts, and ecosystems that influence buyer decisions. Sydney highlights a few scalable tactics to work with buying groups: Persona Workshops: G2 ran hands-on workshops using real Gong quotes to help every department internalize customer personas. Segmented Campaigns: Instead of generic ABM, G2 builds micro-segments like “Security companies using 6sense, not yet G2 customers,” and tailors messaging accordingly. Pipeline Meetings: Marketing, sales, and SDRs review the same data together bi-weekly to troubleshoot stuck opportunities and improve velocity. Deal Acceleration Programs: Everyone in stage 2 of the pipeline gets invited to bi-weekly virtual events to deepen relationships and drive conversion. ⚖️ Brand vs. Demand: It’s Not Either/Or Many companies struggle with where to invest: long-term brand or short-term pipeline. Sydney makes it clear: do both, early and often. Brand earns you a seat at the table. G2’s Buyer Behavior Report shows average vendor shortlists are down to just three. Demand capture turns that attention into pipeline. “Brand is giving something away with no ask. Demand is giving something away to capture a contact. Different plays, both essential.” 📈 Rethinking KPIs for Buying Group Success MQLs are out. So what’s in? Sydney advocates for shared KPIs across marketing and sales focused on: Pipeline creation Closed-won revenue Retention Internally, marketing can track velocity, lead-to-meeting time, and program-level cost-per-lead. But in cross-functional pipeline meetings, everyone should speak the same language: revenue. 🧹 The Data Problem: Why RevOps Must Lead One of the biggest blockers to activating buying group strategies is messy, siloed data. Marketing tools hoard information. Sales tools don’t sync well. And critical insights never make it to the opportunity record. The solution? A strong Revenue Operations team. “I’ve surrendered. Marketing Ops now sits in RevOps—and that’s a good thing. RevOps should own the data foundation.” Clean data doesn’t just support GTM alignment—it powers AI and automation. And as Sydney warns, “Bad data trains bad agents.” 🚀 Final Takeaways: Winning with Buying Groups Buying groups are real—and they convert better. Track and engage multiple stakeholders early. Use intent signals across data types. Build workflows that treat G2 comparisons and pricing page visits as bottom-of-funnel signals. Go beyond ABM. Focus on micro-segments to tell sharper, more personalized stories. Align GTM with shared KPIs. Eliminate the MQL silo and focus on revenue outcomes. Fix your data. Clean, enriched CRM data is essential for sales, marketing, and AI. Want to build a buying group motion that works? Start by getting your GTM teams aligned, your data house in order, and your content strategy laser-focused on each persona in the buying network. And if you’re still chasing MQLs, it might be time to hit pause—and rebuild for the way B2B buying actually works today. Want to hear more stories from revenue leaders? Subscribe to The

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Podcast Individual Post

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Welcome to The Revenue Lounge Align Teams for ABM Success This way you can see for yourself all that we have to offer. Schedule Now. Description This is a heading This is a subheading to go more in detail about the heading. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.”   Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.”   Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.” Facebook Twitter Youtube Subscribe email to get news & updates Am fined rejoiced drawings so he elegance. Set lose dear upon had two its what seen held she sir how know.

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Account-Based Marketing vs. Lead Generation: Why It’s Time to Rethink Your Strategy

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Account Based Marketing vs Lead Generation: Why It’s Time to Rethink Your Strategy A conversation with Kristina Jaramillo, President at Personal ABM. In today’s B2B world, account based marketing vs lead generation isn’t just a battle of tactics—it’s a clash of mindsets. While lead generation focuses on volume and filling the top of the funnel, account-based marketing (ABM) is about precision, alignment, and long-term revenue growth. But here’s the catch: many companies think they’re doing ABM when they’re really just putting a shiny label on their old lead-gen playbooks. According to Kristina Jaramillo, President of Personal ABM, true ABM is not a campaign—it’s a strategic transformation. Facebook Twitter Youtube The Problem: ABM is Misunderstood and Misapplied “ABM isn’t just better targeting. It’s a company-wide go-to-market strategy that aligns marketing, sales, customer success, and product around shared revenue goals.” Most organizations jump into ABM by identifying a list of accounts, defining a few goals, and layering campaigns on top of existing demand gen efforts. But they fail to rethink their content, messaging, team structure, or go-to-market motions. In essence, they’re doing targeted lead generation, not ABM. Element Lead Generation Account Based Marketing Goal Generate as many leads as possible Land and expand strategic accounts Measurement MQLs, form fills, engagement rates Stage progression, win rates, NRR Ownership Primarily marketing Cross-functional: Sales, Marketing, CS, RevOps Approach One-to-many campaigns 1:1, 1:few, or 1:many with personalization Content Generic and persona-based Account-specific and insight-driven Why ABM Often Fails to Deliver Revenue Here’s what Kristina sees time and time again: Companies treat ABM as a bolt-on tactic, not a fundamental shift. Sales and marketing aren’t aligned on account selection, goals, or success metrics. The program lacks executive sponsorship and cross-functional ownership. Teams don’t tailor messaging to strategic priorities or address the status quo bias in buying committees. ABM is measured with tactical metrics like MQAs, not business outcomes. ABM can’t be delegated to a single marketing manager or retrofitted to an existing funnel. It has to be designed to solve the biggest revenue problems—whether that’s breaking into enterprise accounts, reducing churn, or expanding current customers. https://www.youtube.com/watch?v=oFc4f34PJpg A Better Approach to ABM: Start With the Revenue Gaps Kristina’s team begins every ABM engagement by identifying where the revenue leaks are: Are we losing to competitors we should beat? Are customers churning after a short term? Are we unable to move upmarket? Once the problem is clear, the strategy follows: Align sales, marketing, CS, and RevOps around shared objectives. Redefine the Ideal Customer Profile (ICP) based on high-value customers. Develop account-specific messaging tied to strategic business priorities. Focus on internal buyer enablement, not just external outreach. Track meaningful KPIs like deal velocity, ACV growth, and multi-threading success. “ABM is not about the next deal. It’s about driving the greatest revenue streams year over year.” Don’t Just Buy Tech. Build Strategy First Intent platforms like 6sense and Demandbase have become synonymous with ABM—but Kristina cautions against this mindset. “ABM tech doesn’t equal ABM strategy. Buying a platform doesn’t fix broken processes or align your teams.” Intent data only reflects current behaviors—it’s speculative, not predictive. It doesn’t tell you if the account is culturally aligned, ready for change, or worth pursuing. Tech should enable a strategy—not define it. Real-World Proof: How Messaging Changed Everything Kristina shared the story of a freight analytics company struggling to expand deal sizes. Their content was aimed at transportation managers—the platform users—not decision-makers. Their main competitor even offered a similar solution for free. By shifting the messaging to show how their platform integrated with demand forecasting, inventory management, and margin protection, they repositioned their value for C-suite leaders. That shift helped them land and expand accounts on Gartner’s Top 25 Supply Chain list. Metrics That Matter in ABM To measure ABM success, forget MQLs. Kristina recommends focusing on: Stage progression ACV growth Win rates against competitors Engagement with C-suite buyers NRR (Net Revenue Retention) “If your ABM isn’t improving deal size, win rate, and retention—you’re not doing ABM.” Final Thoughts: Time to Kill the Triangle One of Kristina’s boldest takeaways? It’s time to ditch the outdated ABM pyramid. The one-to-many → one-to-few → one-to-one model is too rigid and siloed. Instead, think of it as a dynamic funnel, where high-fit accounts earn deeper personalization based on engagement, strategic fit, and growth potential. TL;DR: Account Based Marketing vs Lead Generation ABM isn’t an evolution of lead gen—it’s a fundamentally different strategy. ABM focuses on revenue, retention, and relationship building, not just pipeline. True ABM requires executive sponsorship, team alignment, and account-specific engagement. Tech alone won’t save you—strategy must come first. Kill the pyramid. Build programs that are integrated, adaptive, and focused on the entire account journey. Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources

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From MQL’s to Buying Groups: Reltio’s Success Story

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From MQLs to Buying Groups: How Reltio Transformed Its GTM Strategy A conversation with Eric Cross, CRO at Reltio. For years, revenue teams have leaned heavily on the MQL. It was the industry-standard metric for marketing success—and the lifeblood of pipeline generation for B2B companies. But in today’s world of complex buying decisions, anonymous research, and multi-threaded stakeholder involvement, the MQL is failing. The old playbooks simply don’t map to how enterprise buyers actually operate today. Eric Cross, Chief Revenue Officer at Reltio, saw this firsthand. And rather than trying to force-fit modern buyers into outdated systems, he and his team made a bold move: they rebuilt their entire go-to-market motion around buying groups. This wasn’t a pilot. It wasn’t a small A/B test. It was a company-wide transformation executed in just 60 days. And the results were staggering: 60% reduction in pipeline attrition 22–23% improvement in average time to close 20% increase in average deal size Best-in-class competitive win rates In this blog, we’ll walk you through exactly how Reltio made this shift—from early warning signs to full implementation, change management, technology, and metrics. If you’re a RevOps, Marketing, or Sales leader evaluating your next GTM evolution, this is the playbook. Facebook Twitter Youtube Spotting the Cracks: Why the MQL Model Wasn’t Enough Eric joined Reltio in 2020 and began evaluating the revenue engine. The data told a troubling story. “We had a legacy demand gen model: leads to MQLs, then into pipeline, and hopefully into opportunities. But once deals entered the pipeline, we were evaporating 35–40% of them in the first two stages. That was alarming.” The consequence? The pipeline looked deceptively healthy on paper, but in reality, a significant chunk was never going to close. “We were creating a false sense of security about how healthy our pipeline was. That was the catalyst for change.” Realignment Begins: “Sales Owns Marketing, and Marketing Owns Sales” The first step wasn’t tactical—it was cultural. “Most companies operate in silos. Sales blames marketing. Marketing blames sales. I had to rewire that thinking completely. We stopped talking about ‘sales’ and ‘marketing.’ We became one GTM team. Sales owns marketing. Marketing owns sales.” To build consensus, Eric organized a two-day offsite with cross-functional leaders from Sales, Marketing, Product, Customer Success, and Ops. “It wasn’t just a marketing and sales decision. This had to be a company decision. We locked the team in a room and said, ‘We’re walking out of here aligned.’” The team was instructed to prepare: A brief problem statement Recommended actions A vision for a new GTM model And they debated—openly and intensely. “You get highs and lows during a session like that. But we made a rule: we don’t have to agree, but we do have to commit. We were either all in or not doing it at all.” https://www.youtube.com/watch?v=xKosC5cYEpU&t=430s Burning the Boats: Why Reltio Didn’t Pilot the Buying Group Model One of the boldest decisions Reltio made was to roll the new model out across the company—not as a pilot. “Pilot programs signal you’re not committed. People think: ‘This is an exercise, I don’t have to change.’ I’ve never seen a pet project like that succeed. So we said: all in, or not at all.” That decision came with high stakes. “I told our CEO, ‘This will either be a game-changer—or you’ll be looking for a new CRO.’” But conviction won out. The team moved forward with full executive and board-level awareness and support. Why Buying Groups? Understanding the Strategic Shift Eric’s rationale for abandoning MQLs in favor of buying groups was rooted in today’s B2B buying behavior. “Enterprise buyers don’t raise their hand right away. They stay anonymous for 60–70% of the buying journey. By the time they engage, they’ve already formed a direction.” This made traditional lead generation—like cold calls and webinar follow-ups—ineffective. “We’re in the era of the great ignore. Buyers get 30 spammy emails a day. They can see automation a mile away. We needed to earn attention earlier, smarter.” The solution? Use intent data to identify surging accounts Personalize outreach for each persona within a buying group Focus on qualified engagement from multiple stakeholders, not just one lead “It’s no longer about how many people we reach. It’s about reaching the right people—the ones who matter to the deal.” The 60-Day GTM Overhaul: From Planning to Execution Eric broke the transformation into three phases: 1. Design and Planning Finalize buying group motion Align teams on definitions, personas, and ICP Redefine opportunity entry/exit criteria Introduce Forrester to validate and refine the strategy “We brought in Forrester to spend half a day with us. They stress-tested our approach and made some great suggestions we incorporated.” 2. Development and Testing Align tech stack: Salesforce, 6sense, Salesloft, Outreach Build ABX dashboards for AEs and BDRs Re-architect sales stages and qualification frameworks (BANT, MedPIC) “We created dashboards where reps could see all their accounts and intent signals. The lightbulb went off—they’d never had visibility like that before.” 3. Production Launch and Measurement Rolled out company-wide in 60 days Quietly tested with one regional team for early signals Measured success using pipeline quality, velocity, and conversion benchmarks Overcoming Resistance: How Reltio Won Buy-in from the Frontlines The biggest challenge? Change management among AEs. “The top objection? ‘Just get me meetings. I’ll take it from there.’ That mindset doesn’t work anymore.” To drive adoption, Eric: Ran listening pods with small AE groups Invited feedback to poke holes in the strategy Used individual performance data to show why change was needed “We showed them their personal conversion rates. Some were below 20%. Even if they were hitting quota, it was clear the system was broken.” While 80% of reps leaned in, 20% resisted. In a few cases, Eric made the hard call. “If you can’t get on board, we’ll reassign your accounts. This isn’t optional.” Redefining Metrics: What Success Looks Like in a Buying Group World Reltio stopped measuring MQLs and switched to two key indicators: 1. Pipeline Quality Entry

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The Marketing Efficiency & Attribution Playbook: What Today’s CMOs Are Tracking

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The Marketing Efficiency & Attribution Playbook: What Today’s CMOs Are Tracking RevOps 10 min Marketing attribution and efficiency metrics are becoming more critical than ever. CEOs want to know how to allocate budgets effectively across marketing, sales, and product. Investors seek clear insights into ROI. And marketers themselves need to track performance by channel and initiative to optimize their efforts. Yet, in B2B marketing, where deal cycles are long and touchpoints span multiple teams, tracking and proving marketing’s true impact is easier said than done. A recent Marketing Budget Benchmark Study by Ray Rike, Jon Miller, and Bill Macitis reveals key insights. sheds light on how top B2B marketers are approaching efficiency and attribution. Let’s explore key takeaways and how you can apply them to your own marketing strategy. What are CMOs Tracking? The Top 3 Metrics When asked about their top three performance metrics, CMOs consistently focused on: Pipeline Generation – Ensuring a steady flow of qualified leads for sales teams. Annual Recurring Revenue (ARR) – Measuring the long-term revenue impact of marketing efforts. Marketing Qualified Leads (MQLs) – Tracking lead volume and initial qualification. Notably absent from the top three were cost-related efficiency metrics, such as cost per opportunity or customer acquisition cost (CAC). This suggests that many marketing leaders are still primarily focused on volume rather than efficiency—raising the question of whether marketing investment is being optimized for maximum impact. Why Efficiency Metrics Matter While pipeline and ARR are crucial, failing to measure marketing’s efficiency can lead to wasteful spending and missed opportunities. The study revealed that larger companies tend to measure: Cost per Dollar of Pipeline – Connecting marketing spend to potential revenue. Marketing Cost per New Customer (New Logo Revenue) – Assessing acquisition efficiency. Cost of Expansion Revenue – Tracking marketing’s role in upsells and renewals. Interestingly, cost per expansion revenue remains under-tracked in many organizations, despite its importance in retention and growth strategies. In many cases, marketing’s contribution to expansion revenue is undervalued compared to account management teams.   Attribution Models: What’s Working and What’s Not Accurately attributing revenue to marketing efforts remains one of the biggest challenges in B2B. The benchmarking data highlighted five primary attribution models: First-Touch Attribution – Identifies the first interaction a prospect had with the brand. While useful for understanding top-of-funnel performance, it overlooks the full buyer journey. Last-Touch Attribution – Credits the final touchpoint before conversion. This model can be misleading, often over-attributing conversions to channels like paid search or SDR outreach. Multi-Touch Attribution – Allocates credit across all touchpoints in the buyer journey. While comprehensive, it often struggles to account for offline influences and brand awareness efforts. Marketing Mix Modeling (MMM) – Uses statistical analysis to measure the impact of different marketing activities. This approach requires significant data and investment, making it more common among large enterprises. A/B Testing – While not a full attribution model, controlled experiments can help validate the impact of specific marketing strategies. How Attribution Matures with Company Growth As companies scale, their approach to attribution evolves: Early-Stage Startups (<$5M revenue) – Often track deals manually, analyzing each conversion on a case-by-case basis. Pre-Scale Companies – Rely heavily on inbound metrics, focusing on organic sources like referrals and word-of-mouth. Scaling Companies – Experiment with first- and last-touch models but face growing pains in attribution accuracy. Mature Companies – Use multi-touch attribution combined with first- and last-touch insights to inform strategy and budgeting. Despite its potential, Marketing Mix Modeling remains underutilized in B2B tech, with adoption still below 10%. However, as organizations gather more data and refine their analytics capabilities, this approach may gain traction. The Future of Marketing Measurement To build a more efficient marketing function, leaders should move beyond simple volume metrics and embrace a more holistic approach: Adopt Blended Cost and Revenue Metrics – Instead of just tracking cost per pipeline, measure cost per revenue to better justify budget allocation. Use Multiple Attribution Models – No single model provides the full picture. A combination of first-touch, last-touch, and multi-touch insights offers better visibility. Prioritize Expansion Revenue Tracking – Marketing plays a key role in customer retention and upselling. Failing to measure its impact means missing a major component of revenue growth. By focusing on both pipeline growth and efficiency, marketing teams can drive stronger results and make a more compelling case for continued investment. Bhaswati Director of Content Marketing at Nektar.ai, an AI-led contact and activity capture solution for revenue teams. With 11+ years of experience, I specialize in crafting engaging content across blogs, podcasts, social media, and premium resources. I also host The Revenue Lounge podcast, sharing insights from revenue leaders. In this blog

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Intelligent Sales Automation: How AI is Transforming Sales Processes

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Intelligent Sales Automation: How AI is Transforming Sales Processes RevOps 10 min Imagine this. You’re a sales rep juggling emails, follow-ups, and endless data entry. Your coffee is cold, your CRM is a mess, and before you know it, half your day is gone, with barely any actual selling done! Sounds familiar? You’re not alone. Sales studies reveal that professionals only sell 22% of the time. The rest goes to manual tasks. The result? Missed opportunities, slow sales cycles, and lost revenue. What if you had a super-powered assistant? It could handle the dull tasks, study customer behaviour, and forecast future sales trends. Intelligent Sales Automation does just that, using the magic of AI sales tools. By leveraging automation, businesses can streamline operations, boost efficiency, and maximize sales performance. This guide looks at the benefits of smart sales automation. We’ll share real-world examples and show how AI is changing sales strategies for success. What is Intelligent Sales Automation? Intelligent sales automation uses AI, machine learning (ML), and data analytics to automate repetitive sales activities. To optimize decision-making, these technologies analyze customer interactions, CRM systems, and market trends. Integrating AI sales tools lets businesses generate more leads, personalise interactions, and raise conversion rates—all without manual effort. How AI Enhances Sales Automation Artificial Intelligence (AI) has revolutionised the sales landscape. Here’s how AI-driven sales tools are making an impact: Customer Data Analysis: AI analyses sales conversations to identify trends and buying patterns. Predictive Sales Forecasting: Machine learning models provide accurate revenue predictions. Automated Email Sequences: AI personalizes follow-up emails based on customer behavior. Lead Scoring & Prioritization: AI ranks leads based on conversion potential. Chatbots for Instant Support: AI chatbots engage prospects and answer queries in real time. AI in sales is growing at an exponential rate, with adoption expected to surge by 139% between 2020 and 2023. Companies using AI-driven automation are finding a competitive edge. They boost efficiency and make sales cycles faster. 7 Powerful Use Cases of Intelligent Sales Automation 1. CRM Data & Contact Automation The Problem: Sales representatives spend a significant amount of time manually entering and updating customer data in CRM systems. In fact, 71% of sales reps cite manual CRM entry as a major time drain, leading to inefficiencies and lost selling opportunities. The AI Solution: AI-powered CRM automation streamlines data entry by capturing key customer details automatically. These intelligent tools extract information from emails, meeting notes, and other customer interactions to populate CRM fields accurately. This not only reduces manual errors but also ensures that sales reps have the most up-to-date customer insights at their fingertips. As a result, teams can spend more time engaging with prospects and closing deals rather than on administrative tasks. 2. AI-Driven Lead Management The Challenge: Generating leads is only the first step—effectively managing them determines conversion success. Companies that implement high levels of sales automation see a 16% increase in lead generation. However, manual lead qualification and follow-up can result in inefficiencies and lost opportunities. The AI Solution: AI-powered lead management takes the guesswork out of lead prioritization. Advanced algorithms assess lead behavior, engagement patterns, and historical data to score leads based on their likelihood to convert. Automated nurturing sequences then ensure timely and personalized follow-ups, keeping prospects engaged throughout the sales funnel. With AI handling lead segmentation and prioritization, sales teams can focus on high-value opportunities, boosting conversion rates. 3. Intelligent Sales Forecasting Why It Matters: Accurate sales forecasting is critical for business planning, resource allocation, and revenue growth. Yet, many sales teams struggle with imprecise forecasts due to reliance on outdated methods or incomplete data. The AI Solution: AI-driven forecasting analyzes historical sales data, market trends, and customer behaviors to generate highly accurate sales predictions. These insights allow sales leaders to make informed decisions regarding inventory, staffing, and revenue goals. AI also continuously refines its predictions by learning from new data, ensuring forecasts remain relevant and reliable over time. 4. AI Chatbots for Customer Support The Trend: AI-powered chatbots have experienced a 92% growth since 2019, highlighting their increasing role in customer interactions. The AI Solution: AI chatbots provide 24/7 support, instantly answering queries, assisting with product recommendations, and resolving customer concerns. These bots use natural language processing (NLP) to understand customer intent and deliver personalized responses. By handling routine inquiries, chatbots free up human sales agents to focus on complex, high-value conversations, ultimately improving customer satisfaction and efficiency. 5. Personalized Email Campaigns The Challenge: Generic email campaigns often fail to capture customer interest, leading to low engagement and poor conversion rates. The AI Solution: AI-driven email automation creates hyper-personalized content based on customer preferences, purchase history, and behavioral data. These intelligent systems craft subject lines, body text, and call-to-actions tailored to each recipient, significantly increasing open rates and conversions. By optimizing send times and content relevance, AI ensures that prospects receive the right message at the right time. 6. AI-Powered Sales Analytics The Insight: Understanding customer behavior and sales performance is key to refining strategies and boosting revenue. The AI Solution: AI sales analytics tools track sales trends, customer interactions, and conversion rates in real-time. These insights enable sales teams to identify successful tactics, pinpoint weaknesses, and adjust their strategies accordingly. AI also provides predictive analytics, helping businesses anticipate customer needs and proactively address market changes. 7. Sales Gamification for Performance Boost The Stat: A whopping 90% of employees say gamification improves their productivity, making it a valuable tool for sales motivation. The AI Solution: AI-powered gamification systems track sales performance, rewarding top performers with incentives, leaderboards, and performance-based challenges. These systems create a competitive yet engaging environment that motivates sales teams to achieve their targets. By integrating AI insights, gamification strategies can be customized to match individual and team goals, fostering a culture of continuous improvement. How Intelligent Sales Automation Benefits Businesses Let’s look at how sales automation actually benefits businesses:   1. Automates Repetitive Tasks The Impact: Businesses can automate over 30% of sales activities, significantly freeing up time for strategic selling. The

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Configure Contact Roles on Salesforce to Unlock Immediate Efficiency Gains

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Configure Contact Roles on Salesforce to Unlock Immediate Efficiency Gains Discover how defining OCRs can enhance visibility into your buying committee, improve sales execution, and boost win rates. RevOps 10 min Let’s begin by simply defining what is an opportunity contact role (OCR). An OCR is a standard object on Salesforce within the Opportunity object that links Contacts to Opportunities, specifying the Contact’s role in that Opportunity. Having great OCR hygiene means sales leadership teams gain better visibility into the buying committee for each opportunity. Better visibility helps monitor if reps have at least identified the necessary people needed to win the deal. If the necessary people are involved, then sales leaders can guide their teams on the right engagement playbook to navigate the deal toward success. While sales teams know the importance of identifying and engaging the entire buying committee, not many follow this through to execution. This becomes worse when we consider the OCR data available in a CRM. Open any CRM today, and you will notice that a majority would have an average of 3 contact roles. Of those 3, one is usually a required field made mandatory by the revenue/sales operations or CRM admin. In companies that practice MEDDIC (and its variations), the ‘Economic Buyer’ and ‘Champion’ are identified and added to the CRM, but the remaining buyer roles are either identified but not added to the CRM or not identified at all. So why should OCRs matter? The answer to this question lies in whether or not you’re working on improving sales execution, rep efficiency, win rates, and forecasting. You’d be surprised if we told you how often we hear prospects say “We have no idea who our sellers are talking to” or “We don’t know how often we’re engaging buyers in open deals”. ‘Who’ you are talking to and ‘how often’ are you talking to buyers are the fundamental units of generating revenue. The ‘process’ of generating revenue can only be improved by tracking and measuring such fundamental units. You may be doing a great job with creating contact lists from third-party data tools like Zoominfo or Lusha or by auto-creating contacts in accounts with tools like Clari or Gong, but if such contacts are not being linked to opportunities, you are losing out on critical data. Technically, in CRM terms, opportunities are won, not accounts. And so having contact data is not good enough. You must aim to have granular and comprehensive contact role data. Introducing Configurable OCRs Using AI, automation, and graph inference, Nektar automatically creates contacts in the relevant accounts present in Salesforce. Until recently, Nektar would automatically associate these contacts as OCRs within the relevant open opportunities. There was no configuration needed. However, through customer feedback and research, Nektar is excited to announce ‘Configurable OCR’. An OCR record is only useful if it is: associated because it is actually involved in the deal a buying role was identified and assigned to it With configurable OCR, you can define rules using buyer-seller engagement data that Nektar has already added to the (open) opportunity and account. For example, a rule can be: “If engagement with contacts in an account is more than 5 times in the last 10 days, and if there is an open opportunity in those accounts, then associate such contacts as opportunity contact roles.” This example considers the recency and frequency of buyer engagement. So, only those contacts that are frequently engaged by the seller will get added to opportunities as OCRs. As a result, sales leaders gain instant visibility into who is actually involved in deals. This is just a simple, straightforward example of a rule. You can define your own rules. Additionally, you can customize the rule for the different segments you may have. For example, have a rule specifically for strategic accounts, expansion accounts, new business accounts, vertical-specific accounts, or any other segmentation you may have. Next, you can configure the second component – the buying role. If you’ve used Nektar, you would know that it extracts job titles from email signatures. A default capability we’ve always offered is to map out job titles to the respective buying roles. With this one-time configuration, as and when Nektar links OCRs, it also assigns a buying role to the OCR based on the corresponding job title. Now, using genAI automation you can define rules to assign an appropriate buying role. You can consider a combination of job titles and engagement trends, job titles and seniority, job titles and engagement and segment – whichever factors address your requirements. After all, the process of generating revenue is unique to a company. The best part is that all this is done using the standard Salesforce records, so they are easily reportable on Salesforce. This can also be achieved for your historical opportunities by backfilling them. Benefits of configurable OCRs Nektar customers use this OCR data for deal inspections, win-loss analyses, playbook optimization, and enhancing their multithreading strategy. Every opportunity has only those contact roles that are involved in the deal while the remaining stakeholders such as legal remain in the account as contacts. So sales leaders are able to monitor which job titles and buying roles are being engaged. Since historical data is also plugged in, you can study buying committee engagement for won and lost deals to analyze what worked and did not work. Some of our customers identified new personas in their closed deals, and have now started prospecting this persona actively to generate new pipeline. By studying won deals, you can also track the engagement pattern and work towards improving your multithreading strategy. Lastly, playbooks can be transformed. For example, one of our customers now has made it mandatory to have a specific number of contact roles if the deal is in stage 3 of the sales process. Similarly, answers to who, how often, and when should different people of the buying committee be engaged can be detailed out. Outside of the sales team, a clean and

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Revenue Leader Caroline Holt on Putting Together the Best Sales Tech Stack

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Revenue Leader Caroline Holt on Putting Together the Best Sales Tech Stack RevOps Sales Techstack 10 min Extracting value from a sales tech stack continues to be a frustrating challenge for revenue leaders. Budget freezes across the board have forced revenue leaders to be more mindful of the tools they add to their tech stack. But it can be a daunting project to undertake with the market being so crowded with tools across multiple categories.How can revenue leaders select the best tools for their tech stack? How can they derive value from this steep investment? And how can they make their sales teams more productive? We sat down with Caroline Holt, VP Revenue Training & Enablement at Bonterra, to unpack some of these nuances around creating the best sales tech stack. Caroline shares some brilliant insights on how revenue leaders can create the best sales tech stack. And make the process more efficient and effective. If you’re short on time, here is a quick summary of the conversation.   If you enjoy our discussion, check out more episodes of our podcast. You can follow on iTunes, Spotify, YouTube or grab the RSS feed in your player of choice. What follows is a lightly edited transcript of the episode. The Sales Tech Landscape Has Exploded & Disrupted Sales   Abhijeet: Caroline, thanks for coming on the show. Caroline: Thank you so much for having me. Abhijeet: You’ve been in the sales tech industry for quite some time. How have you seen it change over the last few years? Caroline: Well, it has not only transformed. But it has exploded, right? Technology has disrupted sales. I think the buying process in some cases has not changed over the last 20 years, but the way we sell and the way that the buyer wants to purchase has changed. So when I think about my role as a BDR early on, I was calling, I was faxing, I was emailing. But I could get to someone typically. And I think in some cases the proliferation of things like cadence tools that allow people to drop somebody into a constant flow of information has actually hindered our ability to get to people that we want, who might actually need what we need to do. So to the overarching question of how technology has changed, I think in some ways it’s changed in a really incredible way. Because I am an efficiency geek. I like removing friction from the sales process. But I think that sometimes we actually get in our own way because of how we purchase technology. I think of the tech stack in terms of where your business is and what you need to be successful. And I think that’s actually the biggest challenge right now. The first thing that I would say is that when you think about technology, it’s a great solution if you have a really good process to start with. And people to manage the automation, ongoing configuration, updates, maintenance, and so on. CarolineHolt VP, Revenue Training and Enablement Technology is going to be great at a foundational level. So the first thing you need is a way to engage with people, whether that is your regular old telephone and email, or whether that is some sort of a dialer tool where you’re capturing that information. And then you need some place for that information to live. So you need some sort of CRM to be able to capture that information, figure out who you’ve been talking to, what that’s been like, if you’re opening opportunities, what that opportunity looks like. Then you need to figure out what’s actually happening in those calls.  And then that you can analyze a lot of that data over time in terms of what people are saying in aggregate. So our whole roadmap should be focused on it. It  provides just a really powerful level of insight. But I think for a lot of organizations, they don’t ever optimize those parts of the tech stack, and then they start adding new stuff. They either haven’t gotten it right the first time, or they think that that’s table stakes.  That foundational piece, particularly the architecture around the CRM, if that stuff isn’t right, none of the other tech is really that helpful because you wind up buying stuff and building stuff that doesn’t really help that whole flow from who are we talking to, what are we talking to them about, what’s happening with those deals to closing those deals. Caroline Holt VP, Revenue Training and Enablement So that’s a really simplistic way of thinking about sales technology. But I would say that most organizations need to start with those fundamental pieces and then start thinking about, okay, once we know, now we need to figure out who those prospects are. So what sort of technology is gonna help us identify who those folks are. So how you build that stuff over time becomes really powerful. And then what you do with that data and analytics becomes really powerful over time. But sometimes people invest really quickly in a lot of technologies, but they never really optimize them for performance. So the other part is just thinking about having what you can actually bite off in terms of tech investments in any given year to be able to do the right thing for your business.  Where is Sales Tech Heading Towards?   Abhijeet: If you don the hat of a sales leader who’s going to spend a hundred dollars this year across the technology stack, how should they go about their investment approach? Where should those a hundred dollars be allocated?  Caroline: So I would say that like everything in enablement or any of the back office operations, it’s where are your problems? So if the business should be investing based on what technology is going to actually help them be more effective, where they’re less effective than they could be today. So

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Welcome Efficiency Gains in 2025 with a Suite of Meeting Insights Built for Revenue Teams

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Welcome Efficiency Gains in 2025 with a Suite of Meeting Insights Built for Revenue Teams Product 10 min Imagine you’re preparing for a 42 km marathon. You’ve set a weekly running plan across terrains and weather conditions. You’ve brought the best equipment – wind-resistant clothing, a sleek water pouch, well-fitted goggles, perfectly cushioned shoes with the right grip, and a pace calculator. There were days when you completed 42 km, there were days you only did 5 km, and there were days you did 25 km, and so on. But, throughout your preparation, the pace calculator unfortunately missed capturing your pacing and the time taken to run the distance. Oops! Now, you have no idea what is the average time you take to complete 42 km or what is your average pace. So you’re going in blind and decide to pace yourself by winging it. Yes, this blog is not about preparing for a marathon. But this example is an analogy to sales. The runner is the revenue leader. The equipment refers to the sales team and tools. Each run refers to a meeting with a buyer. The pace calculator refers to a tool that is meant to provide key insights – what are you doing well, and what you should improve. So, with the analogy and this context, let me challenge you with some questions: How many meetings does it take your SMB and your enterprise teams to win a deal, respectively? How many meetings get completed out of all the scheduled meetings? How often are meetings happening in each of your accounts? How often are the different members of the buying group invited to these meetings? How often are these buying group members attending these meetings? What is the nature of the meeting? What is being discussed exactly? How much time is being spent or wasted in meetings by your sellers and deal support team like solution engineering, executives, etc.? Sure, conversation intelligence tools may help answer a couple of these questions. But, not all. Moreover, most conversation intelligence tools only capture data if they’re set to record that meeting. If it’s not set to record, then the data does not get captured. And before you jump to a conclusion, no, this is not a blog on conversation intelligence. Rather it’s about zooming into your buyer-seller data with a specific focus on meeting insights. Meeting Insights Missing from Your Engagement Data Over the last two quarters, Nektar introduced several useful features that surface insights into buyer-seller engagement. Some of them are specific to meeting data. These insights are 100% accurate because they stem from data picked up at the source of action – your calendar invites, be it Google or Outlook. What’s more? All the data is provided to you in your standard Salesforce objects – account, opportunity, contact, and lead. So you can leverage Salesforce’s powerful reporting capabilities to surface these meeting insights. Let’s dive into some insights that Nektar.ai unlocks through these recently launched features. 1. Meeting Status Every week revenue leaders conduct 1:1 deal reviews where the rep shares with them all the meetings that are scheduled, that took place, and that got canceled or rescheduled. Additionally, the rep also has to share who is invited to the meeting and who attended. The revenue leader then suggests adding a key stakeholder, and the dialogue continues. With Nektar, this ‘zero value information exchange’ can be eliminated. Instead, revenue leaders can access such data in their Salesforce. Nektar automatically marks the status of a meeting across the meeting lifecycle – scheduled, completed, aborted, canceled, missed – to give deep visibility into how meetings are impacting sales cycles, win rates, and revenue generation. The most important question this helps answer is: How many meetings do I need to complete to win an enterprise deal and an SMB deal, respectively? This can be further segmented at an industry or region level for further granularity. Layer Meeting Status with additional factors to unlock clear visibility into deal activities and understand what’s working and not working. 2. Meeting Type Let’s assume an enterprise deal had 55 meetings from creation to close. With Meeting Status you will easily know how many were completed. You may also choose to use native Salesforce reporting to slice this data across deal stages. The only insights you have are that 55 meetings were scheduled, 40 were completed, and each deal stage had a specific count of meetings. But, you’re still not sure what each meeting was about. Was it a demo meeting, a discovery meeting, a use case mapping meeting, a mutual success plan meeting, a proof of concept discussion meeting, or something else? And how many such meetings took place? This is where Activity Tagging becomes beneficial. Nektar automatically assigns tags to meetings based on the context of the meeting using certain keywords. This tag is then automatically added to a custom field on Salesforce within standard objects, making it completely reportable. Equipped with this data point, revenue leaders can easily spot what types of meetings are taking place and how many meetings of the same type are taking place. Most importantly, you can define these tags yourself. For you, you may define one of the tags as ‘use case mapping’, while another company may not. Or, you may have defined only 4 tags while another company may have defined 12 tags. It’s easily customizable to suit your revenue process. Going back to the example we started with, you’ll have the following insights – 55 meetings were scheduled, 40 were completed, 3 discovery meetings, 5 demo meetings, 3 use case mapping meetings, and so on. This insight helps you gather which types of meetings are critical to winning a deal. For example, if deals over $100,000 had more use case mapping meetings and deals less than $50,000 had more negotiation meetings, you can now optimize your plays to replicate this more often to improve your chances of winning deals. Activity tags are customizable. Based on your sales process,

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What is Salesforce Tech Debt? And How Can You Reduce it?

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What is Salesforce Tech Debt? And How Can You Reduce it? RevOps 10 min In a recent statement, Salesforce disclosed its intention to raise list prices across several product offerings, including Sales Cloud, Service Cloud, Marketing Cloud, Industries, and Tableau, with an average increase of 9%. Starting in August 2023, the revised list prices for certain Salesforce products will be implemented, targeting new customers and existing customers acquiring additional cloud services. Salesforce has outlined the following adjustments in pricing for their fundamental Sales and Service Cloud offerings: Professional Edition will increase from $75 to $80 Enterprise Edition will increase from $150 to $165 Unlimited Edition will increase from $300 to $330  These changes are going to affect a lot of organizations. Over 150,000 companies across industries use Salesforce. With specialized solutions for operations across sales, service, marketing, and commerce, it is no wonder that the hike in price would affect almost every industry. For companies using Salesforce, the major concern is: Salesforce Tech Debt.  What is Salesforce Technical Debt? Technical debt refers to the expense of having to do extra work later on due to opting for a quick solution in the present rather than investing the time in a more optimal approach. This concept is also commonly referred to as “Shift Left,” which emphasizes the idea that the sooner you identify and address issues, the more cost-effective it is to resolve them. Technical debt represents the additional effort required to rectify a hasty, less-informed solution chosen in the present (constructed quickly without a deep understanding of business requirements), as opposed to adopting a more time-consuming but superior approach. In a broader sense, technical debt encompasses any customizations, whether through code or declarative means, that were implemented when standard functionality wasn’t suitable or accessible. Technical debt can also contain situations where solutions were initially designed for a specific purpose, but as business needs evolved over time, small adjustments were tacked on. A more constructive perspective on technical debt is to recognize that virtually everything can be considered a form of technical debt, but it’s termed “debt” because it necessitates future efforts to address and resolve. In the past, technical debt was primarily associated with developers taking shortcuts in their code. However, in the era of low-code platforms such as Salesforce, technical debt can arise not only from coding decisions but also from the configuration choices made through user-friendly “clicks” within the platform. What Causes Tech Debt? Salesforce technical debt arises from rushed or suboptimal development practices, including quick fixes, inadequate adherence to best practices, complex customizations without proper planning, and neglect to update and adapt solutions over time. This debt accumulates when shortcuts are taken, making future maintenance and scalability more challenging and costly. Here are a few factors that can cause technical debt: 1. Modified or outdated design This occurs when the business requirements change, rendering certain functionalities unnecessary. However, it’s often deemed safer to retain these functionalities. 2. New releases This arises when the introduction of new platform features surpasses the capabilities of previous releases or custom development efforts. For instance, Salesforce Flows are taking precedence over process builders and workflow rules. 3. Intentional technical debt When a deliberate decision is made to expedite development, fully aware that it will entail higher long-term costs, but it’s considered the appropriate course of action. 4. Unintentional technical debt Accumulates when shortcuts are taken for various reasons, typically due to time constraints or concurrent workstreams. 5. Tacked-on technical debt Occurs when a particular functionality is continually extended incrementally and “bolted on” to maintain its functionality rather than undergoing a proper reconstruction. Up to this point, we’ve delved into the theoretical aspects of technical debt, discussing its causes and mechanisms. However, what does it actually manifest as in real-world scenarios? Let’s have a look: Common Forms of Salesforce Tech Debt Common forms of Salesforce technical debt include the accumulation of unused customizations, outdated roles and permission sets, complex and undocumented workflows, inadequate data modeling, and the absence of thorough testing. This technical debt arises when shortcuts are taken or best practices are overlooked during Salesforce development, making the system harder to maintain and optimize over time. Several prevalent forms of technical debt can be identified In Salesforce, including: 1. Visualforce component vs sales path Before the introduction of Sales Path, organizations required a visual means to depict the progress of an opportunity stage or process. To achieve this, they had to customize a Visualforce component. However, with the release of Sales Path by Salesforce, these visualizations became standardized, which subsequently led to an increase in the technical debt interest rate. 2. Adapting process automation The creators of 10K recognized the necessity of automating their invoice generation process. They initially developed an hourly function to create invoices, incorporating some basic rules. However, as their contract structures evolved, they found themselves adding more functions to their initially straightforward task. Managing these changes became increasingly challenging, prompting them to allocate time to rewrite the process based on the current state of their business operations. 3. Excessive customization As previously mentioned, Salesforce provides a user-friendly environment for creating custom Objects and code, even when a simpler declarative solution would suffice. For instance, opting for a workflow instead of resorting to triggers for scripting tasks. This form of technical debt often arises from an overly responsive approach, where every requested change is implemented without exploring alternative options within standard configurations. 4. Unused customizations Despite being promoted as a ‘no-code’ platform, Salesforce cannot handle every task declaratively. Changes in business requirements may render customizations that were once essential unnecessary. Unless these customizations are retired, they can introduce inherent complexity to every new change and potentially hinder end user adoption by making your Org more challenging to navigate. 5. Access controls You’ve likely encountered the concept of “the principle of least privilege.” On the flip side, we have the “principle of most privilege,” where users end up with excessive access as their roles within the organization evolve. While other forms of technical debt can impede progress, retaining unused profiles and permission

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The Ultimate Guide to After-Parties at the Forrester B2B Summit 2023

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The Ultimate Guide to After-Parties at the Forrester B2B Summit 2023 ABM RevOps Sales Looking to take your networking and socializing to the next level at the Forrester B2B Summit 2023? Look no further!  We’ve curated a list of the hottest parties happening during the summit, ensuring you have a fantastic time while connecting with industry leaders, enjoying live entertainment, and creating lasting memories.  From poolside gatherings to VIP lounges and late-night soirees, these parties offer the perfect blend of business and pleasure. So grab your dancing shoes, bring your A-game, and get ready for an unforgettable experience! 1. Poolside Welcome Party by Bigtincan Dive into the Forrester B2B Summit with Bigtincan’s Poolside Welcome Party! Enjoy a relaxed and vibrant atmosphere, sip on refreshing drinks, and mingle with industry experts while taking in the poolside ambiance. Date: 4th June 2023Time: 5:30pm – 7:30pmVenue: Fairmont Poolside Terrace, 7th FloorMore Info Here. 2. Forrester Pre-party with Sequel Kickstart your Forrester B2B Summit experience with the exciting Forrester Pre-Party by Sequel. Connect with industry professionals, enjoy a relaxed and welcoming atmosphere, and get ready to network and engage in insightful conversations before the main event begins. Date: 4th June 2023Time: 6:30pm – 9:30pm CDTVenue: Zanzibar Rooftop Bar, 304 E Cesar Chavez St, Unit 700, Austin, TX 78701Register here. 3. Bombora VIP Brunch Start your day off right with the Forrester B2B Summit Brunch hosted by Bombora. Enjoy a delicious spread of gourmet food, connect with industry peers over a delightful meal, and fuel up for a day of learning, networking, and inspiration at the summit. Date: 5th June 2023Time: 8:00am – 9:30amVenue: The Four Seasons, 98 San Jacinto Blvd, Austin, TX 78701Register to Attend 4. Relax, Refresh, and Recharge with Demandbase Take a break from the conference and rejuvenate at the Smart Lounge. Unwind in a serene atmosphere, indulge in self-care activities, and refuel your energy with rejuvenating amenities and experiences, ensuring you stay at the top of your game throughout the Forrester B2B Summit. Date: 5th & 6th June 2023Time: 8:00am – 5:00pm CTVenue: 340 E 2nd St, Austin, TX 78701Save your seat 5. Sendoso’s VIP Happy Hour Elevate your networking experience at the exclusive VIP Happy Hour. Enjoy premium drinks, engage in strategic conversations, and connect with top industry influencers in a sophisticated and intimate setting, making it a must-attend event for forging valuable connections at the Forrester B2B Summit. Date; 5th June 2023Time: 6:45pmVenue: Zanzibar, 304 E Cesar Chavez St Unit 700, Austin, TX 78701Sign Up 6. Happy Hour and Networking at Half Step Bar by Showpad Raise a glass and connect with fellow professionals at the lively Happy Hour and Networking Event. Enjoy drinks, engage in meaningful conversations, and expand your network in a vibrant and collaborative environment, fostering valuable relationships at the heart of the Forrester B2B Summit. Date: 5th June 2023Time: 7:00pm – 9:00pmVenue: Half Step Bar, 75 1/2 Rainey Street Austin, TXSave your Spot 7. Hotness Happy Hour by Demandbase Spice up your networking experience with the Hotness Happy Hour. Savor tantalizing cocktails, engage in lively conversations, and connect with industry influencers in a vibrant and energetic setting, making it a memorable and dynamic part of your Forrester B2B Summit journey. Date: 5th June 2023Time: 7:00pm CTVenue: 340 E 2nd St, Austin, TX 78701Save your seat 8. Chill Time at the Forrester B2B Summit Enjoy some chill time at the Forrester B2B Summit at the Lucille Patio Lounge. Hosted by Stensul, MRP, Openprise, and Shift Paradigm, you can expect some delicious food and refreshing drinks in a fully private space. Austin’s very own Jo James is also scheduled to perform some live Texas blues music! Date: Monday, 5th June, 2023Time: 6:30pm – 8:30pm CTVenue: Lucille Patio Lounge, 77 Rainey Street, AustinRegister Here. 9. B2B: Brews & Bites Immerse yourself in a dynamic B2B event hosted by Knak. Engage in interactive sessions, gain valuable insights from industry experts, and discover cutting-edge strategies to elevate your B2B marketing game, making it an essential experience for attendees at the Forrester B2B Summit. Date: 6th June 2023Time: 4:30pm – 8:30pmVenue: Banger’s Sausage House and Beer Garden, 79 Rainey Street, Austin, TXGet on the Guestlist 10. Red Carpet & Private Concert by Bigtincan Get ready to rock out at the exclusive Private Concert during Forrester B2B Summit 2023! Experience an electrifying performance by renowned artists, dance the night away, and create unforgettable memories with fellow attendees. Enjoy cocktails, lively conversations, and forge new connections with industry professionals in a relaxed and informal setting. Date: 6th June 2023Time: 7:00pm – 10:00pmVenue: Austin Convention CentreMore Info Here. 11. Modern RevTech Happy Hour Join a Texas-style happy hour! Rather than just adding more tools to your sales and marketing team infrastructure – add the right, modern tools that work together. Join leaders from Highspot, Klue and Salesloft in a casual environment to learn more. Appetizers and drinks will be served. Date: June 6, Time: 5-7pmVenue: Vince Young SteakhouseRegister here.   With this exciting list of parties, the Forrester B2B Summit 2023 promises to be an event like no other. These parties provide the opportunity to unwind, build connections, and enjoy the vibrant atmosphere alongside like-minded professionals. We can’t wait to meet you there! Did we miss out on any event? Send a tweet to @ainektar and we’ll be sure to add it in. Meet the Nektar Team!  Come, say hello to the Nektar team (Jordan, Logan, Danielle, & Abhijeet). Whether it’s about after-parties, accelerating your revenue funnel or plugging CRM data gaps, we would love to chat.   Book a time here.

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What is Predictive Sales Analytics?

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What is Predictive Sales Analytics? Sales When it comes to weather forecasting, experts use historical weather patterns, current atmospheric conditions, and advanced technology to predict future weather. They anticipate whether it will rain, snow, or be sunny. The better their data points are, the better their predictions.  Similarly, Predictive Sales Analytics ​​examines past sales data, market trends, customer behaviors, and other factors to forecast future sales outcomes. This allows organizations to make informed decisions, allocate resources effectively, and tailor their sales strategies, much like how people adjust their plans based on the weather forecast to ensure a smooth day ahead. Let’s have a detailed walkthrough. What is Predictive Sales Analytics? Predictive sales analytics uses data, statistical algorithms, and machine learning techniques to forecast future sales outcomes and trends. The approach employs statistical modeling, data mining methods, and machine learning to detect patterns within diverse datasets. Predictive sales analytics studies historical sales data, customer behaviors, market trends, and other relevant factors, applying sophisticated mathematical models to forecast upcoming sales outcomes.  Predictive sales analytics has several features, including: 1. Data collection and preparation The process begins by collecting relevant data from multiple sources. This can include historical sales data, customer interactions, website activity, marketing campaigns, and external market trends. The data is then cleaned and organized to ensure accuracy and consistency. The quality of the data directly impacts the accuracy of predictions. 2. Feature selection In this step, the most important variables, also known as features, are identified. These features can include factors such as time of year, customer demographics, purchase history, marketing channel, and economic indicators. 3. Model building Predictive models are built using statistical algorithms and machine learning techniques. These models use historical data to establish relationships between the chosen features and the target variable, which is typically future sales. 4. Training and testing The built model is then trained using a portion of the historical data. This training process involves adjusting the model’s parameters to minimize errors and improve accuracy. The model’s performance is evaluated using testing data that the model has not seen before. This step helps ensure that the model can generalize its predictions to new data. 5. Prediction and analysis Once the model is trained and validated, it is ready to predict future sales. It takes new data inputs, such as current market conditions and customer behaviors, and generates forecasts based on established patterns. 6. Actionable insights The predictions generated by the model provide actionable insights for businesses. These insights can include forecasts of future sales volumes, identification of high-potential leads, recommendations for optimizing marketing campaigns, and insights into product demand. 7. Iterative refinement Predictive sales analytics is an ongoing process. As new data becomes available, the model can be retrained and refined to improve its accuracy and relevance. This ensures that the predictions remain aligned with changing market dynamics. 8. Decision-making and strategy formulation Businesses use the insights from predictive sales analytics to inform their decision-making and shape their sales and marketing strategies. For example, they can allocate resources based on anticipated sales trends, tailor marketing efforts to specific customer segments, and optimize inventory management. Now that we have understood the process of predictive sales analytics, let’s have a look at the companies that are using this tool.  Which Companies Use Predictive Sales Analytics? Predictive sales analytics is embraced by a diverse range of companies spanning various industries. These companies want to transform raw data into actionable insights, enabling them to anticipate customer behavior, allocate resources more efficiently, and make well-informed decisions. Let’s see how different companies across industries are using predictive sales analytics:  1. Retail Industry Retail companies use predictive sales analytics to forecast demand for products, optimize pricing strategies, and manage inventory levels. This helps them avoid stockouts and overstocking, ensuring they meet customer demands effectively. 2. Financial Services Banks and financial institutions employ predictive sales analytics to assess credit risk, detect fraudulent activities, and make informed lending decisions. This results in reduced financial losses and improves the quality of loan portfolios. 3. Healthcare Sector Healthcare organizations leverage predictive sales analytics to predict patient trends and allocate resources efficiently. It aids in optimizing hospital operations, patient admissions, and resource utilization, ultimately leading to better patient care. 4. Technology Companies Technology firms utilize predictive sales analytics to analyze customer behavior and preferences, enabling them to tailor their products and services. This helps increase customer satisfaction and loyalty. 5. Manufacturing Sector Manufacturing companies apply predictive sales analytics to optimize supply chain processes, anticipate equipment maintenance needs, and enhance production efficiency. This minimizes downtime and maximizes productivity. 6. Automotive Industry Automotive companies use predictive sales analytics to anticipate market demand for specific vehicle models, allowing them to adjust production and marketing strategies accordingly. 7. Telecommunications Telecommunication companies employ predictive sales analytics to analyze customer usage patterns and predict churn rates. It helps them design targeted retention strategies and personalized offerings. 8. Hospitality and Travel Hospitality businesses utilize predictive sales analytics to forecast occupancy rates, optimize room pricing, and enhance guest experiences by tailoring offerings based on customer preferences. 9. Energy Sector Energy companies leverage predictive sales analytics to predict energy consumption patterns, optimize energy distribution, and plan maintenance activities for power infrastructure. 10. Consumer Goods Consumer goods companies apply predictive sales analytics to identify consumer trends, anticipate shifts in demand for different products, and optimize marketing strategies. 11. Real Estate Real estate firms use predictive sales analytics to analyze property market trends, anticipate property values, and optimize pricing strategies for rental and sales properties. 12. Pharmaceutical Industry Pharmaceutical companies utilize predictive sales analytics to forecast demand for medications, optimize inventory levels, and align production with market needs. With so many companies using predictive sales analytics, it is important to understand what it actually does? How does it affect processes, and why is it so important?  Why Is Predictive Sales Analytics Important? Predictive analytics software can handle complex and demanding data processes behind the scenes, allowing sales professionals to concentrate on their core strengths. In simpler terms, predictive sales analytics assists sales professionals in transforming a potentially overwhelming volume of data into straightforward, comprehensible insights that serve the

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Your Guide to Dreamforce 2024 After-Parties

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Your Guide to Dreamforce 2023 After-Parties Event 10 min Networking and Nightlife: Unveiling the Social Soirees of Dreamforce 2023 The excitement isn’t just in the conference rooms and keynote stages as the most anticipated event in the tech world, Dreamforce 2023, approaches. Salesforce’s annual Dreamforce tech event is known for its ground-breaking panel discussions as well as its legendary afterparties. Check out our carefully prepared list of Dreamforce 2023 afterparties that you simply should not miss. 1. Whatfix Dreamforce Cocktail Soirée Date: September 12, 2023 Time: 7PM Where: Cityscape Lounge Register here: https://go.whatfix.com/dreamfix-2023/?utm_source=party_blog&utm_medium=blog&utm_content=register_pass&utm_campaign=df-2023&utm_term= Whatfix is organizing a night filled with good food, drinks and an opportunity to connect with some of the most brilliant minds in the industry. This gathering will take place at the highest rooftop bar in San Francisco, offering an unparalleled 360° cityscape. So get your cameras ready to capture the breathtaking San Francisco skyline while getting pumped for the event! 2. Dreamfest 2023 Date: Sep 14, 2023 Time: TBA Where: Chase Center Note: Dreamfest access is included in your Dreamforce ticket. The biggest Dreamforce party is here and we are all hyped for it! Once again supporting UCSF Benioff Children’s Hospitals Foundation, this year’s main act hasn’t been announced yet but it’s totally acceptable to get excited already as we are too. 3. Tableau and MuleSoft Welcome Reception Date: Sep 11, 2022 Time: 5PM – 8PM Where: PABU Izakaya Register Here: https://www.tableau.com/community/events/tableau-and-mulesoft-welcome-reception-dreamforce-2023-09-11 Kickstart your Dreamforce journey with flair, accompanied by Ryan Aytay, the Chief Executive Officer of Tableau, alongside distinguished figures from the industry. Enjoy a delightful evening of refreshments, sushi delicacies, and live musical performances. 4. ElementsGPT Dreamforce Kickoff Party Date: Sept 11, 2022 Time: 6:00 PM – 9:00 PM Location: Elements Cloud Spaces, 95 3rd St Register Here: https://df23events.com/go/elements-gpt-party You simply can’t miss this one happening just a block away from Moscone. Mingle with people from the industry, plan your night and celebrate the spirit of Dreamforce! 5. The RevOps Dream Team Happy Hour Date: Sep 12, 2022 Time: 5:00 PM – 9:00 PM Location: Soma Eats on Second (a short, five-minute walk from Moscone Center) 186 2nd Street, San Francisco, CA, 94105 Register Here: https://tractioncomplete.com/dreamforce23-revops-dream-team-happy-hour/?utm_campaign=24q2+dreamforce&utm_medium=link&utm_source=third+party&utm_content=salesforce+ben&utm_term=happy+hour+sept+12 Join the Revenue Optimists and Traction Complete towards the end of first day of Dreamforce. Mix, mingle and network with the smartest minds in Revenue, Sales and Marketing Operations. 6. AfterParty GPT Date: Sep 12, 2022 Time: 7:00 PM – 1:00 AM Location: Temple Night Club Register Here: https://www.salesforceben.com/dreamforce-party-afterpartygpt/?utm_content=167352256&utm_medium=social&utm_source=linkedin&hss_channel=lcp-7970687 Following the roaring success of 2022, Salesforce Ben is reigniting the party spirit with AfterParty GPT. Taking the inspiration from Summer of AI, the venue is thoughtfully chosen to provide the ultimate party experience while networking with industry experts. 7. Dreamforce After Party Bash Date: Sep 12, 2022 Time: 4:30 PM – 8:30 PM Location: Northern Duck Register Here: https://www.eventbrite.com/e/dreamforce-after-party-bash-salesforce-tickets-687528194337 Celebrate 20 years of Dreamforce with drinks, delectable dim sum, and boundless jubilation at the Dreamforce After Party Celebration! Come join the festivities at the Twitter headquarters in Northern Duck. Stand a chance to mingle with industry leaders here! 8. The Revenue Launch Pad for Dreamfest Date: September 13, 2022 Time: 5:00 PM – 8:00 PM Location: Soma Eats on Second (a short, five-minute walk from Moscone Center) 186 2nd Street, San Francisco, CA, 94105 Register Here: https://tractioncomplete.com/dreamforce23-revenue-launch-pad-dreamfest-happy-hour/?utm_campaign=24q2+dreamforce&utm_medium=link&utm_source=third+party&utm_content=salesforce+ben&utm_term=happy+hour+sept+13 Cheers RevOps! After spending a busy day at Dreamforce, come together and relax with your new found friends at Dreamforce and Traction Complete. Unwind, socialize, and engage with exceptional individuals in the realms of RevOps, sales operations, and sales leadership while enjoying delicious food and drinks. 9. Computer Futures Dreamforce 2023 Happy Hour Date: Sep 13, 2023 Time: 4:00 PM – 7:00 PM Venue: Wine Down SF Register Here: https://www.eventbrite.com/e/computer-futures-dreamforce-2023-happy-hour-tickets-680977410767?aff=ebdssbdestsearch&from=98cdc745265c11eeb9562e4412cf12a8 Relish good food, good drinks and good company as you take some time off to unwind at Computer Features Happy Hour. 10. Marketers Afterglow Party Date: Sep 14, 2023 Time: 4:00 PM – 6:30 PM Venue: Home for Marketers at The Pink Elephant Alibi Register Here: https://dreamforce.sercante.com/marketers-afterglow-party/ Join us to wrap up your Dreamforce journey and engage in a networking occasion tailored specifically for marketers, trailblazers, and the thriving Salesforce community. Enjoy complimentary refreshments while you prepare to bid adieu to the valuable relationships you’ve nurtured throughout the exciting week of Dreamforce. With several other parties and get-togethers lined up in the itinerary, Dreamforce is the right destination for you to meet, network and connect with like-minded brains of your industry alongside taking time to unwind from bustling schedules. We are thrilled to see you there! 11. Vonage Happy Hour Date: September 12 & 13, 2023 Time: 4-6PM Where: Gallery Ballroom, Hyatt Regency San Francisco Downtown Soma, 50 3rd St, San Francisco, CA 94103 Register here Brought to you by Vonage, and sponsors, Verint, AutoReach & Roycon, this Happy Hour will be buzzing with fun, networking and excitement! Maximize your Dreamforce and join us for Drag Queen Bingo and an awesome set from DJ Amy, as well as great snacks and a well-stocked bar. Did we miss out on any event? Send a tweet to @ainektar and we’ll be sure to add it in. Or email us at marketing@nektar.ai Meet the Nektar Team!  Come, say hello to the Nektar team (Jordan, Randy, Ankit, Danielle, & Abhijeet). Whether it’s about after-parties, accelerating your revenue funnel or plugging CRM data gaps, we would love to chat.   Bhaswati Director of Content Marketing at Nektar.ai, an AI-led contact and activity capture solution for revenue teams. With 11+ years of experience, I specialize in crafting engaging content across blogs, podcasts, social media, and premium resources. I also host The Revenue Lounge podcast, sharing insights from revenue leaders. In this blog

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Tech Stack Consolidation for Revenue Teams: Streamlining Efficiency and Productivity in 2025

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Tech Stack Consolidation for Revenue Teams: Streamlining Efficiency and Productivity in 2025 Sales Sales Tech Stack The entire customer journey, from lead to opportunity to revenue to retention is riddled with complexities.  Buyers are well-informed about a product and its competitors way before they even book a demo.  Sales cycles are longer with multiple stakeholders influencing the buying decisions at each stage of the customer journey.  Customer churn is at an all time high. To successfully close deals and generate revenue, GTM teams today need to be hyper fluent with customer pain points. And be able to offer tailored solutions to them at their time of need.  This is why revenue teams need technologies at their disposal. Which can help them act on insights that can enhance the customer experience. And lock in more revenue every quarter. While investing in these tools is table stakes to achieve revenue targets, the concept of “the more the merrier ” does not work here.  While it might be tempting to solve a problem with the shiniest new software out there, organizations are realizing that this can actually drain the productivity of their teams and lead to a myriad of inefficiencies. Ep #11: Components of a Modern Sales Tech Stack Bloated tech stacks can create many problems in disguise and add to a lot of hidden costs such as cost of integrating, tool fatigue, cost of siloed data and much more. Which is why 2024 is the year of tech stack consolidation. 62% of businesses are trying to cut down the number of tools they use and trim the excess fat from their tech stacks. In this blog, we will explore what revenue tech stack consolidation means. And how you can go about approaching it. Before we get into what tech stack consolidation means, let’s take a quick look at what led us here.  More Tools Don’t Mean More Revenue A whopping number of tools are being added to the modern revenue technology stack. SaaS organizations use an average of 130 applications! But only 53% of users say their technology aids productivity and positively impacts results.  According to another survey, 57% of marketing leaders, who had over 20 tools in their tech stack, strongly doubted if they’d reach their ROI goals.  It’s clear that the promise of efficiency gains and higher productivity that these tools claim for GTM teams are often not met. Instead, it leads to enormous amounts of tech debt for businesses.  And an ever increasing stack of tools only adds to the complexity of daily operations, causing revenue to leak across various points along the customer journey.  Here are some of the ways too many tools lead to loss of revenue opportunities: A web of fragmented tools adds to complexity in day to day operations. Tools are siloed in multiple systems which makes it difficult to track data, draw insights from it or keep it consistent and secure. No unified view of data leading to misalignment among GTM teams Overwhelmed employees who spend nearly 70% of their time on painstaking administrative tasks such as updating spreadsheets, adding prospects to CRM and augmenting data. These damaging effects of too many tools have increased the need for a leaner tech stack. Revenue leaders are taking a critical look at their existing tech stacks. And figuring out how to trim the fat without losing out on any core functionality. This is what we call tech stack consolidation. What is Tech Stack Consolidation? Tech stack consolidation is the process of reducing the number of tools in a company’s tech stack by merging functionalities into lesser and more exhaustive platforms. The goal of consolidation is not to knock down all of the investments in point solutions that already exist. It demands a structured approach in analyzing which tools offer real value for GTM teams. And eliminate tools that don’t add any merit to their day to day workflows. More tools in the tech stack add the burden of deployment, management and adoption. The goal for revenue leaders is to evaluate what they have, consolidate wherever they can and optimize their tech stacks to improve productivity and execution across every role. Consolidated technology seems to be the recipe for winning teams as per this survey by Sales Hacker. Teams that use tech stack that enable the full sales motion, from creating pipeline to closing deals are more likely to meet their revenue goals. A lean and fully capable sales tech stack is a reality as companies look to consolidate vendors while retaining the features and capability of their previous array of point solutions.  With the need for efficiency and productivity rising, let’s discuss an evaluation framework that can help you consolidate your tech stack. Evaluation Framework for Tech Stack Consolidation Too many tools add a lot of costs to a business. These costs go beyond the price on the invoice.  Poorly implemented and managed tech can lead to a lot of soft costs which arise from frustration in using the tools, poor adoption, implementation and maintenance and other issues that eat up the precious time of revenue teams.   Making changes to a tech stack is a delicate affair and needs to be handled with caution. It’s important to have all the necessary information at the very beginning to make informed decisions.  Here is a step by step evaluation framework to consider for a tech stack consolidation.  Step 1 – Identify your biggest challenges along the customer journey As a first step, inspect where your problems lie. Ask yourself: How can you boost productivity and efficiency at every stage of the customer journey with your existing tech stack? Are your marketing, sales and customer success teams meeting their targets? Do they have the right tools at their disposal? If not, what can make them more productive? Do you have clear visibility into the deals in your pipeline? If not, why? Identify where frictions exist in your customer journey. Is it at the very beginning of the funnel when a lead enters your CRM?  Is it when an opportunity needs to be handed over to customer

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CRM Data Cleansing: How to Keep CRM data Pristine

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CRM Data Cleansing: How to Keep CRM data Pristine CRM On average, in a B2B company, the volume of prospect and customer data doubles every 12-18 months.  This massive influx comes with a significant risk of errors, duplicates, outdated records, and other inconsistencies creeping into your CRM. The longer this dirty data sits in your CRM, the worse the outcomes of your CRM would get much like a snowball rolling downhill. What can you do?  Implement robust CRM data cleansing practices. These practices include conducting regular CRM data audits, using CRM data validation techniques, and leveraging automated tools to keep your data clean and credible.  Ep #12: Driving Revenue With Clean CRM Data ft. Jacki Leahy In this article, we will learn all about CRM data cleansing and how automation and AI ease the process of data cleansing.  Let’s get started with the basics.  What is CRM Data Cleansing? Imagine you are going on a trip and need to pack your stuff. Will you be able to do it in a messy room full of stuff scattered everywhere? You’d spend ages just trying to find your things, let alone packing them efficiently. But when everything is neatly organized, you can do all the packing in a fraction of the time. Well, CRM data cleansing is similar. It’s all about taking that chaotic, messy data and transforming them into well-organized and accurate datasets.  In a nutshell, CRM data cleansing is the process of identifying and fixing inaccurate or incomplete data in your CRM database. It involves detecting and eliminating duplicate, outdated, or irrelevant data, ensuring that the CRM database remains accurate and up to date informing smarter and reliable business decisions. How Poor CRM Data Hygiene Affects Your Revenue For great results, you need to be careful of what you feed your CRM system. Or else, it becomes a classic case of “garbage in, garbage out.” You cannot expect great results from CRM insights if the source of the data in it is unreliable.  Data lies at the heart of gaining visibility on where to make improvements, drive focus on leading indicators and fix the revenue funnel before it breaks. If the data in the CRM in itself is plagued, you cannot expect insights from it that drive revenue.  In fact, it is quite the opposite. In a recent survey, 44% of respondents estimated their company loses over 10% of annual revenue due to poor data quality. Such data inefficiencies are causing revenues to leak through your funnel in myriad ways.  Some of them include: 1. High employee turnover CRM users aka your employees are reaching a saturation point. 64% of them say they would consider leaving their current role if organizations don’t invest resources in a CRM data quality plan. In a world where talent is scarce, employees leaving would mean so much more time and resources gone in hiring more people, onboarding them and keeping them engaged. 2. Poor sales forecasting The quality of your sales forecast has a direct impact on your revenue. A poor sales forecast is a result of bad data fed into your systems that fail to predict how much revenue will be closed quarter after quarter. The result is wasted resources on avenues that lead to no result. 3. Poor ROI from tech stack Revenue leaders invest in different tools as a part of their tech stack, CRM being one of them. But all these tech stacks can only deliver ROI when they have the right data to work with. Without quality data, these tech stacks will just remain as shiny objects that eat up budgets without delivering any meaningful value to revenue.  4. Poor targeting Picking up all contacts from a CRM and running a uniform campaign for all is passe. Today’s customers want hyper-personalized messaging, which requires marketing teams access to high-quality data that tell them more about their contacts than simple name and email ids.  CRM data tells marketing teams who to target for their campaigns. It fails to address the “why.”  Bad data aggravates this problem by sending wrong messages to the wrong customers for solutions they might not even be looking for, thus putting the reputation of a brand on the brink of damage. Advantages of CRM Data Cleansing  Leverage the power of a clean CRM to drive business growth in the following ways:  1. Effective prospect communication Clean data ensures you reach the right people with the right message at the right time. By having accurate contact details, preferences, and purchase history, you can personalize your follow-ups, build effective marketing campaigns, and provide exceptional customer service. 2. Improved productivity Outdated or incorrect data leads to wasted time and effort. We are not the only ones saying this, a report by Mckinsey says that employees spend 9.3 hours a week simply searching for the data they need.  By keeping your CRM clean, you avoid redundant tasks, such as contacting the same leads multiple times or dealing with undeliverable emails. It streamlines your processes, increases efficiency, and allows your team to focus on what matters most—building valuable customer relationships. https://youtu.be/-Zi6T1Ny9jI 3. Improved conversion rates 78% of businesses say that the data they collect helps them increase customer acquisitions and lead conversions. Reliable CRM data enables your sales team to target the most promising leads and opportunities. By eliminating duplicates, outdated leads, or invalid contacts, businesses optimize their sales efforts, increase conversion rates, and close deals more effectively. 4. Cost savings Maintaining clean data prevents unnecessary expenses. By avoiding mailing or marketing to incorrect or inactive contacts, you save on time and costs. Additionally, you reduce the risk of penalties associated with non-compliance, such as sending messages to individuals who have opted out.  Here’s something to cement our claim, data quality issues can cost a lot of revenue around 1/5th of the sales to be precise. 5. Better customer segmentation  Clean CRM data allows you to segment your customer base effectively. By organizing and categorizing customers based on accurate data points like demographics, purchase history, and preferences, you can create targeted marketing campaigns and personalized

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Your CRM Contact Data is the Key to Drive Sales Efficiency. Here’s How.

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Your CRM Contact Data is the Key to Drive Sales Efficiency. Here’s How. Sales Activity Capture Driving sales efficiency remains the ultimate goal for most businesses. Going after the right deals, building long-lasting relationships with multiple buyers in an account is key. This evolving landscape demands sales teams to be agile, strategic, and, most importantly, armed with the right data.  And at the heart of this data-driven revolution lies B2B contact data – a crucial element in the arsenal of sales teams striving for success. Having access to contact data can open several doors for sales teams.  Organizations already have a wealth of contact data. Unfortunately, they are trapped across various applications and tools in siloed Go-to-market (GTM) systems. Think of crucial data trapped in phone calls, emails, meetings, calendars and countless other tools that your reps use.  The CRM, intended as the central hub for this information, often becomes a repository of incomplete, inaccurate, or rapidly decaying data. Manual updates are sporadic, and the consequence is a compromised ability to engage effectively with prospects. The result? Critical data about prospects and buyers never make it to the CRM. And your sales team ends up targeting the wrong people and chasing the wrong deals. That’s the opposite of efficiency.  Merely having a vast pool of contact information is not enough. Tracking the dynamic relationship between sales teams and prospects is table stakes. Every interaction – phone calls, demos, emails, and notes – needs to be meticulously recorded. And shared in a unified manner for sales and marketing teams to be on a common page.  Enter AI-led Contact Data Automation The solution lies in automating contact data capture into CRMs and deploying Artificial Intelligence (AI) for real-time actionable insights. This not only streamlines the process but also ensures that the data is consistently accurate. AI provides a unified, comprehensive view of prospects, enabling sales teams to deliver an exceptional buyer experience at every stage of the journey. Benefits of AI-led Contact Data Automation Introducing AI-led automation into your contact data strategy can yield several benefits across the buyer’s journey. Let’s look at the top ones: 1. Clean, Complete, and Up-to-Date CRM Data AI can automate the process of collecting, cleaning, and updating contact data, ensuring that your CRM is always equipped with accurate and current information. This improves the reliability of your data and allows for more effective communication with leads and customers. 2. Automated Manual Tasks AI can take care of time-consuming tasks like data entry, freeing up valuable time for your sales team. This allows them to focus on more important tasks, such as building relationships with leads and closing deals. 3. Actionable Insights AI can analyze contact data and provide actionable insights about leads and buyer behavior. This can help sales teams understand their target audience better, tailor their sales strategies, and improve the effectiveness of their campaigns. 4. Predictive Analytics AI can use historical data to anticipate future trends and behaviors. This allows sales teams to stay ahead of the competition by identifying potential opportunities and risks in advance. 5. Unified View of Deals and Activities AI can provide both sales and marketing teams with a unified view of data, allowing for better collaboration and alignment. This ensures that both teams are working with consistent and accurate data, leading to more effective campaigns and sales strategies. Use Cases for Sales Efficiency From the first point of contact to nurturing long-term customer relationships. AI-led contact data automation can address various gaps in the sales process. And real-time insights into deal status and buyer behavior can become the foundation for driving sales efficiency. Let’s look at some of our top use cases that contact automation can drive for sales: 1. Contact-Level Engagement Insights for Effective Multithreading Pushing deals from creation to closed-won requires strategically engaging every member of the buying committee. Quite often, sales leaders do not have visibility into who their sales reps are engaging in every deal. They rely on a download from the deal owners during the pipeline review calls. But almost always, most deal owners simply talk about champion and/or economic buyer engagement. It’s rare to discuss buying committee coverage, which can have 10-30 members involved if we consider enterprise deals. What makes this worse is that the opportunities in CRM would also only show 2-4 contacts. Sales leaders and managers continue to be in the dark. They don’t know what they don’t know. By automating contact data capture, sales leaders instantly get visibility into buying committees. Combining this with good Salesforce reporting, they can gain visibility into the depth and breadth of engagement with each member of the buying committee. Such insights enable sales leaders to guide deal owners to execute more effectively. While this is the age of AI, the truth remains that people buy from people, especially in high-touch B2B sales. This mandates reliable visibility into the strength of buyer-seller, or rather buying committee-seller relationships. Each buying committee member is like a door. All doors lead to the same destination, in this case, that destination is ‘closed-won’. But the path to closed-won can vary behind the door. Some doors can open long paths, some short. So every door must be opened because you never know which door has a shorter and quicker path to achieving a closed-won deal. 2. Sales-Marketing Harmony for Account-Based GTM If you’re a sales leader or an operations leader planning an account-based GTM strategy, ask your marketing counterparts if they have unprecedented access to clean and complete contact data. There’s a very high chance that their response will be ‘limited’. And don’t be surprised or offended if they blame your sales reps for not adding contacts to the CRM. Your marketing teams are forced to rely on third-party data vendors for contact data, when in reality, there’s an abundance of those in your sales reps inboxes and calendars. The result? Irrelevant marketing campaigns due to poor audience targeting. This is where sales reps start blaming the marketing team for poor air-cover.

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Top 7 Salesforce Automation Tools in 2025

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What is Salesforce Tech Debt? And How Can You Reduce it? RevOps 10 min Managing sales processes and customer relationships has always been tedious. Fortunately, for many of us, Salesforce and its automation tools have come as a savior. These solutions streamline and automate sales tasks and help focus on building meaningful relationships with customers.  However, with the rapidly evolving landscape of sales and technology, finding the right Salesforce automation tools that align with your business needs can take time and effort. To make it easier for you, we have compiled a list of the seven most promising Salesforce automation tools you need to consider in 2023.  What’s your goal? Enhance lead generation? Optimize sales pipelines? Improve customer interactions? We’ve got you covered with a curated list of cutting-edge solutions that are sure to drive your sales success.  So, let’s dive in and discover the tools that will empower your team to thrive and achieve your sales goals. 7 Best Salesforce Automation Tools Here are the seven best Salesforce automation solutions you should consider for your business: 1. Nektar Nektar is a leading Salesforce automation tool with advanced contact automation capabilities. It helps sales teams unlock a whole new level of efficiency and sales productivity. Nektar can generate 8 times more buyer contacts through automated contact management. It ensures no potential lead slips through the cracks—no more missed opportunities. Get a steady stream of qualified prospects that are worth your attention. If you are looking to ramp up your Account-Based Marketing (ABM) campaigns, Nektar has got you covered. The tool enables you to supercharge your ABM efforts by automating personalized outreach. It ensures your message reaches the right decision-makers at the right time. Nektar doesn’t just automate tasks but provides invaluable relationship intelligence. Tracking and analyzing buyer interactions allows you to gain insights into customer behavior. The newfound intelligence empowers you to tailor your sales strategies and build stronger, more meaningful relationships with your prospects. Multithreading every opportunity also becomes a breeze with Nektar. It facilitates seamless collaboration and communication across your sales team and ensures every critical touchpoint gets noticed. Stay on top of every interaction and nurture every opportunity with precision and agility. Key features: Gain detailed contact lists for every Account in your CRM Segment Account contacts and Opportunity Contact Roles (OCR) based on their affinity and involvement Automatically create the buying committee map for advanced intelligence  Get auto-updated contact details with job titles and phone numbers 2. Veloxy Veloxy is another leading Salesforce automation tool that seamlessly extends the power of Salesforce to your favorite inbox and mobile devices. The platform revolutionizes the way you capture leads and update records through intuitive features and seamless integration. Veloxy effortlessly integrates with your preferred inbox or your smartphone. The integration ensures automatic lead capturing and updating of records in Salesforce. It saves valuable time and eliminates the hassle of data entry. Furthermore, understanding customer engagement is essential for effective lead prioritization. Veloxy takes care of this by automatically tracking your customers’ email engagement. Insights into open rates for emails and click-through rates help you prioritize leads based on their level of engagement. Key features: Automatic analysis and prioritization based on buyer intent for leads and contacts Optimized field sales routes for more stop-ins and meetings Automated capturing and updates of contact information from your inbox 3. ZoomInfo ZoomInfo creates a single source of truth for your organization. With its seamless integration and comprehensive data-driven solutions, ZoomInfo enhances the Salesforce experience for your sales teams. ZoomInfo works seamlessly with Salesforce. It ensures a flawless integration that makes life easier for your teams. Native applications and ongoing lead enrichment allow ZoomInfo to empower your organization to maintain a reliable Salesforce ecosystem. From lead enrichment to ongoing data updates, ZoomInfo equips your Salesforce ecosystem with the latest and most relevant information. ZoomInfo streamlines Salesforce and provides comprehensive data-driven solutions. With accurate and up-to-date information readily available, your teams can focus their energy on productive sales activities. Key features: Build and save targeted contact lists and account details 200+ data point filters, including employee, company, and geographic location Continuously enrich Salesforce data by getting rid of discrepancies 4. Qualtrics Qualtrics, a Salesforce automation tool, seamlessly brings advanced customer feedback analytics into the Salesforce platform. It allows you to unlock invaluable customer insights and take decisive action to close more deals. With Qualtrics, you can elevate your customer experience game and drive success, all within a single, integrated platform. Qualtrics can embed advanced customer feedback analytics directly in Salesforce. The integration enables you to surface deep customer insights without switching between platforms. The power of Qualtrics’ analytics capabilities within Salesforce helps you comprehensively understand your customers and their preferences. Furthermore, Qualtrics empowers you to automate feedback requests within Salesforce. It lets you capture customer sentiment at crucial milestones throughout the sales cycle. Automating feedback requests based on account milestones helps you gain insights into customer behavior and satisfaction levels at every stage. Key features: Get new leads in Salesforce from your Qualtrics surveys  Set up email triggers with surveys to send when a specified object’s Flow conditions are met Map information from your Qualtrics survey into Salesforce records 5. LevelEleven LevelEleven is an advanced Salesforce automation tool that specializes in sales performance management. With its focus on gamification and coaching, LevelEleven helps organizations reinforce successful behaviors to drive motivation and achieve sales excellence. With personalized scorecards and intelligent goal management, LevelEleven directly brings a comprehensive sales performance solution into Salesforce. Incorporating game-like elements into the sales process allows LevelEleven to create an engaging and motivating environment for sales teams. Personalized scorecards enable individuals to track their progress, see their performance metrics, and compete against their goals or other team members. With intelligent goal management tools, LevelEleven enables organizations to set and track sales targets. It ensures alignment with business objectives. Real-time visibility into goal progress allows sales teams to stay focused and make data-driven decisions. The streamlined goal management process drives accountability and fosters a results-oriented sales culture.

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Top 5 CRM Automation Use Cases

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Top 5 CRM Automation Use Cases RevOps 10 min CRM is the soul of every modern business today. It serves as the epicenter for managing customer relationships and sales processes.  But, what gives it that special edge?  CRM automation – that’s right! The automation capabilities take it to a whole new level.  With automation, businesses have stopped wasting resources on repetitive tasks that have minimal to no impact on their revenues. Instead, they just let the CRM take care of these tasks helping them streamline operations, facilitate efficiency, and allocate more time to meaningful customer interactions.  And, that’s not all – CRM and its automation features can do much more.  In this article, we will keep CRM automation at the forefront and discuss the top five use cases through which you can maximize the ROI from your CRM. What is CRM Automation? CRM automation refers to leveraging technology to streamline and simplify various tasks and workflows of your business. It automates repetitive, manual tasks that otherwise hamper productivity. And truth be told, AI is simply upping the game now. Who doesn’t want a helping hand that takes care of data entry, sends personalized follow-up emails, and even reminds when it’s time to reach out to a customer? 94% of employees say they perform repetitive, time-consuming tasks in their role. With CRM automation, your teams can leave behind repetitive tasks and focus on high-value activities such as building relationships and delivering personalized experiences.  But there’s more to it, which is why we will now delve into why exactly CRM automation has become omnipotent today.  Why Do You Need CRM Automation? CRM automation has the potential to turn your business outcomes upside down. Here’s how.  1. Improved sales productivity Free up precious resources and automate repetitive processes. Let technology handle data entry, lead tracking, and follow-ups, allowing your team to focus on revenue-driving sales activities that push your business forward.  According to McKinsey, automation can boost global productivity growth by 0.8-1.4 % every year.  2. Better team collaboration CRM automation facilitates seamless collaboration between teams. Sales, marketing, and customer service departments can access real-time customer data, track interactions, and coordinate efforts. This collaboration ensures a harmonious approach, leading to satisfactory customer experiences and streamlined operations. 3. Data-driven culture Data is everywhere, constantly present and ever-growing, but analyzing it manually can be overwhelming. Since 85% of data is unstructured, automation is critical for a business to save time and minimize mistakes.  CRM automation captures and organizes data, providing you with valuable insights at your fingertips. Make data-driven decisions, identify trends, and uncover opportunities for optimization and growth.   4. Deeper personalization Whether you’re selling, marketing, or supporting your customers, personalization is the new black and for that, you probably don’t want to miss any details. CRM automation enables you to deliver tailored and timely interactions with customers. Automated workflows ensure that no leads fall through the cracks and that every customer receives the attention they deserve, resulting in more satisfaction and loyalty. 5. Sustainable revenue generation At the end of the day, it’s all about the bottom line. CRM automation empowers you to optimize your revenue operations, identify cross-sell and upsell opportunities, and nurture leads effectively. By aligning your teams and processes, you create a well-oiled revenue engine. It comes as no surprise that 61% of businesses leveraging automation reported exceeding revenue targets in 2020.  5 Use Cases of CRM Automation A CRM comes with a wealth of possibilities for your business. We will now explore the top 5 use cases to improve your CRM’s ROI. 1. Contact automation  Don’t let the important contact data sit idle. Use a CRM to automate contact data capture from your reps’ inboxes, calendars, and Zoom meetings. The platform can efficiently organize contacts by segmenting them according to their affinity and level of involvement in current opportunities. The CRM can also automatically build buying committees and keep the contact information updated. The numbers say it all. Companies that incorporate high-level automation into their sales process generate around 16% more leads compared to those that incorporate low-level or no automation. 2. Personalize customer service & onboarding  60% of consumers say they’ll become repeat customers after a personalized experience. If you want to offer personalized support right from the beginning of the customer journey, you need the right data. And what better source than CRM to gather all the data required for personalizing the customer experiences? All relevant customer information stored in one centralized hub which is your CRM helps automate customer onboarding workflows, guide customers through each step, and offer them necessary resources proactively. A complete view of each customer’s history, preferences, and interactions in the CRM empowers businesses with the data they need to address customer needs promptly thereby delivering consistent and personalized experiences. 3. Run lucrative marketing campaigns The top marketing priority of 44% of businesses is increasing revenue from current customers. To yield such results, a CRM becomes vital for businesses to run effective marketing campaigns. They can use the customer data in the CRM for targeting and segmentation of their audience.  Businesses can further personalize their messaging to resonate with specific customer segments, improving the conversion rate. CRM automation also plays a pivotal role by simplifying campaign workflows and automating email sequences for timely customer engagement.  To go one step ahead, you can also integrate CRM with marketing tools to enhance reach and enable cross-channel campaigns. Robust tracking and analytics of CRM provide businesses with insights into campaign performance, enabling them to optimize strategies for higher campaign returns.  4. Identify business opportunities and trends  Harness CRM analytics to dive deep into customer behavior, trends, and campaign performance. Understand hidden patterns, identify opportunities, and make data-backed decisions that will certainly take your business forward.  The analytics are important to identify high-potential prospects, understand their pain points, and tailor your sales pitches accordingly. With a CRM, you also get a detailed view of the sales pipeline, allowing your team to identify bottlenecks and optimize the sales process. The impact is evidently huge as 62% of retailers have stated that using big data gives them a competitive advantage. 5. Reliable sales

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Top Revenue Optimization Software for 2025

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Top Revenue Optimization Software for 2025 RevOps 10 min Is your sales team striving for sustainable growth and profitability? Achieving these objectives requires a keen focus on optimizing revenue streams. Revenue optimization software is a critical element in achieving these goals. Comprehensive research and informed decision-making in software selection become crucial to maximize your revenue potential.  This article looks at the top revenue optimization software for 2025. We will conduct an in-depth analysis to provide you with a valuable resource. It will simplify your decision and help you implement the most effective tool for revenue enhancement. Top Revenue Optimization Software for 2024 1. Nektar 2. Clari 3. Gainsight 4. Planhat 5. Accord 6. Churnzero 7. Totango 8. Aviso 9. Vitally What is a Revenue Optimization Software? Revenue optimization software is a strategic solution that assists organizations in maximizing their revenue potential. The software leverages advanced data analytics, and artificial intelligence to provide actionable insights. You can understand finer details about pricing, demand forecasting, inventory management, sales strategies, and more.  Integrating and analyzing large datasets helps businesses make data-driven decisions that enhance revenue performance. Revenue optimization software thus serves as a critical tool for enterprises seeking to optimize their pricing strategies and boost sales. There is an added advantage of streamlined operations while maintaining a competitive edge. Overview of Top Revenue Optimization Software for 2025 Here are the ten best revenue optimization software solutions for your business in 2025. 1. Nektar Nektar is the world’s first AI for revenue operations. The platform takes an innovative approach to revenue management by harnessing the power of actionable relationship data to combat revenue churn effectively.  Nektar excels in addressing CRM data gaps, both historical and ongoing, through the application of AI time travel. It ensures organizations possess a comprehensive and up-to-date understanding of their customer relationships. The software can transform popular communication platforms like Slack or MS Teams into an early warning system. It can proactively mitigate revenue risk by identifying potential issues before they arise.  Extracting valuable insights from seller conversations and tracking champion movement makes Nektar adept at surfacing new pipeline opportunities and hot leads. Your sales team can ultimately seize revenue-generating prospects. Nektar insists on the importance of CRM data accuracy as a prerequisite for unlocking its generative AI capabilities. This way, the platform ensures it is a reliable and indispensable asset for your go-to-market process. Top features and benefits: Zero rep adoption Day 1 ROI Zero change management Seamless deployment 2. Clari Clari offers a comprehensive revenue platform to enhance efficiency, predictability, and growth throughout the revenue process. With Clari, revenue teams gain unparalleled visibility into their business operations for improved buyer-seller alignment.  There’s also proactive identification of risk and opportunity within the sales pipeline. The heightened visibility significantly improves forecast accuracy and drives operational efficiency. Revenue professionals can foster better connectivity, efficiency, and predictability in their revenue processes. It will ultimately empower them to achieve sustainable growth and success. Top features and benefits: Forecasting & RevOps Conversation intelligence Sales engagement Deal inspection & management Mutual action plans & deal rooms Data capture & ingestion 3. Gainsight   Gainsight is a pioneering revenue optimization software that exemplifies the future of growth through its innovative, customer-centric technology. Gainsight empowers customer success, product, and community engagement teams to scale their operations efficiently. The platform fosters alignment and provides a comprehensive view of their customers.  A holistic approach aids in boosting product adoption and proves instrumental in preventing churn and nurturing the growth of customer communities. Gainsight CS is thus a vital asset for businesses committed to delivering exceptional customer experiences while driving revenue growth and fostering lasting customer relationships. Top features and benefits: Identify and prevent revenue leakage Drive a high-performing renewals process Identify and execute expansion opportunities to drive growth 4. Planhat Gainsight is a pioneering revenue optimization software that exemplifies the future of growth through its innovative, customer-centric technology. Gainsight empowers customer success, product, and community engagement teams to scale their operations efficiently. The platform fosters alignment and provides a comprehensive view of their customers.  A holistic approach aids in boosting product adoption and proves instrumental in preventing churn and nurturing the growth of customer communities. Gainsight CS is thus a vital asset for businesses committed to delivering exceptional customer experiences while driving revenue growth and fostering lasting customer relationships. Top features and benefits: Identify and prevent revenue leakage Drive a high-performing renewals process Identify and execute expansion opportunities to drive growth 5. Accord Accord is a revenue optimization software designed to fortify sales processes and methodologies. It helps in enhancing the predictability and efficiency of deal execution. The platform empowers organizations to directly integrate their successful sales strategies into their sales representatives’ workflows.  Accord helps sales teams with the tools to execute winning sales processes consistently. It contributes to a more efficient approach to revenue generation. The emphasis on reinforcing established methodologies and delivering them directly to the front lines makes Accord invaluable for businesses aiming to optimize revenue. Top features and benefits: Standardized best practices across reps on every deal Up-level sales execution for enhanced deal velocity and win rates Increased team efficiency through decreased rep ramp times 6. Churnzero ChurnZero helps subscription-based businesses thrive at scale. It has a comprehensive suite of tools meticulously crafted to enhance efficiency, boost revenue, and deliver unparalleled customer experiences. Leveraging cutting-edge automation, personalization, in-app communications, and the innovation of Customer Success AI™ helps the platform facilitate seamless customer engagement. The platform guides them towards realizing the total value of their investments.  ChurnZero offers varied resources, including journeys, health scoring, survey tools, segmentation, playbooks, robust reporting, real-time alerts, guided walkthroughs, collaboration centers, and more. Furthermore, ChurnZero seamlessly integrates with your CRM and technology stack. It ensures a cohesive and efficient approach to achieving sustainable revenue growth while focusing on customer satisfaction. Top features and benefits: Systematically track upcoming renewals Use health scores to gauge the likelihood of renewal Automate renewal activities Easily identify expansion opportunities Increase in-app upsell conversions 7. Totango Totango helps cross-functional enterprise teams enhance productivity and retention

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5 Tips to Build a CRM Data Governance Strategy

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5 Tips to Build a CRM Data Governance Strategy RevOps 10 min CRM data governance relies on a solid system.  This includes implementing processes to ensure the data seamlessly flows in the system across departments, while simultaneously maintaining the quality, usability, and accessibility of this data. CRMs are are considered an upgrade or a quick fix to marketing, sales, and service performances. The data gathered is meant to be constantly updated and free of duplicates or copies. But most data in CRM is dirty. After encountering failures with this mindset, companies often feel discouraged and are unable to get the hang of the problem. They start blaming the CRM capabilities when in fact the underlying problem lies in their very own database. Many, if not most, business owners pay no attention to the contact rearrangement or standardization of data and run new strategies based on outdated or siloed data. CRM data governance emphasizes the best practices to tackle these problems so organizations can rely on an updated and single data source to drive business growth. Before we move on to how you can go about building a CRM data governance strategy, let’s first understand why it’s needed in the first place. How Poor CRM Data Affects Revenue Data can swoop in and save the day by helping you tackle problems, keeping an eye on performance, enhancing your processes, and unraveling the mysteries of your industry. On the other hand, poor data quality is like having a mischievous gremlin. It can wreak havoc on your business, leaving nothing but chaos and mayhem in its wake.  Here are some ways poor quality CRM data can make you bleed revenue: 1. Shakes up business processes Since data management serves as a crucial source of information for all departments within a company, any inconsistencies can significantly affect various business operations. Even a small error in the master data can trigger a domino effect that becomes challenging to mitigate once it sets in motion. Inaccurate data leads to a ripple effect of mistakes across departments and drains significant company resources. Addressing data discrepancies requires allocating corporate resources to conduct root-cause analyses and implement corrective measures, impacting the productivity of your staff in the process. 2. Hinders effective decision-making When your data is inaccurate, it can throw you off track and lead to some pretty lousy decisions. Imagine relying on faulty reports and dashboards – it’s like driving blindfolded! Without the right information, your management team will be clueless about what’s really going on in the business. And that’s a recipe for making some really risky and uninformed choices that could seriously hurt your company’s future growth. 3. Puts a wrench in business operations Consider a scenario where a manufacturing company heavily relies on inaccurate supplier data. They have outdated information about lead times, pricing, and product availability from their suppliers. As a result, they struggle with unreliable delivery schedules, unexpected price fluctuations, and limited visibility into the availability of key materials. This leads to production delays, missed deadlines, and increased costs. The company’s ability to fulfil customer orders on time is severely hindered, causing dissatisfaction and the potential loss of valuable business relationships. The poor data quality in supplier information negatively impacts the efficiency and effectiveness of the company’s business operations. 4. Drives up expenditure Referring to the above example, if the company makes decisions based on inaccurate data, it is possible to end up shipping extra materials to the wrong address at the wrong time, costing the company extra. These direct costs can put a dent in the company’s profit. Indirect costs can include outdated pricing structures, inaccurate customer segments, and staff dissatisfaction. Fixing all these will cost additional resources and time, which otherwise could have been put to more productive use. 5. Affects regulatory compliance Compliance is a big deal for any company. You see, these data privacy rules in many countries dictate how personal information should be handled. So, if a company deals with sensitive client data, they gotta go the extra mile to ensure data quality and security. When it comes to verifying your contacts, it’s important to be thorough with your data quality. You wouldn’t want to accidentally send information to the wrong person just because of a small typo in their email address. That can lead to some serious consequences.  Inaccurate data can even land organizations in hot water, with fines and all. There have been cases where companies had to pay for text messages sent to numbers that had already been given to new owners. So, it’s better to double-check and ensure your data is accurate to avoid any costly mishaps. 5 Tips to Build a CRM Data Governance Strategy Implementing this process in your CRM may seem overwhelming at first, leading many to pass the responsibility onto someone else once the data is sourced. However, by focusing on five key concepts, your team can better navigate this task and work towards achieving success. 1. Define clear data standards Establishing clear guidelines and standards for data entry is crucial to maintain data integrity and consistency. By doing so, businesses can ensure that all customer data is accurately captured and formatted correctly.  This involves defining comprehensive naming conventions, which provide a consistent format for entering customer information. Additionally, implementing data validation rules helps in preventing errors and inconsistencies by validating the accuracy and completeness of the entered data. Setting required fields ensures that essential information is not missed during data entry, enhancing the overall quality of customer data.  By enforcing these guidelines and standards, businesses can rely on a robust and reliable database, enabling better decision-making and analysis based on accurate and consistent customer information. 2. Implement role-based access controls It’s crucial to grant the right access permissions to individuals based on their specific roles and responsibilities within the organization. This ensures that everyone has the appropriate level of access to perform their tasks effectively while also safeguarding sensitive customer data. Limiting access to only authorized personnel can significantly reduce the risk of unauthorized access or data breaches. This means

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Why Your Sales Tech Stack Isn’t Delivering Value

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Why Your Sales Tech Stack Isn’t Delivering Value RevOps 10 min Deriving maximum value from their sales tech stack investments continues to be a frustrating challenge for revenue leaders.  With more than 1200 sales tools in the market spread over 49 categories, how do you select the right tools that can help you drive your revenue strategy? Well, the answer to this question is not a straight-forward one.  Before we get deeper to explore nuances of this question, let’s first understand what a sales tech stack is. What is a Sales Tech Stack? A sales tech stack is a set of software tools and technologies that help optimize the performance of your sales teams. The kind of sales tech stack you choose to invest in can have a significant impact on your revenue engine.  A thoughtfully selected and implemented sales tech stack helps remove bottlenecks from the sales process. By closing the existing gaps, it ultimately helps your reps close more deals. Current Landscape of Sales Tech Stack The current landscape of the sales tech market, as Gartner puts is, is absolute mayhem.  The pandemic forced sellers to move to virtual selling. Buyers quickly adapted to this new reality. 50% of buyers say that working remotely has made the purchasing process easier.  These rapid changes increased the need for technology that can enable sellers to meet the rising demands of the modern buyer. Capturing leads, reaching out to prospects, engaging or communication – all these facets of sales are harder than ever before. The right sales tech stack can help sellers optimize the buyer’s journey and thrive in today’s hyper-competitive sales environment. Let’s look at some of the top trends in the sales tech landscape as of 2022: 1. Narrow list of vendors offering multiple capabilities The biggest trend that was seen in 2021 was vendor consolidation, where large companies were seen evolving their tech stacks to more categories than ever.  The market is fast moving towards a narrow list of vendors that offer a wide portfolio of capabilities. For example, HubSpot emerged as a top player in a total of 7 categories including CRM.  Another example is ZoomInfo’s acquisition of Chorus.ai where a large data provider is now offering conversation intelligence features.  2. CRM continues to emerge as a mature category Well-established companies continue to dominate the CRM space, making this a more mature category in sales tech than others. Most CRMs also offer complimentary sales tools. For example, HubSpot continues to be a leader in the CRM space, and also offers complimentary sales tools such as email tracking and marketing automation. 3. Increase in sales budgets for sales tech investment 97% of commercial leaders plan to increase their sales tech investment for 2022.  And 25% of sales budgets are going towards tools and technologies that support the selling or buying experience. The investment in sales tech is increasing and it looks like it’s only going to increase in times to come.  4. There has been a rise in investment into AI and ML technology in sales tech AI fuelled sales and technology companies have seen more than $5 Billion in investment in 2021. 88% of Chief Sales Officers (CSOs) have already invested in or are considering investing in AI analytics tools and technologies.  Companies that adopt and build on this new technology can have a competitive advantage in their respective market.   Why Is Your Sales Tech Stack Not Delivering? There is clearly not a dearth of sales tools that companies use. 67% of sales teams use between 4 and 10 digital selling tools as part of their sales tech stacks. But 42% of sales teams fail to see a clear ROI on these tools.  The real question then is not how many tools sales teams are using. But how effective are these tools in making sales teams win more deals? Let’s look at some of the top reasons why your sales tech stack is not delivering. 1. Your tools are not built for your sales reps Most conventional sales tools are not built for sales reps. They are geared towards the sales managers and sales ops leaders.  These tools help to audit the sales reps, but do nothing to help them close more deals or make them productive.  Using these tools also lead to time wastage as sales reps have to jump multiple hoops to get their job done, be it entering data into a CRM (17% of daily time), collaborating with their peers or other functions. If your sales tools are making your reps’ lives harder and not helping them sell better, it’s clear why it is not delivering value. 2. You have way too many tools According to SBI’s research, an organization purchases 27 sales tools on an average. And the average number of planned tool purchases stand at 4. This research suggests that organizations’ tool purchases are spontaneous. Most decisions to invest in sales tools might not align with the company’s long-term growth strategy.  Because of a lack of thoughtful evaluation, most tools end up being redundant, unused or simply useless. 3. Your processes are not well-defined Most processes around the purchase and implementation of sales tech are not clearly defined. 60.67% of organizations say that they have a somewhat structured purchase process for sales tools. And only 43.82% of organizations have a clearly defined implementation process.  Having no central stakeholder to create a roadmap for the purchase, implementation and continuous reinforcement of the right processes increases the risk of a lower ROI from sales tech investment.  4. Your tools are underutilized Companies utilize less than 50% of the potential of the sales tools that they buy. Even tools that are critical for day-to-day operations have a low degree of usage. Related Blog: Components of a Modern Sales Tech Stack For example, 74% of respondents in a survey said that Account and Opportunity Management is a critical tool for their day-to-day operations. However, only 45% of companies actually end up utilizing this tool. The inability to leverage tools to their full capacity might be because companies aren’t enabling their reps to use the tool effectively. Or are failing to administer the solution in a way that its

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CRM Data Capture: How to Deal with Missing Data from CRM

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CRM Data Capture: How to Deal with Missing Data from CRM RevOps 10 min It is often said that data is the new oil in the modern business world. Companies spend millions trying to extract correct data from the appropriate resources.  The same is true for the sales team. Sales representatives often spend up to 20% of their time updating their CRM! Even after this, half of the contacts they deal with are not present in their CRM. It seems like organizations often are able to extract data but unable to use it judiciously. This is what happens when the CRM data capture is not of good quality.  In this blog, we will read about high-quality data capture, why it matters, and the best practices companies should follow to ensure high-quality CRM data collection. Why High-Quality Data Capture Matters CRM data capture is the method employed by businesses to gather and consolidate information concerning their potential and existing customers. CRM systems amass a lot of valuable data, which is leveraged by sales teams and relationship-focused dealmakers to foster prospects into customers or clients. They subsequently transform these new transactions into referral channels. The ultimate objective of effective data capture is to enhance, grow, and sustain a company’s customer base. As per IDC, inaccurate data inflicts a staggering $3.1 trillion annual cost on American businesses. Another study conducted by Experience Data Quality reveals that companies forfeit an average of 12% of their potential revenue due to data inaccuracies. The root of many data problems frequently originates during the initial phase of data collection. Given that CRM platforms often constitute a significant financial commitment for businesses, the key to obtaining a substantial return on this investment lies in the effective capture and upkeep of high-quality, precise customer data. Here are a few areas that high-quality CRM data capture can improve:  1. Bad data and lack of trust When sales representatives lack relevant information about potential customers, their interactions become less significant, resulting in overlooked opportunities and unsuccessful deals. 2. Inaccurate forecasts Inaccurate forecasting and reporting can create strategic challenges, making it challenging for management to make timely, data-driven decisions.  3. Automation errors Costly automation errors, such as segmentation mistakes that result in sending incorrect email messages to prospects can damage a company’s brand reputation.  4. Bad customer experience Erroneous contact information can adversely affect customer experiences and erode trust, potentially leading to customer dissatisfaction and loss of credibility for the company. 5. Financial pain Poor or unreliable data can also result in financial waste, such as sending materials to the same customer on multiple occasions due to duplicate records. Dysfunctional integrations with other software systems can consume valuable time and effort while causing frustration.  6. CRM issues If data-related issues are impacting your Salesforce and HubSpot tools, they can impede your team’s progress and potentially disrupt marketing and relationship-building activities until these problems are addressed. While clean data is crucial, achieving high-quality data capture can be quite demanding. Manual input into spreadsheets such as Excel or Google Sheets is susceptible to errors, including omissions, duplicate entries, or inaccuracies. Additionally, manual data entry is incredibly time-intensive, and every instance where a salesperson invests time in inputting CRM data is a missed opportunity to nurture relationships. This is where the need to automate CRM data capture arises.  Let’s have a look at a few ways that organizations can improve their CRM data collection:  Ways to Improve CRM Data Capture Improving your CRM data capture methods is a valuable investment of time and energy. When your data capture process is reliable, your team can have confidence in the accuracy of your customer data, allowing them to allocate more time to acquiring, overseeing, and finalizing deals. Here are some of the best practices to improve CRM data capture:  1. Conduct a review of your current data  You can pinpoint significant issues in your CRM data capture by conducting an audit of your existing data. Research conducted by SiriusDecisions revealed that B2B marketing databases can contain serious errors in approximately 10% to 25% of their contacts. Review your current data to detect typical errors and identify areas where data capture standardization can be enhanced. Intelligent CRM platforms also offer technology to assist in auditing your data during the onboarding process and subsequent data imports, making it easier to spot duplicate entries. During your audit, you should be on the lookout for customer- or client-related data errors such as: Data format discrepancies should be rectified to ensure uniformity in expressing phone numbers, states, and zip codes.  Address inconsistency issues in data, such as variations in job titles (e.g., “COO” and “Chief Operating Officer”).  Address missing information in certain records, such as absent email addresses, to ensure completeness. Detect records with low data quality, including those with obviously false names or free email addresses.  Identifying these and similar issues will simplify the development of more efficient data capture procedures for your CRM, enabling you to witness improvements in data quality. 2. Automate data capture When it comes to enhancing CRM data capture, automating this process stands out as the most potent action you can take. On average, professionals make approximately one error for every one hundred keystrokes. Considering that salespeople invest numerous hours each week in capturing and updating CRM data, this error rate can result in a significant volume of inaccurately recorded data in your CRM. Furthermore, certain errors carry more significant consequences than others. For instance, a one-letter mistake in a crucial prospect’s email address (e.g., the distinction between “janesmith@company.com” and “jaensmith@company.com”) could determine whether a deal is secured or an opportunity is completely missed. The most effective approach to prevent subpar data from entering your CRM is to minimize manual data entry as much as possible and replace it with automated processes. Relationship intelligence CRM platforms like Affinity excel in automatically generating and managing customer records by extracting information from inboxes and calendars and subsequently enhancing these profiles with the latest industry data. Automation serves as a solution to numerous challenges associated with data capture. Not only does it

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MEDDIC vs Challenger: What’s the Difference?

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MEDDIC vs Challenger: What’s the Difference? RevOps 10 min Hitting targets is one of the topmost goals for any sales rep. Understandably, all sales teams want to perform consistently well and achieve their goals.  But if you’ve seen your teams struggle in the last few years, you’re certainly not alone.  A recent crowdsourced survey by SaaStr shows that only 18% of sales teams hit a 70%+ quota attainment level. Average quota attainment for reps is down 5 points in 2023 from 2021. Quota attainment is also down for 5 out of 7 such teams.  To change the narrative, you’re probably digging into different sales methods that more successful businesses use. Or, you may simply want to level up your sales game as organizational growth becomes stagnant.  The first few methods popping up will undoubtedly be the MEDDIC and Challenger Sale. Both are useful with proven results for different companies. But confusion may persist on MEDDIC vs Challenger Sale and which one’s the best for you.  We’ve put together a quick overview of both methods that could help you make a decision.  Understanding the MEDDIC Academy Sales Method For 71.4% of sales professionals, only 50% or less of their initial leads are a good fit for their ICP. Reps blame poor qualification of potential customers before taking them through the entire sales process for 67% of lost deals.   There’s one method that shines in these situations.  MEDDIC is a B2B sales qualification methodology used to understand the customer at each stage of the buyer journey. The process drives revenue and business growth by qualifying buyers more accurately.  Here’s how the MEDDIC Academy explains what the process stands for: 1. Metrics What is the quantifiable value of your product for the customer?  2. Economic Buyer Who has the final word on the financial decision at the buyer’s end?  3. Decision Criteria What factors or criteria influence the purchase decision?  4. Decision Process How does the buyer reach a decision?  5. Implicate Pain What is a problem serious enough for the buyer to seek an external solution?  6. Champion Who is the stakeholder most invested in onboarding your solution?  MEDDIC places the focus on customer experience instead of selling with the sole objective of making money. It works because 56% of sales leaders consider engaging and paying attention to gain a client’s trust as the best approach.  With the MEDDIC Academy method, you can: Find leads that are the right fit for you Access critical stakeholders in the buyer committee  Build better forecasts  Boost winning rates  Over time, the MEDDIC Academy has included more steps, such as MEDDPICC, where P stands for paper process and C is competition.  Understanding the Challenger Sale Method Today, 32% of B2B buyers use more sources to research and evaluate processes than before. And 31% spend more time on social media to check out vendors and their solutions.  This means customers enter into a sales transaction with preconceived notions about the product. Reps need to develop an experience going beyond features and benefits. Instead, sellers could challenge the buyer and disrupt their current thinking. This is the Challenger Sale Method. You’re a challenge seller if you: Have a unique perspective of the world Understand the customer’s business in and out Create constructive tension using a casual debate Intentionally dispute the customer’s thinking Push the customer to get out of their comfort zone  Here’s what the Challenger Sale process looks like: 1. Warm-up First up, you build credibility with prospects by researching and investigating their pain points, challenges, and needs. Then, you describe these issues to the buyer in a way they agree.  2. Reframe You reframe the problem as a growth opportunity. This switch is made by sharing an insight that the buyer may not have considered before. 3. Rational drowning You back your reframing with quantitative data and the latest statistics. Numbers illustrate the risk of leaving the problem unresolved. It uses rational thinking to appeal to the customer’s emotions.  4. Value proposition Show the buyer possibilities of a better future. Tie their value drivers with your solution’s capabilities (without explicitly introducing the product).  5. Introducing the solution After the building blocks are in place, you can introduce your product. This is when you explain exactly how it solves the buyer’s problem. With Challenger Sale, you deliver insights into an unknown problem or opportunity in the buyer’s business. Your product is uniquely positioned to solve this problem. By encouraging the buyer to consider new opportunities, a Challenger Seller offers alternative ways forward. But they need three essential skills to succeed:  Teach by providing insights on new or better ways to solve the buyer’s problem  Tailor the message to the buyer’s needs Take control of the sale and guide the customer to closure MEDDIC vs Challenger Sale: How Do They Compare? Some sales experts consider MEDDIC as a sales methodology and Challenger Sale as simply an approach. But there’s more to it.  We’ve listed each MEDDIC vs Challenger Sale comparison below.  Despite the long list of MEDDIC vs Challenger Sale differences, both methods have three things in common: 1. Buyer evolution Both methods take into account the evolving buyer. MEDDIC considers the transformation from the individual buyer to a buying committee with multiple members.  Similarly, Challenger Sale knows that buyers are gathering more information online and contacting the seller later during their journey.  2. Buyer’s drivers Both MEDDIC and Challenger Sale identify the buyer’s value and economic drivers for the selling process.  3. Cross-functional alignment  MEDDIC and Challenger Sale need alignment between revenue teams and leadership buy-in. Marketing managers and leaders provide training and resources for all reps.  Challenger vs MEDDIC Academy Process: What’s the Verdict? Here’s a list of things to keep in mind when considering MEDDIC vs Challenger Sale.   MEDDIC Use the MEDDIC Academy sales process to determine if a prospect is the right fit for your company. It helps teams that are struggling to keep up with the existing sales process and want to improve.  MEDDIC can intervene to help you: Sell to the correct buyer Identify the right stakeholders in a complex enterprise B2B buying committee Regardless of so

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