The traditional MQL funnel doesn’t reflect how B2B buyers actually buy. Jenna Chambers shares how GTM teams can identify real buying signals, uncover buyer groups, align around account priorities, and use AI to turn signals into action.
How to Drive Sales and Marketing Alignment With Unified Data Sales, Marketing 13 min Updated: August 14, 2026 Sales and marketing alignment is a huge, ongoing problem. Roughly 9 in 10 sales and marketing professionals say their teams are misaligned, worrying in a business environment that only moves faster every year. Because sales and marketing performance gets measured differently, both teams end up using different approaches and systems, producing disjointed content, maintaining a passive relationship, and setting disconnected goals. All of it leads to real revenue leakage. Get our latest insights into your inbox What Is Sales and Marketing Alignment? Sales and marketing alignment is the ongoing set of processes both teams use to collaborate seamlessly across the full range of revenue-generating activity, not a single initiative with a defined end date. It matters more in a digital, distributed business environment, where teams are scattered across geographies and increasingly remote. Alignment isn’t an outcome you reach once, it’s a continuing joint effort, and a large majority of sellers and marketers feel poor alignment actively hurts both the business and the customer experience. Misalignment most commonly shows up when marketing hands off leads without complete or current contact information, when both teams set disconnected revenue goals based on their own separate strategies, or when communication between the two is simply muddled. Cross-functional collaboration smooths these bumps out, and the first real step toward it is putting unified data at the center of the process. A Peek Into Unified Data Data volume keeps growing every year, and it’s growing faster than most estimates from even a few years ago suggested. The real challenge has never been generating data, it’s creating value from it. Nearly half of employees find it genuinely difficult to share information across teams because of poorly integrated systems, and the result is the same dirty data pattern showing up everywhere: incomplete, inaccurate, non-compliant, outdated, inconsistent. This doesn’t just hurt rep performance, it hurts the customer experience directly, a majority of reps believe organizational silos negatively affect how a prospect experiences their team. Unified data solves this by combining data from disparate sources and disconnected systems into a single, central view, capturing data across the sales and marketing tech stack so everyone works from the same picture. It also drives better customer engagement, reduced churn, and higher ARR. Forrester’s research highlights how much buyer engagement now happens before a deal closes: buyers commonly contact sellers five or more times before closing, expect instant answers to complex questions to shorten the cycle, and a large share do substantial independent research before ever talking to sales. That journey leaves behind data breadcrumbs with real insight in them, if a team is actually set up to see it. Making the most of that engagement means sales and marketing need continuous data exchange, not a periodic handoff. New prospect information keeps arriving, and it needs to be accumulated, managed, and kept current so both teams have it at their fingertips. That’s the specific problem unified data solves, and automation, paired with AI for contextual insight, is what makes it work at real scale. Marketing data sales can use: lead and organizational data, lead scoring and qualification results, customer behavior and intent analysis. Sales data marketing can use: connecting campaign objectives and performance directly to revenue, nurturing leads with genuinely relevant content, and building lookalike models of sales-ready leads for new prospecting. The Need for Sales and Marketing Alignment Misalignment between sales and marketing is estimated to cost businesses more than $1 trillion annually, a figure tracing back to Harvard Business Review and IDC research that’s still actively cited in current studies on this exact topic. Sales and marketing have conventionally operated as separate worlds, with different objectives, revenue goals, and processes, creating friction that keeps both from operating at their best. In today’s dynamic environment, where events like economic instability can shift the landscape quickly, a disconnected sales-marketing relationship simply isn’t viable for sustained growth anymore. The buying process itself keeps getting more complex, too. Businesses need to build trust and real relationships, and the buyer today is a buying group, key stakeholders across multiple departments, not one person. Gartner’s research puts the current average at 6 to 10 stakeholders per deal, with enterprise deals frequently reaching 17 or more, and a large majority of B2B deals now involve at least three buying-group members. That buying group wants to engage with multiple people on the seller’s side too, evaluating the company, its process, and its offering as a whole, not just one rep’s individual pitch. As the buying process evolves, so does the customer journey. Traditionally, that journey ended at deal closure. In the modern, bow-tie-shaped funnel, it continues well past close, into onboarding, driving real impact, and sustaining growth, and for subscription businesses specifically, post-sale service and retention matter as much as the initial close, sometimes more. Most SaaS businesses rank customer retention as a genuinely high priority, and for good reason: happy customers are highly likely to purchase again, and companies with strong post-sale support see meaningfully higher repeat-customer rates. At the same time, buyers increasingly want less direct involvement from a rep during the process itself. A majority prefer a rep-free purchase experience where possible, and while selling has become more remote than ever, virtual sales execution still tends to fall short of the win rates teams actually expect. Sales and marketing alignment is a real part of solving that gap, but it has to be more than an exchange of information between the two teams, it has to be a genuine exchange of ideas. Best Practices for Sales and Marketing Alignment With Unified Data Organizations with genuinely well-aligned sales and marketing functions see measurably higher customer retention and higher sales win rates, and strong cross-functional collaboration has been linked to significant increases in key customer spend. Here’s how to actually get there. 1. Define Shared Goals and Strategies Start by establishing common ground through shared Objectives and Key Results,
10 Ways Enriched CRM Data Improves Sales Productivity CRM, Sales 10 min Updated: August 11, 2026 A CRM is one of the most potent tools in a salesperson’s arsenal, and growing digitization should be making it stronger every year. The reality often falls short. CRM data decays fast, Dun & Bradstreet’s research puts annual CRM data decay at around 70%, with a large share of CRM data incomplete at any given time, and the cost of running a manual system on bad data adds up quickly. The impact on reps is real: combing through multiple tools to extract one useful insight for a single deal, and losing real selling time to making sure CRM information is even accurate to begin with. Could better CRM data actually fix this? This guide covers ten specific ways enriched CRM data drives sales productivity, and where AI fits into each. Get our latest insights into your inbox Enriched CRM Data = Better Data Reps want as much visibility on a prospect as possible for an effective deal: names, email, deal size, phone number, and more, and for multithreaded deals, that same information across every stakeholder involved. Raw data pulled from several sources may or may not actually be accurate, and about half of salespeople believe a more effective CRM system would directly improve their productivity. CRM data enrichment is what turns that raw pool into something usable, verifying existing information and adding the supplemental detail that’s actually crucial to closing a deal. It’s a different process than data cleansing: cleansing removes wrong or unusable information, while enrichment verifies what’s accurate and adds new, useful information on top of it. AI Plays a Key Role in Data Enrichment Gartner has identified CRM data entry as a task particularly well suited to AI. AI enriches CRM data by automating the structuring and filtering of raw data, work that’s genuinely time-consuming for a person, and can perform more complex tasks too: predicting, forecasting, recommending, transcribing conversations, qualifying leads, and feeding them into the CRM automatically. As the CRM market keeps growing, so does the practical need for AI to keep pace with the data volume involved. How Enriched CRM Data Improves Sales Productivity Nearly half of all reps feel their process and workflow is too complicated, and that complexity shows up directly as a productivity problem. Here are ten specific ways AI-enriched data helps. 1. Automate Sales Tasks Sales professionals spend a meaningful chunk of their week on CRM data entry alone, adding up to something close to a full day’s work. With data enrichment, reps can offload real tasks: automated, personalized nurture emails, lead reassignment when a rep is unavailable, scheduled follow-ups so nothing slips, engagement tracking (email opens, response rates, task completion), and pipeline management that flags deals sitting past a feasible time-to-convert. Time management is a well-established productivity lever, and giving reps tools that remove friction from the process lets them stay fully committed to it rather than context-switching constantly. Nektar’s Data Foundation, for instance, automates CRM data entry from multiple first-party sources, helps manage the pipeline, and frees up real time for reps to focus on what actually drives revenue: selling. 2. Get Higher-Quality Lead Capture and Predictive Scoring Tracking every stakeholder gets harder as deal size grows. A champion leaving mid-deal, through a role or job change, means re-nurturing every other stakeholder from scratch if a rep hasn’t tracked them all along the way. AI-powered enrichment updates contact details in real time. If a champion loops in a CMO, a CFO, and an IT head across several email threads over time, and then leaves the conversation entirely, a rep doesn’t need to comb through old threads to reconstruct who else is involved, the data is already captured. Enrichment covering demographic, geographic, and financial detail also supports higher-quality predictive lead scoring, letting reps focus on genuinely engaged prospects who fit the ICP rather than assigning scoring values by hand. Buying Group Intelligence is built specifically around this problem, automatically capturing contact data from first-party sources like email, calls, and meetings for accurate lead capture and scoring. 3. Understand Buyer Intent Single-level contact data, a name and an email, doesn’t hold enough transactional, demographic, or behavioral detail to build real trust and rapport. Reps need genuinely complete data to explore patterns, needs, and buyer personas at any depth. Enriched CRM data surfaces additional context too, transaction history, competitor detail, business model, and purchase triggers, all of which support segmentation, personalized interaction, and more targeted campaigns. 4. Enable Personalized Experiences Missing data, incomplete contacts, and mismatched records have long limited a traditional CRM to being a passive data repository. AI is what’s letting CRMs act as an actual personalization guide instead. Buyers expect brands to understand their priorities deeply, and confidence in delivering that kind of personalization at scale remains low across most organizations, which is exactly the gap AI-enriched data addresses. AI-enriched CRM data analyzes large datasets, recommends how to move a specific deal forward, and supports a real customer journey built around targeted segments rather than a single generic pitch for everyone. 5. Avoid Missed Opportunities A CRM that tells a rep whom to target without explaining why leaves real value on the table. AI closes that gap by organizing CRM data, avoiding duplication, and surfacing the small details that actually speed up a deal, plus cross-sell and upsell opportunities a rep might otherwise have missed entirely. With that visibility, reps can redirect focus toward the deals genuinely most likely to close. Daisy AI works the same way, flagging which prospects carry the strongest purchase likelihood, surfacing risk on a given deal, and recommending next steps grounded in real captured activity. 6. Refer to a Single Source of Truth A large share of prospect-facing teams still can’t access real-time, actionable insight, and instead move between several tools just to assemble one piece of analysis on a single customer. Data enrichment brings every data point under one roof, giving reps real-time visibility and
15 Sales Optimization Tools to Fast Track Your Deals in 2026 Sales, Sales Tech Stack 11 min Updated: August 4, 2026 Imagine a machine with every part in working condition, run daily, that still produces suboptimal output. The issue is oiling. Without proper, regular oiling, the various parts can’t function together well. Sales optimization tools are that oiling, keeping the sales function running at its actual potential rather than just technically operational. Get our latest insights into your inbox What Is Sales Process Optimization? Sales process optimization means refining and improving the steps involved in selling a product or service, lead generation, qualification, needs assessment, proposal creation, negotiation, and closing. The goal is greater efficiency and effectiveness, which translates directly into more successful sales and more revenue. How Sales Optimization Tools Work in B2B Sales B2B sales cycles run longer and more complex than B2C, typically involving multiple decision-makers and influencers, and requiring a rep to demonstrate specific business value rather than a generic pitch. Sales process optimization in B2B specifically involves: Identifying and targeting the right prospects. Using data analytics to find businesses that are genuinely a good fit, and building targeted outreach around that fit rather than a broad net. Understanding the buying process. Identifying the actual decision-makers in a deal, understanding their individual needs and priorities, and tailoring messaging to each of them specifically. Creating a value proposition. Articulating specifically how a product or service solves the prospect’s actual pain points, not a generic feature list. Managing the sales process. Using CRM software to track leads and opportunities, setting regular touchpoints, and managing negotiation and closing deliberately rather than reactively. Analyzing and optimizing continuously. Reviewing sales data and feedback to identify what’s actually working, and adjusting the process accordingly rather than running the same playbook indefinitely. A Closer Look at the Sales Optimization Process Define your goals. Set specific targets, revenue, deal count, or whatever metric matters most to your business right now. Analyze your current process. Review sales data, talk to the team, and gather customer feedback to find where the real friction is. Develop a plan. Based on that analysis, decide what actually needs to change, strategy, tooling, or training. Implement the plan. Roll out new processes or tools, train the team, and adjust strategy as needed. Monitor your results. Track progress against the original goals, and keep gathering data and feedback as you go. Continuously improve. Sales optimization isn’t a one-time project. Keep refining based on what the data and your team are actually telling you, and be ready to make bigger changes if goals or market conditions shift meaningfully. Use Cases of Sales Optimization Tools Sales optimization spans automating lead generation, personalizing the sales experience, improving buying-group intelligence, and building out a real sales enablement strategy. A few specific examples: Automate lead generation. Identify potential customers against specific criteria automatically, rather than relying solely on manual prospecting. Personalize the sales experience. Understand each stakeholder in a buying committee individually, and tailor messaging to resonate with each of them, which also supports better multithreading by design. Open more doors with more active contacts. Equip reps with additional contacts automatically discovered across the sales tools they already use, rather than a list built by hand. Improve buying-group intelligence. Give reps immediate access to a buying committee map, so they know exactly whom to engage, how, and when to move a deal forward. Real-time activity intelligence. Automatically capture structured and unstructured data and update it against active opportunities in real time, with no manual work from reps. Implement a sales enablement strategy. Equip reps with the tools, training, and resources they actually need, a sales playbook, CRM access, and regular training on technique and best practice. Optimize the sales funnel. Identify exactly where prospects drop off and simplify the process at that specific point, rather than guessing at what’s broken. Use customer data to drive sales. Build targeted campaigns and personalized outreach around real buying patterns, rather than a one-size-fits-all message. 15 Best Sales Optimization Tools for 2026 1. Freshsales Suite Freshsales Suite (Freshworks’ rebrand of its former standalone Freshsales product) is a comprehensive automation solution giving sales teams built-in email, phone, chat, and telephony, along with AI-powered insight to attract leads and drive deals. Native CPQ makes generating and sharing quotes straightforward, and the platform pulls sales, marketing, and support data into one system so a rep isn’t reconstructing customer context across separate tools. Key features: built-in phone, email, and chat within the CRM itself; AI-powered deal insights and lead scoring; native CPQ for quote generation; visual pipeline and deal management; workflow automation for repetitive follow-up tasks. Best for: Teams wanting communication channels, CPQ, and CRM unified in one platform rather than stitched together from separate vendors. 2. Aviso AI Aviso brings AI-driven forecasting, pipeline inspection, and deal risk analysis into one workspace, paired with MIKI, a conversational AI orchestrator that can query pipeline data and trigger CRM updates directly rather than just displaying a dashboard. Key features: MIKI conversational AI orchestrator for natural-language pipeline queries, predictive forecasting trained on historical deal and engagement data, real-time deal risk and coaching alerts, no-code agent studio for building custom guided workflows. Best for: Teams wanting AI agents built directly into forecasting and pipeline execution, not just a static report. 3. Kluster Kluster standardizes the forecasting and pipeline-review process, giving teams a consistent cadence and reporting structure rather than rebuilding the process every cycle, with AI-driven pipeline-change analysis flagging where a forecast is quietly drifting from reality. Key features: live forecasting with historical accuracy tracking, pipeline-change analysis to catch drift early, security alerts for anomalous pipeline activity, revenue analytics across the full funnel. Best for: RevOps teams wanting forecast consistency and drift detection without building the process manually in spreadsheets. 4. ClickPoint Software ClickPoint is a cloud-based lead management solution that helps reps reach more prospects and close deals more efficiently, with a track record specifically in improving return on lead follow-up. It’s built around the idea
Top 10 Sales Methodologies to Use in 2025 Sales 10 min Updated: August 3, 2026 Every business out there is trying to sell something, whether it’s tangible products, services, knowledge, or software. But the real question is: are they keeping up with the changing trends in customer buying patterns? Customers have gotten wiser, and their preferences and behavior have evolved with time. 67% of customers now prefer self-service over speaking to a company representative, and businesses have to tailor their sales approach to that shift. It’s not enough to just sell something anymore; it has to resonate with the customer and meet expectations they’ve already set for themselves elsewhere. Businesses that try to do this without a structured, strategic approach tend to get poor sales results and low methodology adoption. The right sales methodology keeps a team on track and focused on the actual customer journey, but there are enough methodologies out there to genuinely confuse the decision. This guide covers the basics, and the ten worth considering for selling to today’s customer. Get our latest insights into your inbox What Is a Sales Methodology? A sales methodology is a systematic, strategic approach to selling: a set of principles and practices that guide how a sales team interacts with customers, aimed at understanding customer needs, building trust, and closing more deals. Sales methodology has a real history. Early 20th-century sales technique focused almost entirely on personal persuasion and hard-selling. Consultative selling emerged in the 1950s, prioritizing relationship-building and genuine understanding of customer needs, and the approach became widely known through Neil Rackham’s SPIN Selling in the late 1980s. Since then, many methodologies have emerged, each with distinct features: Challenger Sale, Solution Selling, MEDDIC, SPIN Selling, and Value Selling among the most established. Sales Methodology vs. Sales Process A sales methodology is the framework guiding how a rep approaches selling, understanding needs, building trust, closing deals, and includes principles for how to approach customers, position a product, and handle objections. A sales process, by contrast, is the actual series of steps a team follows to move a prospect from first contact to close: prospecting, qualification, needs assessment, presentation, negotiation, closing, something you can map out as a flowchart. Put simply: methodology is the overarching philosophy; process is the specific sequence of steps that carries that philosophy out in practice. Advantages of Sales Methodologies A defined methodology genuinely fuels sales effort in several distinct ways: Increased efficiency. A structured approach helps reps stay organized rather than improvising every interaction from scratch. Improved customer satisfaction. Focusing on genuinely understanding a customer’s needs and pain points builds real trust. Personalized sales. Reps can tailor their approach to different customers based on actual buying motivation and preference, not a single generic script. Better collaboration. A team following the same methodology works together more effectively, since everyone’s speaking the same language about the deal. Measurable sales efforts. Each step is clearly defined, which makes progress and success genuinely trackable. Sales optimization. Businesses can analyze which parts of the methodology are working and adjust the parts that aren’t. Better sales results. Reps equipped with a proven approach that’s worked in similar situations before tend to close more reliably. A well-defined methodology functions like a map through unpredictable terrain, keeping a team oriented toward its actual goals rather than reinventing the approach deal by deal. How to Choose the Best Sales Methodology for Your Business Dr. Leff BonneyMarketing Professor As an industry, we cling to this incorrect notion that there’s a single best way to sell. We select a sales process or methodology that we believe is a “best practice,” and we tell our sellers to repeat that same sales approach with every customer in every circumstance. It’s a fundamentally flawed strategy. A few factors are worth genuinely considering before choosing, rather than defaulting to whatever methodology is currently trending. Needs of your target audience. Customer needs, preferences, and buying habits should sit at the center of the decision. Independent-research-driven customers might fit a self-service approach like the Value Selling Framework; customers who prefer a more interactive process might fit a hands-on technique like SPIN Selling better. Sales cycle and complexity. Duration and complexity vary by what’s being sold, how the decision gets made, and how many people are involved. A long, multi-touchpoint cycle might fit NEAT Selling or the Challenger Sale better than a shorter one. Product or service. A complex offering needing significant explanation might fit Conceptual Selling; a straightforward offering with a short cycle might fit SNAP Selling instead. Business goals. Market-share growth and new-customer acquisition might point toward Target Account Selling or the Challenger Sale; building loyalty with existing clients might point toward the Value Selling Framework. Sales team. A team of strong relationship-builders might fit Inbound Selling well; a team of deep subject-matter experts might fit MEDDIC better. Industry trends. A shift toward inbound marketing and sales across your industry might make Inbound Selling the right call; a wave of new competitive entrants might make the Challenger Sale’s differentiation focus more relevant. Top 10 Sales Methodologies to Use in 2026 1. SPIN Selling Developed by Neil Rackham in 1988, SPIN Selling diagnoses a customer’s problem before attempting to sell anything, using targeted questions rather than a rigid script. The acronym maps to four question types: Situation (a prospect’s processes and objectives), Problem (their current challenges), Implication (what happens if the problem stays unsolved), and Need-payoff (how a solution benefits the organization, framed for the specific stakeholders who’ll evaluate it). Best used when: sales cycles are long and involve multiple touchpoints with decision-makers. 2. N.E.A.T Selling NEAT Selling starts with identifying which leads are actually likely to convert, so reps focus effort on the right audience from the start. The four pillars: Need (the pain point requiring a solution), Economic impact (the financial benefit of solving it), Access to Authority (identifying and reaching the actual decision-makers), and Timeline (a realistic path to sale and implementation). Need and budget are consistently the two biggest
Everything You Need to Know About Sales Territory Mapping Sales 10 min Updated: August 3, 2026 Successful sales strategies play a key role in achieving business goals. But what drives these strategies from inception to execution, improving sales operations and on-ground performance? Sales territory mapping. Without the right sales territory map template, your sales team could face poor productivity, revenue mismatch or imbalance, subpar revenue performance, poor customer experience, client loss, and wasted resources. So, how do you get sales territory mapping right to achieve business goals and grow your revenue? Let’s find out in this guide. Get our latest insights into your inbox Sales Territory Mapping: Setting On-Ground Sales in Motion Sales territory mapping defines and visualizes the area, sales amount, and revenue your sales team will target. It divides and categorizes customers based on specific characteristics within your ideal customer profile. A sales territory map template also helps you assign categories and customers to the salespersons best equipped to serve them, reaching the right customers in the right areas with the right characteristics to achieve targets and improve growth. The task of aligning your sales plan with business goals in the most profitable way lies with sales managers. From the larger business perspective, sales territory mapping is part of location intelligence, helping segment customers and find more relevant target markets for revenue success. How Is Sales Territory Mapping Instrumental to Business Growth? A sales territory map template does more than act as a blueprint. Here are six ways it contributes to growth. 1. Ties Back to Business Goals Sales territory mapping creates a blueprint for achieving your business goals. It clearly lays out sales targets and directs reps to the most profitable customers or verticals by strategically assigning territories. 2. Maintains Balance One of sales territory mapping’s primary objectives is to secure a balanced and fair distribution of work among sales teams, moving and optimizing resources effectively to maximize revenue potential. 3. Increases Selling Time Reps can increase facetime with clients by cutting down time spent on planning. Sales territory mapping tools can decrease that planning time from months to minutes. 4. Improves Win Rates When reps spend more time selling, they can nurture clients better through the funnel, and each assignment is backed by data. That data offers more visibility into customers and prevents deals from slipping through the cracks, improving customer experience and uncovering new leads to increase win rates. 5. Boosts Morale A sales territory map template encourages intelligent planning, further improving sales productivity. When reps can increase win rates, achieve quota, and earn more, morale improves and attrition drops. It also highlights areas useful for coaching. 6. Extracts Hidden Insights Sales territory mapping helps measure sales data by connecting the map to the CRM, so when multiple salespersons are involved in a deal, you can attribute the sale to the right person. Recognizing the benefits of sales territory mapping is the first step. Step two is understanding its different types. Choosing From 5 Types of Sales Territory Mapping Conventionally, sales territories were based on locations. Today, you can customize them per customer, market, or even product needs. 1. Geography Geographic sales territory mapping is the most commonly used and also the oldest. It classifies your market based on geographical locations, cities, states, countries, and zip codes. For example, Sales Team A can serve Texas, while Sales Team B covers California. To get geographic mapping right, your sales team must have a regional, cultural, and linguistic understanding of the territory they’re allocated, and needs to be available when customers are actually active in that region. 2. Product Product-based sales territory mapping works when you have multiple offerings, categorizing and assigning reps to specific products or technological offerings. It’s useful when certain reps have in-depth expertise on specific products. For example, Team A has expertise in CRM solutions, while Team B caters to clients looking for digital advertising software. Assigning reps to the right products helps them sell to clients more convincingly. 3. Customer The third way to divide sales territories is based on specific customer characteristics like demographics or roles. For instance, Sales Team A may sell to clients with yearly revenue of $500,000, while Sales Team B focuses on higher-margin clients with yearly revenue of $1 million and up. 4. Industry Industry-based sales territory mapping assigns reps to specific industries or verticals. It works best when your product caters to businesses across multiple industries. For example, Team A sells to construction, while Team B covers education, and within education, Team B might handle universities and higher education specifically while Team C is responsible for schools. 5. Sales Channel An increasingly common type of sales territory map template categorizes territories by the sales channels reps or clients use. McKinsey’s research found B2B buyers now use ten or more channels on average as they move through the buying process, combining digital self-serve channels for some activities with video or in-person channels for others. Consider this example: Team A is responsible for selling via digital channels like social media, while Team B sells through offline channels such as cold calling. You may also get more granular, assigning reps with expertise in specific platforms to those mediums, Rep A sells via email, Rep B via LinkedIn. Knowing the key types of sales territories is useful. But figuring out which type suits you best requires a systematic process. Building Your Sales Territory Map Template Whether it’s your first sales territory map template or your seventeenth, these five steps help streamline and simplify the process. Step 1: Define Goals and Objectives Start by defining your goals and objectives, mainly relating to sales, and set measurable goals. Take on revenue goals first, using your revenue forecast to determine how much new revenue you need from each territory, whether from upsells, cross-sells, or new leads. For example, if your goal is to drive sales for a new product functionality that benefits certain industries more than others, that’s the goal to focus
5 Ways to Improve Your Sales Pipeline Visibility Sales 12 min Updated: July 30, 2026 Driving sales pipeline in an organization is like driving a vehicle. You have a goal, a rough map of how to reach your destination, and you want to avoid roadblocks and reach the end point quickly. Navigating a sales pipeline without proper visibility is like driving a car through the night without headlights. You might have a general idea of where you’re going, but you can’t see the obstacles or opportunities directly ahead. The scale of the resulting forecasting problem is well documented. 93% of sales leaders can’t forecast revenue within 5%, even with two weeks left in the quarter. More recent research adds sharper detail: 7% of sales organizations achieve forecast accuracy of 90% or higher. A separate analysis of 270,912 closed-won opportunities by XANT Labs, representing $18.1B in revenue, found only 28.1% closed within 5% of their 90-day forecasted amount, with the average 90-day prediction missing by more than 31%. A lack of visibility can result in overestimating financial performance, leading to missed targets, misaligned resources, and poor decision-making. Without clear visibility into the pipeline, sales teams can’t prioritize leads effectively, resulting in missed opportunities and lost revenue. Poor visibility also makes it harder to identify and fix inefficiencies in the sales process, leading to longer sales cycles and lower customer satisfaction. Get our latest insights into your inbox What Is Sales Pipeline Visibility? Sales pipeline visibility means seeing and understanding the various stages of a company’s sales process, from lead generation to closing deals, with that information available to every revenue team, sales, marketing, finance, product management, and customer success, not just sales alone. Visibility into the pipeline lets sales managers and reps track the progress of opportunities, identify bottlenecks, and make informed decisions about resource allocation and strategy. A typical sales pipeline runs through several stages: 1. Lead generation The first stage: identifying potential customers through cold outreach, email campaigns, or social channels. 2. Qualification Gathering information on budget, timeline, and decision-making process to confirm a lead is actually a good fit before investing further time. 3. Needs analysis Working with the prospect to understand their specific needs and challenges, and how the product or service addresses them, shaping a pitch and proposal around their actual situation rather than a generic template. 4. Proposal Presenting a specific solution, with pricing and details, built around what the needs analysis surfaced. 5. Negotiation Addressing concerns or objections directly, adjusting the proposal or offering incentives as needed to move the deal forward. 6. Closed-won The prospect agrees to buy, converting from potential customer to paying client. Good pipeline visibility means tracking and analyzing every opportunity at every one of these stages, which is what makes accurate forecasting, planning, and process improvement possible in the first place. 5 Ways to Improve Sales Pipeline Visibility 1. Define clear sales stages Clearly defining each stage, with specific criteria for when a deal moves to the next one, is the foundation everything else builds on. With clear stages, teams can accurately track where each deal actually sits and prioritize effort on the ones most likely to close. Analyzing conversion rates between stages produces meaningfully more accurate forecasts than a single end-to-end win rate, and clear stages promote accountability by making it obvious who’s responsible for moving a specific deal forward. 2. Implement a CRM system A CRM is essential infrastructure for pipeline visibility. Dedicated platforms like HubSpot centralize customer and prospect data so sales teams can track and manage every deal from a single system, rather than piecing it together across spreadsheets and inboxes. Reps can view a deal’s status alongside its tasks, notes, and documents in one place. Implementing a real CRM system can increase sales productivity, improve customer relationships, and make the whole pipeline more efficient to manage. 3. Assign ownership and accountability Assigning a clear owner to every deal ensures someone is actually responsible for moving it forward, rather than it drifting between reps or falling through the cracks entirely. Accountability goes a level deeper: specific team members responsible for specific tasks within the process, one person scheduling meetings, another preparing proposals, so nothing depends on someone remembering to volunteer for it. Together, ownership and accountability streamline the sales process and improve visibility, supporting better deal tracking, more accurate forecasting, and more effective decisions. 4. Use data analytics Analyzing conversion rates, win/loss ratios, and sales cycle times surfaces exactly where the process is actually breaking down, turning a vague sense that “deals are taking too long” into a specific, addressable bottleneck. Tracking KPIs like deal size and cycle length over time reveals patterns a single quarter’s snapshot can’t show. Data analytics also sharpens forecasting directly: analyzing historical data and current trends produces a materially more accurate prediction of what will actually close than gut feel, supporting better resource allocation and decision-making. And it supports segmentation and targeting, identifying which prospect types convert best and which strategies actually work for them, so effort gets allocated where it has the best odds of paying off. 5. Conduct regular deal reviews Reviewing the pipeline on a real cadence surfaces deals that are quietly stuck, letting a manager step in and unblock them before they go cold entirely. Regular reviews also create a natural coaching moment: watching how a rep is actually handling their deals reveals exactly where they need support, far more specifically than a generic training session could. Over time, recurring reviews surface patterns in what’s working across the whole process, not just in one deal, letting a team adjust strategy based on real evidence instead of anecdote. A visible pipeline adds real, measurable value to an organization’s revenue, but the actual key to sustained visibility is clean data underneath it. Organizations with clean data have a meaningfully easier time achieving real pipeline visibility than organizations layering visibility tools on top of messy CRM records. Here’s a closer look at why. The Role of Clean Data
10 Best Sales Intelligence Tools for 2026 Sales Tech Stack 12 min Updated: July 30, 2026 Sales intelligence tools and CRMs play different roles in supporting sales. A CRM nurtures customer relationships and tracks interactions; sales intelligence tools give sales teams and leaders the data insight to actually improve performance, how buyers make decisions, how prospects behave at each stage, which tech stack a target account runs, and how to build a forecast and pipeline you can actually trust. The category has consolidated meaningfully since this list was first written. Several tools that used to be independent are now subsidiaries of larger platforms, and the AI layer on top of sales intelligence has moved from a novelty to table stakes. This guide covers what a sales intelligence tool actually is, the current state of 11 major players, and how AI has changed what “good” sales intelligence needs to mean. Get our latest insights into your inbox What Is a Sales Intelligence Tool? A sales intelligence tool gives you the data and insight to make smarter sales decisions: generating high-quality leads, defining your ideal customer profile, and keeping that data accurate and current. The best ones don’t operate as a standalone island, they integrate with your existing CRM and sales stack, so the intelligence they surface actually reaches the workflow a rep is already using rather than sitting in a separate dashboard nobody checks. 10 Best Sales Intelligence Tools for 2026 Nektar, GTM data foundation and AI signal layer LinkedIn Sales Navigator, social and professional relationship intelligence HubSpot Sales Hub, CRM-native sales intelligence and automation ZoomInfo Chorus, conversation intelligence backed by B2B data Traq.ai, AI-powered call recording and coaching Winmo, media and advertising sales intelligence Apollo.io, prospecting, engagement, and sales intelligence in one platform Demandbase One, account-based intelligence and orchestration 6sense, predictive account intelligence and journey orchestration Cognism, compliant contact data and intent signals Overview of the 10 Best Sales Intelligence Tools 1. Nektar Nektar’s role in sales intelligence is upstream of most tools on this list: every platform is only as good as the underlying CRM data it’s reasoning over, and most CRMs are missing a large share of what’s actually happening in a deal. Data Foundation automatically captures every email, meeting, call, and calendar event across a team and writes it natively into Salesforce, HubSpot, or Dynamics, with zero rep effort required. Time Travel™ retroactively corrects historical records as new context arrives, something no other tool on this list does. Daisy AI then surfaces 39 signals across categories including buyer visibility, deal risk, and rep performance, directly on the Salesforce Opportunity tab rather than a separate interface. Key features: zero-rep-effort activity capture across email, calendar, meetings, and calls; automatic buying-group mapping with persona and role enrichment; Time Travel retroactive correction of historical CRM records; Daisy AI signal library spanning deal risk, buyer engagement, and rep performance; vendor-neutral integration alongside your existing sales stack. Pricing: Custom, based on team size and scope. A free CRM scan shows how much of your own pipeline activity is currently missing before you commit to anything. Best for: Salesforce-first revenue teams that need the underlying deal data reliable enough for both reps and any AI layered on top of it. 2. LinkedIn Sales Navigator LinkedIn Sales Navigator helps you find and connect with the people who matter most to your business on LinkedIn specifically, using advanced search and lead recommendations to surface prospects based on criteria you actually care about. Key features: personalized lead recommendations, advanced search filters across LinkedIn’s full network, InMail messaging to reach prospects outside your existing connections, real-time alerts on saved leads and accounts, CRM sync for Salesforce and Dynamics. Pricing: Three tiers (Core, Advanced, Advanced Plus), plus a free trial. Current pricing is best confirmed directly with LinkedIn, since tiers and included seats have shifted more than once in recent years. Best for: Prospecting and warm-path discovery through LinkedIn’s own network graph, best paired with a CRM-native tool rather than used as a standalone system of record. 3. HubSpot Sales Hub HubSpot Sales Hub is a full sales platform combining CRM, sales analytics, email tracking, and automation in one place, with an increasingly broad AI toolset layered on top for outreach drafting, prospect research, and deal scoring. Key features: sales analytics and forecasting, contact and deal management, email tracking and sequencing, sales automation for repetitive tasks, AI-assisted lead and deal scoring. Pricing: Free CRM tier available; paid tiers (Starter, Professional, Enterprise) scale with seats and automation depth. Confirm current tiers directly with HubSpot, since per-seat pricing and included features have changed structurally since 2023 and a fixed table here would likely be stale again quickly. Best for: Teams already running HubSpot as their CRM who want sales intelligence and automation bundled into the same platform rather than a separate tool. 4. ZoomInfo Chorus Chorus has been part of ZoomInfo since 2021 (not Zoom, a common mix-up) and now runs on ZoomInfo’s broader B2B data layer, the GTM Context Graph. It records and transcribes sales calls, using AI to detect sentiment, keywords, and key moments in a conversation, giving managers real-time coaching visibility into calls as they happen. Key features: call recording and transcription, real-time sales coaching during live calls, AI-detected sentiment and keyword analysis, conversation analytics backed by ZoomInfo’s B2B data layer. Pricing: Custom, quote-based. Best for: Teams wanting conversation intelligence with the added weight of ZoomInfo’s data behind it, particularly if you’re already on ZoomInfo for prospecting. 5. Traq.ai Traq.ai is an AI-powered platform that records, transcribes, and analyzes sales calls, extracting objections, opportunities, and next steps automatically rather than requiring a rep to take notes during the call itself. Key features: automated call and video recording and transcription, AI-driven buyer sentiment and risk analysis, centralized deal intelligence storage, custom analysis tailored to your specific industry or sales process, integrations with HubSpot, Zoho, Microsoft Teams, and Google Meet. Pricing: A free tier is available; paid individual and professional monthly plans exist, with enterprise pricing available on request.
9 Sales Commission Software for 2026 Sales 10 min Updated: July 30, 2026 Sales commissions remain one of the oldest and most direct motivators in a sales org, and getting them wrong, through miscalculation, delay, or disputed numbers, erodes exactly the trust a comp plan is supposed to build. Managing commissions manually, through spreadsheets, doesn’t scale past a small team, and it introduces the kind of error that turns a well-designed comp plan into a source of friction rather than motivation. That’s the job sales commission software exists to do: automate the calculation, keep it transparent to reps, and remove the manual reconciliation work from finance and RevOps. Get our latest insights into your inbox What Is Sales Commission Software? Sales commission software (also called incentive compensation management, or ICM) automates the calculation and payment of sales commissions based on quota attainment, deal value, and whatever specific rules a comp plan defines, accelerators, tiers, clawbacks, SPIFs. It removes manual calculation error, gives reps real-time visibility into what they’re earning and why, and gives finance and RevOps teams an auditable, consistent process instead of a spreadsheet that only one person fully understands. 9 Sales Commission Software Platforms for 2026 Spiff, generative AI-assisted commission plan design and management Qobra, no-code compensation automation for modern GTM teams Everstage, no-code commission platform with rep-facing analytics Anaplan, enterprise connected-planning platform with compensation modeling QuotaPath, commission tracking built for SMB and remote sales teams Xactly, enterprise-grade incentive compensation management Performio, data-first commission platform for complex, high-volume sales orgs SalesCookie, budget-friendly commission platform for SMBs OpenComp, compensation platform focused on equity and cash comp together Overview of the 9 Platforms 1. Spiff Salesforce Spiff (fully integrated into Salesforce following the February 2024 acquisition, now sold as Salesforce’s own Incentive Compensation Management product) is a well-established commission platform known for its generative AI assistant, branded Spiff Assistant, which helps admins understand and troubleshoot commission plan logic in plain language, and a Commission Estimator feature giving reps live visibility into potential earnings as they work a deal, directly inside Salesforce. Key features: generative AI-assisted plan troubleshooting (Spiff Assistant), real-time commission estimation during active deals, no-code plan design tools, mobile access for reps. Best for: Teams already on Salesforce wanting commission visibility built into the deal workflow itself, especially now that Spiff operates as part of the Salesforce ecosystem. 2. Qobra Qobra is a sales compensation automation platform built for modern GTM teams, positioning itself around eliminating spreadsheet-based commission management entirely. It automates plan design (accelerators, tiers, bonuses, clawbacks) without requiring code, gives reps real-time visibility into earnings and payout breakdowns, and supports scenario modeling for finance teams evaluating the cost impact of plan changes or new hires. Key features: end-to-end compensation automation from plan design to payout, real-time rep-facing dashboards, scenario modeling and forecasting for finance leaders, broad integration coverage across CRM (Salesforce, HubSpot, Pipedrive), data warehouses (Snowflake, BigQuery), and HR/payroll systems. Best for: Revenue and finance teams wanting to move off spreadsheets entirely, with strong support for both US and European payroll and compliance requirements. 3. Everstage Everstage offers a no-code platform for building commission plans, SPIFs, and bonus structures without engineering support, with rep-facing tools for tracking earnings and understanding plan logic. Key features: no-code plan and rule building, rep-facing earnings dashboards, collaboration tools for plan feedback between finance and sales leadership. Best for: Mid-market teams wanting a no-code platform they can configure and adjust themselves without ongoing vendor or engineering dependency. 4. Anaplan Anaplan is a large-scale connected-planning platform used across finance, supply chain, and workforce planning, with incentive compensation as one significant use case among several. Its core strength is scenario modeling at scale, useful specifically for larger organizations that need to model compensation changes alongside broader business planning. Key features: enterprise-scale scenario modeling and what-if planning, cross-functional connected planning beyond compensation alone, strong integration with BI tools like Tableau and Snowflake. Best for: Large enterprises that want compensation planning integrated into a broader connected-planning platform rather than a standalone comp tool. 5. QuotaPath QuotaPath is built specifically for small to mid-sized businesses and remote sales teams, with a focus on affordability, transparency, and ease of setup relative to enterprise-grade platforms. It offers a free tier for smaller teams, real-time earnings tracking, and self-service rep portals where reps can model “what-if” scenarios for their own commissions. Key features: self-service rep earnings simulator, free tier available for smaller teams, straightforward CRM (Salesforce, HubSpot, Pipedrive) and payroll (Gusto, Rippling, ADP) integrations. Best for: SMBs and remote-first sales teams wanting an affordable, fast-to-implement commission tool without enterprise-level complexity or cost. 6. Xactly Xactly is an established, enterprise-grade incentive compensation management platform used widely by large and Fortune 500 organizations, with strong compliance tooling for operating commission plans across multiple countries and tax jurisdictions. Key features: enterprise-scale plan design and administration, multi-country tax and compliance support, territory and quota planning, strong security and audit-trail certifications (SOC 2, ISO 27001). Best for: Large enterprises needing multi-country compliance and audit rigor alongside commission calculation, not just a domestic SMB use case. 7. Performio Performio positions itself as a data-first commission platform for organizations with complex data environments, aggregating commission-relevant data from multiple CRM, ERP, and other business systems into one place, aimed at industries and teams where commission calculation depends on data scattered across several systems rather than one clean CRM. Key features: multi-source data aggregation for commission calculation, automated approval workflows for payroll processing, audit-ready reporting. Best for: Organizations with commission-relevant data spread across multiple systems (CRM, ERP, and others) that need a platform built to reconcile all of it, not just sync with a single CRM. 8. SalesCookie SalesCookie is a cloud-based commission platform aimed at small and mid-sized businesses, with pre-built plan templates and a straightforward, lower-cost setup relative to enterprise platforms. Key features: pre-built, industry-specific plan templates, multi-currency support for global payouts, straightforward CRM (HubSpot, Pipedrive) and payroll integrations. Best for: SMBs wanting a fast, template-driven setup without building a comp plan structure from scratch. Confirm
10 Killer Tips to Use ChatGPT for Sales Sales 10 min Updated: July 30, 2026 ChatGPT has moved well past the novelty phase in most sales orgs. Reps use it for drafting, research, and prep the same way they use a search engine, reflexively, without much thought. The current generation of models (the GPT-5 family, as of mid-2026) supports persistent memory across conversations, live web browsing, and multi-tool agentic actions as standard capabilities, a meaningfully different tool than the ChatGPT most sales teams first tried in 2023. The real question in 2026 isn’t whether ChatGPT can help with sales. It’s where general-purpose prompting genuinely helps, and where it quietly runs out of road because it doesn’t know anything specific about your actual deals, accounts, or CRM data. This guide covers both: ten practical ways to use ChatGPT for sales work today, and where that approach hits a wall that only grounded, CRM-connected AI can get past. Sales enablement software exists to fix that ratio: giving reps the tools, content, and resources they need to spend more time selling and less time on everything around it. Get our latest insights into your inbox What Is ChatGPT, and What’s Actually Changed ChatGPT is OpenAI’s conversational AI assistant, built on its GPT model family. The capability gap between the original 2022 version and today’s is substantial: current models hold context and memory across sessions rather than starting fresh every conversation, can browse the live web instead of working from a frozen training cutoff, and can take multi-step agentic actions (running a workflow across several tools in sequence) rather than just answering a single prompt. What hasn’t changed: ChatGPT still only knows what you tell it in a given conversation, plus whatever it can find via web search, plus whatever’s in its memory of your prior chats. It has no native access to your CRM, your actual pipeline, your specific accounts, or your team’s real interaction history unless you explicitly connect it or paste that information in yourself. That single limitation is the throughline of this entire guide. Prompt Engineering Still Matters, But Less Than It Did Prompt engineering got treated as a standalone hot skill in 2023; current-generation models need far less prompt gymnastics to get a useful answer, since they’re better at inferring intent from a straightforward request. What still matters: being specific about the actual scenario, the industry, the objection, the buyer context, since a vague prompt still gets a generic answer regardless of how capable the underlying model is. 10 Ways to Use ChatGPT for Sales 1. Sales outreach drafting ChatGPT can draft personalized email templates and social outreach messages, and adapt tone and language across markets and cultures reasonably well. The catch: it can only personalize based on what you give it. A prompt that includes real, specific detail about the actual prospect (their stated priority, a recent company event, their role) produces a genuinely tailored draft. A prompt with a generic persona description produces a generic-sounding email with a name swapped in. 2. Upselling and cross-selling ideas Given a customer’s stated situation, ChatGPT can suggest complementary products or upgrades and help frame the value case for them. It can’t see actual purchase history or usage data on its own, that context has to come from you, pasted in or connected via an integration, or the suggestions default to generic “customers who buy X often want Y” reasoning rather than anything specific to your actual account. 3. Objection handling practice ChatGPT can generate objection-and-rebuttal scenarios for practice, and can role-play as a skeptical buyer raising realistic pushback. This is genuinely useful for rep training. It’s weaker as a real-time objection-handling tool mid-deal, since it doesn’t know what this specific buyer has actually said in prior conversations unless you feed that context in directly. 4. Lead qualification question design ChatGPT is good at generating a structured set of qualifying questions (budget, authority, need, timeline) tailored to an industry or persona. What it can’t do on its own is apply those questions to your actual leads and produce a real score, that requires connecting it to your actual lead data, which is a different (and more valuable) capability than prompting alone provides. 5. Market and competitor research Current models with live browsing can pull recent public information, reviews, and reporting on competitors reasonably well, a real improvement over the original ChatGPT’s frozen training cutoff. It’s still working from public information only. It has no visibility into how your specific deals are actually going up against a specific competitor in your own pipeline, which is a private, first-party data problem no general-purpose AI assistant can solve without being connected to your CRM directly. 6. FAQ and first-line support drafting ChatGPT can draft consistent answers to common customer questions, useful for building out a knowledge base or a first-pass chatbot script. For anything account-specific (a customer’s actual contract terms, their specific configuration, their support history) it needs that information fed in, or it will answer confidently and generically, which is worse than not answering at all in a support context. 7. Sales strategy brainstorming As a brainstorming partner, ChatGPT can synthesize market trends and general best practice into a reasonable starting point for positioning, segment strategy, or channel prioritization. Treat the output as a first draft to react to, not a strategy grounded in your actual pipeline data, performance history, or competitive reality, since it has none of that unless you supply it. 8. Sales training and role-play This is one of the strongest, least caveated use cases on this list. ChatGPT can realistically simulate a skeptical prospect, adapt the objections it raises based on how a rep responds, and give a rep low-stakes practice reps can’t easily get elsewhere. Current models are noticeably better at this than the original 2023 version, holding a more consistent persona across a longer role-play. 9. Deal scoring criteria design ChatGPT can help you design a scoring rubric, which factors matter, how to weight them, what
7 Salesforce Data Enrichment Tools for 2026 Salesforce 10 min Updated: July 30, 2026 What Is Data Enrichment? Your ideal customer isn’t just a name and an address. They’re a full person with specific buying habits, a role, and a digital footprint that either fits your ICP or doesn’t. Raw Salesforce data often shows only a distorted or partial picture of that person and the buying committee around them, more like a dusty attic full of half-remembered details than a usable profile. Your CRM is the backbone of business decisions, and skewed numbers make for skewed strategy. Data enrichment is what fills in the gap. Data enrichment adds complete information to your existing leads and contacts: phone number, address, company size, industry, location, and more. A lead named “Adam Doe from Acme Ltd” isn’t useful until enrichment fills in what Acme actually does and who Adam actually is beyond an email address, at which point a rep can tailor a pitch to an actual person instead of a name in a form field. Data enrichment happens in three ways: Direct: the lead provides complete information themselves, through a form or survey. Internal: you combine scattered information about the same lead across your own disconnected systems into one record. External: a third-party enrichment service appends information from outside sources you don’t otherwise have access to. Enrichment itself relies on two underlying processes: data cleansing (removing obsolete, duplicated, or partial data so the dataset is accurate to begin with) and data appending (pulling data from multiple sources together into one unified profile). Get our latest insights into your inbox Why You Need a Salesforce Data Enrichment Tool 77% of organizations report struggling with data quality issues, and reps are already dealing with a growing buying committee to keep track of. Data enrichment makes both problems more manageable by giving reps as much accurate context about a lead as possible, rather than a name and a guess. With the right enrichment in place, sales teams can: Work from better-quality data. Enrichment adds context and removes redundancy, which builds a more effective, less manually-maintained pipeline. Craft messages that actually land. Enrichment can surface real detail about a prospect’s interests and context, letting a rep tailor outreach that actually resonates instead of a generic template. Target the right people. A complete picture of a prospect’s company reveals who the real stakeholders are, letting reps invest effort in the buying committee that actually matters rather than guessing. Forecast with more confidence. Understanding a buying committee’s actual behavior, backed by real data instead of assumption, supports a more accurate read on which deals will really close. Enrichment also strengthens internal data over time: connecting the dots across enriched records surfaces patterns that help spot churn risk before it becomes a lost renewal. Our Top 7 Picks for Salesforce Data Enrichment 1. Nektar Nektar approaches enrichment differently than the other six tools on this list. Rather than appending third-party data purchased from an outside provider, it automatically captures first-party contact and activity data directly from email, calendar, and meetings, the actual record of what’s happening in your own relationship with an account, and structures it in Salesforce with zero rep effort required. That distinction matters: third-party enrichment tells you about a company in general; Nektar tells you what’s actually happening between your team and that specific account right now. Key features: Automated contact and opportunity management. Contacts get added, edited, and linked to the correct opportunity automatically, so it’s clear who’s actually likely to make the decision, not just who happened to get manually entered. Time Travel retroactive correction. Historical records get corrected as new context arrives, rather than staying static from the moment they were first created, closing gaps a one-time enrichment pass can’t touch. Depth and breadth of activity data. Every email and meeting exchange between buyers and sellers across the customer journey gets captured, giving granular, contact-level engagement visibility across leads, opportunities, and accounts. Data automation via Daisy AI. Teams can define logic that produces quantitative output directly in Salesforce: engagement scores, auto-filled fields like Competitor or MEDDPICC criteria, or an automatic stage update (marking an opportunity closed-lost after three months of no engagement, for instance), meaningfully reducing manual CRM upkeep. Vendor-neutral integration, sitting alongside third-party enrichment tools like the ones below rather than replacing them. Best for: Salesforce-first teams whose real gap is first-party activity data, what’s actually happening with an account, not just firmographic detail about the company itself. 2. ZoomInfo ZoomInfo is the largest and most established firmographic database in this category, providing 360-degree intelligence on individuals and companies, firmographic data including company name, size, industry, and location, natively optimized for Salesforce and appending existing or new records automatically as they enter the CRM. Its scale is the core differentiator: for most B2B categories, ZoomInfo’s database coverage is deep enough that a rep rarely comes up empty on a target account. Key features: Massive, continuously refreshed database covering millions of companies and contacts Deep data insights across both firmographics (size, industry, revenue) and technographics (what tech stack a company runs) Direct-dial and verified contact information for hard-to-reach decision-makers Native Salesforce integration with automatic record appending Intent data signaling when a company is actively researching a relevant category Best for: Teams needing the broadest possible firmographic and technographic coverage, especially for finding and verifying contact information for senior decision-makers. 3. Clay Clay has become one of the fastest-growing enrichment platforms in the category, built around waterfall enrichment: automatically querying dozens of underlying data providers in sequence until a field is actually filled, rather than relying on any single provider’s coverage gaps. Instead of buying one vendor’s fixed dataset, teams build their own enrichment logic, chaining together whichever combination of data sources and AI-driven research steps actually gets the field filled for their specific ICP. Key features: Waterfall enrichment across dozens of underlying data sources for meaningfully higher match rates than any single provider Highly customizable, no-code workflow builder for designing your own
Top 10 Sales Enablement Software of 2026 Sales 12 min Updated: July 30, 2026 Your sales reps have a mile-long to-do list. Generate leads, manage the pipeline, attend customer meetings, follow up on everything else, and somewhere in there, actually sell. It’s overwhelming by design, and it’s one of the biggest blockers for sales teams today. Reps consistently report spending only a third of their time actually selling, the rest goes to admin, research, and internal coordination. Sales enablement software exists to fix that ratio: giving reps the tools, content, and resources they need to spend more time selling and less time on everything around it. Get our latest insights into your inbox Top 10 Sales Enablement Software for 2026 HubSpot Sales Hub, unified sales platform with a broad AI toolset Showpad (now part of Bigtincan), content, coaching, and buyer engagement in one platform Spekit, AI-powered just-in-time enablement inside the flow of work Dock, an AI revenue enablement platform InsideSales, AI-driven sales engagement and buyer intelligence Allego, unified AI-driven learning, content, and coaching Spotio, field sales tracking and territory management SalesHood, independent onboarding, content, and coaching platform VanillaSoft, sales engagement with AI-driven lead prioritization Mindtickle, AI-powered sales readiness and live deal coaching What Is Sales Enablement? Sales enablement is no longer a nice-to-have, it’s a must-have for any organization that wants to stay competitive in today’s rapidly evolving business landscape. Forrester Research Sales enablement means giving sales teams the tools and resources they need to sell more effectively: product knowledge, training, customer insight, automation, and the content that helps a rep have a genuinely useful conversation instead of a generic one. The goal, ultimately, is more revenue through reps who are better equipped to have that conversation. Overview of the 10 Best Sales Enablement Platforms 1. HubSpot Sales Hub HubSpot Sales Hub is a unified sales platform known for a broad, genuinely useful AI toolset spanning outreach drafting, prospect research, report generation, and deal evaluation. It also includes CPQ management, conversation intelligence, document tracking, and sales playbook storage, all inside one straightforward interface. Key features: AI-powered lead and deal scoring, automatic next-step suggestions for guided selling, sales forecasting and customizable dashboards, omnichannel communication, automatic CRM data enrichment, AI prospecting agent, email tracking and scheduling. Best for: HubSpot-native teams wanting a single platform covering CRM, enablement, and AI-assisted selling without adding several point tools. 2. Showpad (Now Part of Bigtincan) Showpad was acquired by Vector Capital and merged with Bigtincan in October 2025; the combined company continues to sell and support Showpad’s platform, so evaluating it today means evaluating a business mid-integration with its former competitor. The underlying product still combines content management, buyer engagement tracking, and coaching in one enablement platform, with AI-guided content recommendations that surface the right asset based on deal stage and buyer context, plus a Shared Spaces feature giving buyers a persistent, trackable hub for shared content across a deal. Worth asking directly about post-merger product roadmap stability before committing to a multi-year contract, a pattern that shows up across most of this category’s recent consolidation. Key features: AI-guided content recommendations, buyer-facing Shared Spaces with engagement analytics, structured coaching and call review tools, content performance analytics tied to deal outcomes. Best for: Enterprise sales teams needing content management, buyer-facing engagement tracking, and coaching bundled into one platform at scale, with the caveat that the product is currently integrating with its former competitor’s stack. 3. Spekit Spekit is a modern, AI-powered sales enablement platform built around delivering enablement in the flow of work rather than a separate tool reps have to context-switch into. Its AI Sidekick uses contextual signals from Salesforce, email, and call tools to anticipate what a rep needs next, surfacing the right playbook, case study, or talking point at the moment it’s actually useful. Reps can create and share content instantly through Deal Rooms, track buyer engagement in real time, and see how each asset actually influences pipeline through Revenue Insights. Key features: AI Sidekick for contextual, just-in-time coaching and recommendations; intelligent content management that flags outdated material automatically; Deal Rooms with real-time buyer engagement data; Revenue Insights tying content usage to deal outcomes; a governance dashboard for content accuracy oversight. Best for: Teams wanting the fastest implementation in this category and genuinely high adoption, since Spekit’s enablement surfaces inside existing workflows rather than requiring reps to learn a new interface. 4. Dock Dock is an AI revenue enablement platform that combines digital sales rooms, customer onboarding hubs, centralized content management, and learning tools for go-to-market teams. It gives reps the content, training, and buyer collaboration usually split across separate tools. Dock covers the full customer lifecycle, from first pitch through onboarding and renewal, and keeps enablement content and playbooks current. Its AI drafts sales content and answers rep and buyer questions from the company’s own material and deal data. Key features: Branded digital sales rooms with buyer engagement tracking Customer onboarding hubs with shared plans and tasks Centralized content library for decks, docs, and links Learning playbooks and courses for ramping reps AI agents that answer using your content and deal data Native order forms and e-signature Salesforce and HubSpot integrations 5. InsideSales InsideSales uses AI and machine learning trained on a large base of aggregated buyer-behavior data to help reps figure out who to call, when, and in what sequence. Playbooks™ turns that into structured, repeatable outreach cadences, guiding a rep through a defined sequence of calls, emails, and follow-ups rather than leaving prospecting to individual instinct. The platform’s Prioritization and Scoring tools rank leads and accounts by actual likelihood to convert, based on historical buyer patterns rather than a static lead-source rule, and its Buyer Intelligence layer surfaces signals (job changes, engagement patterns, account activity) that flag when a previously cold account is worth another look. Reporting and Scorecards give managers visibility into which reps and which cadences are actually driving pipeline, rather than just activity volume. Key features: Playbooks™ for structured, AI-guided outreach cadences; predictive lead and account scoring
Multithreading in Sales: The Modern Secret to Winning More Deals Sales 12 min Updated: July 28, 2026 B2B buying is no longer a solo act. According to a Forrester survey, 94% of respondents sold to a group of three or more individuals, and 38% sold to groups of 10 or more buyers. Gartner puts the current average at 6 to 10 stakeholders, with enterprise deals frequently reaching 17 or more. The decision to invest in a product is not one person’s job. It takes multiple rounds of discussion with stakeholders across departments, and as much as 82% of decisions are made by a buying group rather than an individual. Take technology sellers as an example: those outside IT now influence 63% of technology purchase decisions, pulling finance, legal, and compliance into a process that used to sit almost entirely inside one department. Digital transformation put buyers at the center of the process, and the buying committee got bigger and more diverse as a result. For a successful sale, you need the C-suite, marketing, and other stakeholders on board, and all of them value different things. What does it take to achieve consensus across a group like that? Multithreading Get our latest insights into your inbox What Is Multithreading in Sales? Multithreading is when a sales rep builds relationships with multiple stakeholders in a buying committee, rather than relying on a single point of contact. It directly increases the odds of closing a deal even if the champion leaves the buying organization mid-cycle. Consider the scenario: a rep has spent months building trust with a champion, the person responsible for implementing the solution internally. Then that champion quits for a new opportunity. What happens next? The rep may reach out to a replacement, but nurturing that new relationship takes weeks or months, and deal momentum slows. In the worst case, there’s no identified replacement at all, and the buying committee moves on to another vendor while the rep is still figuring out who to talk to. Multithread the whole committee instead, and a single departure doesn’t take the deal down with it. The Risks of Single Threading Despite multithreading’s effectiveness, most reps still default to single threading, one seller connecting with one buyer. A LinkedIn study found 78% of sales reps are single-threaded. It looks simpler on the surface, and can build a strong relationship with that one contact, but it overly relies on a single individual on each side of the deal. The moment either one leaves, the whole process is disrupted, and rapport has to rebuild from scratch, which drags out sales cycles, raises churn, and lowers win rates. The numbers back this up directly: roughly 25% of buyers change jobs every year, and 80% of sellers admit at least one deal was lost or delayed because a prospect or key stakeholder changed jobs mid-cycle. At that frequency, the revenue lost to single-threading compounds fast. Deploy Multithreading in Sales 1. Get visibility into your buying committee A buying committee is made up of individuals who wield influence across multiple departments, roles, and personas, and understanding who they are and what they each care about is the whole game. The problem is that most sales reps talk to far more people than ever make it into the CRM. Only 2 to 4 contacts typically get logged per opportunity, which means sales managers have effectively no visibility into the real buying committee. This gap, sometimes called “contact blindness,” puts deals at real risk: reps miss the chance to build relationships with the right stakeholders, and managers lose the context they’d need to coach a rep on moving the deal forward. The first step is making sure you actually have visibility into the full buying committee on every deal, and manually entering contacts into a CRM isn’t a realistic way to get there at scale. Once you can see the buying committee, build an account map and connect each stakeholder’s pain points to your solution. Understand what they’re currently using, why they’d need something new, and how much influence they actually carry in the final decision. 2. Multithread early With an account map in hand, reach out to the key decision-makers directly. LinkedIn is a reliable starting point, but case studies of the buyer’s own company or their competitors are another good source, they often name specific stakeholders by title, which tells you who to look for in your target account. Executive sponsors are another underused path: bring up the account in a deal review and ask a leader to tap their own network for a warm introduction. Or ask your champion directly to introduce you to others on the committee. Once connected, run an initial discussion with a clear agenda to understand each stakeholder’s role and priorities before pitching anything. When you do present, avoid a one-size-fits-all pitch, show each department how the solution affects what they specifically care about. 3. Simplify the buying process 77% of buyers describe their purchase journey as challenging and complex, with multiple stakeholders bringing conflicting information and a confusing number of options to sort through. That complexity is actually an opening for multithreading done well, not a reason to sell harder. A buyer-first approach means: learning what the buyer’s actual problem is before defining it back to them, sharing high-quality information openly (buyers with better information are 26% more likely to purchase), aiming to solve the problem rather than just sell into it, showing real, measurable value rather than just describing it, and staying open to detractors on the committee instead of assuming universal enthusiasm. 4. Drive value Value means different things to different stakeholders on the same committee, optimized pricing, regulatory compliance, a specific pain point solved. Gartner’s research found buyers who got information from suppliers that genuinely helped advance their own buying process were 2.8 times more likely to experience an easier purchase and 3 times more likely to go for a bigger deal with less regret afterward. Value doesn’t stop at
Top 5 Trends That Will Impact Sales Operations in 2026 SalesOps 12 min Updated: July 23, 2026 Sales operations spent the last two years absorbing AI into an already-complex stack. 2026 is the year that absorption gets tested for real: Gartner’s research finds over 60% of sales teams now use generative AI, but only about one in three report genuine productivity gains from it. That gap, between adopting AI and actually getting value from it, is the thread running through every trend below. Gartner’s own framing for sales operations leaders heading into 2026 is blunt: the operating model that worked in the past is no longer relevant. Salesops has to reassess where it invests, moving away from generic tool rollouts toward sales transformation, real data analytics, and disciplined AI utilization. That’s a meaningfully different mandate than “add more tools” or “get buy-in for the tech stack,” which is roughly where this conversation sat a few years ago. Get our latest insights into your inbox What is Sales Operations (SalesOps)? Sales operations is the function responsible for removing friction from the sales process so reps can sell faster, more predictably, and with less manual overhead. It’s the team that builds and maintains the sales tech stack, designs process and territory structure, and increasingly, according to Gartner’s own research, supports five or more groups across the business while allocating roughly 68% of its time to nonclient-facing work. Sales ops has a direct line to revenue, and it’s become a more cross-functional, more analytically demanding role than the “keep the CRM running” job it used to be. The 5 Trends Shaping Sales Operations in 2026 1. AI Moves From Experimentation to Governed Execution The headline number for 2026 isn’t adoption. Adoption is already high. It’s the gap between adoption and results. With most sales teams now using generative AI in some form but only a third seeing real productivity gains, the sales ops mandate has shifted from “get AI deployed” to “figure out where it’s actually working and govern the rest.” Gartner names this directly as the top 2026 priority for chief sales officers: building a sales-centric AI portfolio roadmap tied to specific commercial outcomes, rather than a scattershot rollout of whatever tool looked impressive in a demo. What this looks like in practice: sales ops leaders auditing which AI use cases are tied to a measurable outcome (forecast accuracy, time saved per rep, faster deal-risk detection) and which ones are running on faith. The tools that survive that audit tend to be the ones grounded in real, complete data rather than inference, since an AI feature working from gaps produces confident, wrong output rather than a cautious one. 2. GTM Motions Get Rebuilt Around Buyer Preference, Not Rep Convenience The number of B2B buyers who’d prefer a rep-free purchase experience is at 67%, and buyers now weigh an average of seven information sources before a rep is meaningfully involved. But the same research found 69% of buyers still come back to a human rep specifically to validate AI-generated insights before finalizing a decision. The rep’s role hasn’t disappeared. It’s moved from primary information source to the point of confidence and validation at specific moments in the journey, and sales ops is the function responsible for redesigning the GTM motion around that shift rather than the old linear funnel. Marty OvermanEVP Americas Sales at Darktrace You don’t necessarily need a salesperson anymore. You need a sense maker. Someone who can help buyers make sense of all the data and information available to them. Practically, this means fewer generic top-of-funnel touchpoints and more investment in the specific moments that Gartner’s research shows still require a human: complex objection handling, contract negotiation, and validating a buyer’s own AI-assisted research. Sales ops teams that keep measuring rep activity the old way (call volume, email sequences) are optimizing for a motion buyers are actively moving away from. 3. Sales Ops Becomes the Data-Readiness Function for Agentic AI Clean data has been a Salesops priority for years. What’s different in 2026 is why it matters. MuleSoft’s 2026 Connectivity Benchmark found that half of enterprise AI agents currently operate in isolated silos, and Gartner projects 60% of AI projects will be abandoned through 2026 specifically because the underlying data wasn’t ready for AI to use. That reframes data quality from a hygiene task IT or RevOps handles in the background to a direct precondition for whether any of the AI investment in trend #1 actually pays off. The practical shift: Salesops teams auditing CRM completeness before, not after, rolling out an AI feature on top of it. A stage field that’s wrong, a stakeholder who was never logged as a contact, an activity that never made it into the opportunity record, these used to just produce a slightly-off forecast a manager could catch. Fed into an AI agent acting on that data directly, the same gaps produce a wrong output at machine speed, with nobody reviewing it first. 4. Buying-Group Intelligence Becomes a Formal Discipline, Not a Best Practice Multithreading has been “good advice” in sales for years. In 2026 it’s closer to a measurable operating requirement, because the buying committees it’s meant to cover have kept growing. Gartner puts the average B2B deal at 6 to 10 stakeholders, with enterprise deals frequently reaching 17 or more, most of whom never get added as a CRM contact unless something automatically catches them. Salesops teams are increasingly treating buying-committee coverage as a trackable metric, not just a coaching point: how many contacts are actually mapped per opportunity, how engaged each one is, and where coverage has gone stale. That requires detecting stakeholders from actual email and calendar activity rather than relying on a rep to remember to add them, which is a data-capture problem as much as a sales-process one. By far, Nektar has been the most impactful tool to understand our buyers and their influence. Almost immediately we got the visibility we needed for a long time Dan
10 B2B Sales Closing Techniques for 2026 Sales 11 min Updated: July 21, 2026 “How hard can you push a client to close a deal?” It’s still the wrong question, and it’s gotten more wrong since we first wrote this guide. Gartner’s 2026 buyer research found that 67% of B2B buyers prefer a rep-free experience, and buyers now weigh an average of seven different information sources that includes AI tools. All this happens before a rep is meaningfully involved at all. A tactic designed to manufacture agreement doesn’t land well on a buyer who’s already done most of the homework and has little patience for anything that feels like a script. That doesn’t mean closing techniques stopped mattering. It means what “closing well” looks like has changed. 69% of buyers still turn to sales reps specifically to validate AI-generated insights. The seller’s role has shifted from primary source of information to source of validation and confidence at the specific moments a buyer actually needs it. Buyers who combine self-directed research with the right rep interaction at the right moment are 1.8 times more likely to complete a high-quality deal than buyers who go fully independent. Marty OvermanEVP of Americas Sales, Darktrace You don’t necessarily need a salesperson anymore. You need a sense maker who can help buyers make sense of all the data and information available to them. This guide keeps the techniques that hold up under that shift and replaces the ones that don’t. Get our latest insights into your inbox Why Old-School Closing Tactics Backfire Buying committees have gotten bigger and more skeptical. Gartner puts the average B2B deal at 6 to 10 stakeholders, with enterprise deals reaching 17 or more. The average B2B win rates have fallen to roughly 20%, with sales cycles running 38% longer than in 2021. There are more people in the room, more independent research happening before you’re in it, and less tolerance for anything that feels like pressure rather than partnership. The techniques below are built around that reality: buyers who are already informed, skeptical of scripts, and looking for a rep who reduces their risk rather than one who’s trying to manufacture urgency. The 10 B2B Sales Closing Techniques 1. Lead with their goals, not your script For senior buyers, the decision is close to binary: your product either meets a specific goal or it doesn’t. Consultative selling i.e. diagnosing the real problem before proposing anything remains the technique most aligned with what buyers actually want; multiple 2026 studies cite a strong majority of B2B buyers wanting sales reps to act primarily as advisors rather than pitchers. To do this well: Look past the sales script and ICP data. Ask what the actual person in front of you is trying to accomplish this year. Use the language they use to describe the problem, not your own terminology. Ask specifically, and early: “What does success on this initiative actually look like for you?” 2. Don’t lead with a discount Asking about goals is also how you qualify a deal. A buyer with a clear, time-bound initiative and no objective evaluation criteria yet is a very different conversation than one already comparing vendors on price. If a buyer pushes for a discount before you’ve established value, start from a position of value, not concession. And never offer a discount before it’s asked for. Buyers in 2026 are broadly more cautious with spend than in prior years. A rep who leads with price signals that price is the only thing worth discussing. 3. Use competitor comparisons as an opening, not a threat Buyers increasingly already know a competitor’s weaknesses before they talk to you. Independent research (reviews, analyst coverage, peer communities) surfaces vendor gaps that used to only come out in a sales conversation. Assume that, rather than trying to extract it. Ask directly: “On a scale of 1 to 10, how well is [current tool] actually working for you?” Listen for where the gap is, then ask what would need to be true for it to be a 10. Use their own words to describe the gap, and confirm understanding before moving on. The goal is accuracy, not a gotcha. 4. Lead with a mutual action plan, sized to the real buying committee A mutual action plan maps out who needs to do what to close the deal, with dates attached. This matters more now than it did a few years ago, since the buying committee it needs to account for has grown. A MAP built for a single buyer doesn’t hold up against a committee that size. Cover three things explicitly: the realistic timeframe to close, what it costs both sides (due diligence, procurement, compliance), and who’s actually involved on each side. Send a written summary after the conversation and ask them to confirm it. That alone tells you a lot about how seriously the deal is being treated internally. 5. Use “we,” not “you,” when the stakes are shared A small technique, but a real one: replacing “you” with “we” when describing a shared goal (“we’re both trying to hit this timeline”) does more to build genuine partnership than most rapport scripts. It only works if it’s true. Use it when you’re actually aligned on an outcome, not as a rhetorical trick layered on top of a pitch. 6. Run a premortem before you ask for the close Before pushing a deal to the next stage, assume it’s six months from now and it falls apart. Work backward from there. Why did it fail? Did the champion lose internal support? Did budget get reallocated in Q3? Did a new stakeholder join and froze the decision? This technique, borrowed from research psychology and increasingly cited in latest sales research, surfaces risks of a straightforward “any concerns?” question often misses, because it forces specificity instead of a polite “no, we’re good.” 7. Make the close easy, but only once the signals say it’s earned An assumptive close (“Would you prefer to start
Top 15 Guided Selling Tools for 2026 Sales 12 min Updated: July 20, 2026 Imagine planning to build a new house without knowing where to start. You have a rough idea of what you want, but you’re not an architect. A good architect takes your needs, preferences, and budget, and guides you through the decisions, materials, layout, features, that turn a vague idea into an actual house. A guided selling tool does roughly the same job for a sales rep facing a complex deal: it uses customer data and sales expertise to help reps (and increasingly, buyers directly) navigate a purchasing decision, offering personalized recommendations, answering questions, and steering the process toward a decision that actually fits. Get our latest insights into your inbox What Is Guided Selling? Guided selling is a structured approach to leading potential customers through the sales process, using current and historical sales data alongside customer information to help reps make tailored product recommendations and increase the likelihood of conversion. Picture shopping for a laptop online. A guided selling flow asks what you’ll primarily use it for, whether you need a large screen or something lightweight, how much battery life matters, and what your budget is, then recommends a shortlist based on your answers, with detail on specs, reviews, and ratings to help you decide. Guided selling works especially well for complex or high-value purchases, where buyers need more support to feel confident in a decision. Done well, it also builds the kind of trust that leads to a longer relationship rather than a one-time transaction. How Guided Selling Works in B2B SaaS In B2B SaaS, guided selling usually runs through a sales rep or customer success manager rather than a self-serve website flow. It starts with the customer describing their goals, and the guide using that context to recommend relevant products or plans, often supported by a live demo, case studies, or other content that helps the buyer understand how the product actually solves their problem. The Guided Selling Process Gathering customer information. Collecting data on the customer’s needs, budget, and constraints. Identifying pain points. Using that information, usually through targeted questions or a needs assessment, to surface what’s actually blocking the buyer. Providing recommendations. Matching the buyer’s needs to the specific product, plan, or configuration that fits. Presenting solutions. Walking through features, benefits, and pricing in the context of the buyer’s stated problem. Handling objections. Addressing concerns directly rather than avoiding them. Closing the sale. Facilitating the actual purchase once the buyer is confident. Follow-up and support. Making sure the customer is set up for success after the sale, not just after the signature. What Guided Selling Looks Like in Practice Automated sales playbooks. Guided selling depends on a consistent methodology, so the playbook itself needs to be automated and easy to follow, not a document reps have to remember to consult. Needs-identification questionnaires. A short, structured set of questions steers a buyer (or a rep) toward the right recommendation faster than an open-ended conversation would. Real-time responsiveness. A guided selling tool has to react to what’s actually happening in a deal as it happens. Responding to a live signal within minutes rather than hours meaningfully increases the odds of a sale. Pipeline visibility. A good guided selling tool gives reps and managers a clear view into pipeline health, surfacing at-risk deals and letting managers compare how reps are actually spending their time, not just what they report spending it on. Integration with the rest of the stack. Teams typically buy 10 to 15 tools but only actively use 3 to 6 of them, which makes integration a real constraint on a guided selling tool’s actual usefulness. A tool connected only to the CRM and email, with no visibility into content usage or engagement analytics, leaves reps guessing which sales material actually works at each stage. The more complete the data feeding it, the better a guided selling tool performs, which is exactly why the underlying data problem matters as much as the guided selling layer sitting on top of it. Top 15 Guided Selling Tools for 2026 Nektar, CRM data foundation and AI-guided deal signals HubSpot, marketing and sales analytics with guided reporting Salesforce CPQ, configure-price-quote guidance for complex deals Revenue.io, AI-guided sales methodology and real-time coaching ClickPoint, lead management and prioritization Aviso, AI-driven pipeline inspection and forecasting LevelEleven, performance scorecards and real-time coaching Zebrafi, cloud-based guided selling and pipeline insight DealHub, revenue workflow and guided selling playbooks Veelo, onboarding and content guidance in one platform Quark Docurated, content intelligence and recommendation Highspot, sales enablement with AI-guided content and coaching Seismic, enablement platform with AI-guided content and buyer engagement Tact.ai, edge AI for enterprise CRM guidance Vymo, guided selling for financial services Overview of the 15 Best Guided Selling Tools 1. Nektar Nektar’s role in guided selling is upstream of most of the tools on this list: it makes sure the CRM data a guided selling tool depends on is actually complete before that tool tries to guide anything. Data Foundation automatically captures every email, meeting, call, and calendar event across a team and writes it natively into Salesforce, HubSpot, or Dynamics, with zero rep effort required. Daisy AI then turns that captured activity into the specific signals guided selling depends on: deal risk flags, buying-group coverage, and MEDDPICC completeness, surfaced directly on the Salesforce Opportunity tab rather than a separate dashboard. Best for: Salesforce-first teams that need the underlying deal data reliable enough for both reps and any AI-guided tool sitting on top of it. 2. HubSpot HubSpot’s marketing analytics and dashboard tools let you track marketing and sales campaigns in one place, giving your team a shared, reliable data foundation to guide sales efforts from. 3. Salesforce CPQ Salesforce CPQ accelerates quoting, price management, and deal closing, giving reps structured guidance through configuration and pricing decisions on complex deals. Available in three editions, with the full Quote-to-Cash edition also supporting billing and collections. 4. Revenue.io Revenue.io uses AI to guide
7 Elements of a Successful Deal Review RevOps 13 min July 20, 2026 Knowing the ins and outs of your deals is what makes revenue predictable. A good deal review tells you what’s actually happening in your pipeline, where to pivot, and which risks to get ahead of before they cost you the quarter. It’s also one of the most commonly botched rituals in sales. Most deal reviews are unplanned, ad-hoc sessions that interrogate a rep instead of helping them win. The result is the same as it’s always been: inaccurate forecasts, missed targets, and reps who dread the meeting instead of using it. The first question to ask is what’s riding on getting deal reviews right. Before the advent of AI, the data a deal review runs on used to be interpreted by a human. Probably a manager reading a stage field, applying judgment, and catching the obvious gaps. Cut to present times, that same data now feeds AI agents that update opportunity stages, flag deal risk, or trigger next steps directly inside Salesforce, with a lot less human judgment sitting between the data and the action. A deal review built on incomplete data used to produce a bad meeting. Today it can produce a bad decision made by software, at a speed no manager can catch in time. This guide presents a seven-element framework for what a deal review actually needs to look like now. Get our latest insights into your inbox What Is a Deal Review? A deal review is a meeting between a sales manager and a rep about the deals in that rep’s pipeline. It assesses the probability of closing, and agreeing on next-best actions for anything that’s stuck. Done well, it’s a coaching tool. Done badly, it’s an interrogation that produces a status update nobody trusts. What’s Actually Changed The mechanics of a deal review haven’t changed. What has changed is the environment it runs in: Buying committees are bigger, and reps see less of them. Gartner puts the average B2B buying group at 6 to 10 stakeholders, most of whom your rep will never speak to directly, and none of whom show up in Salesforce unless someone manually adds them as a contact. AI agents are now acting on the data a deal review used to just discuss. Salesforce’s April 2026 Headless 360 release made every core Salesforce capability available as an API or MCP tool specifically so agents can read, write, and execute workflows without a human in the loop. When a stage field, a close date, or a forecast category is wrong, it’s no longer just misleading a manager in a Friday pipeline review. It’s potentially misleading an agent that acts on it before anyone notices. The data gap deal reviews have always fought is now measurable at scale. Most CRMs are missing a large share of what actually happens in a deal: meetings that never got logged, stakeholders who were never added, activity that lives in someone’s inbox instead of the opportunity record. That gap used to just make forecasts optimistic. Now it’s the input layer for automated decisions. None of this changes what a good deal review is for. It changes what “good data going into the review” needs to mean. Why You Still Need Deal Reviews Selling has only gotten harder to do by “feel” alone. Longer cycles, bigger buying committees, and more channels for a deal to quietly go sideways all mean a manager’s instinct is a weaker substitute for actual pipeline data than it used to be. Here’s what a deal review still gives you that nothing else does: 1. Identify risks and opportunities early A good deal review surfaces deal risk before it’s a lost deal. It answers questions like which stakeholders have gone quiet, which deals haven’t had a meeting in weeks, or which “commit” deals don’t actually have the engagement to back that up. Sales teams that catch this early can act on it; teams that find out at quarter-close can’t. 2. Align with cross-functional teams Deal reviews often surface why a deal is stuck for reasons the rep alone can’t fix. Maybe it needs a solutions engineer in the next call, a piece of marketing collateral, or executive air cover. A good review turns that into an action item instead of a shrug. 3. Increase rep accountability Every deal review should end with a clear next step for the rep, and a regular cadence to follow up on it. That consistency, not the interrogation, is what actually makes reps more accountable over time. 4. Gain executive support Executive deal reviews are where a rep can borrow leverage they don’t have alone. An exec-to-exec relationship, a strategic sponsorship, a connection nobody on the account team knew existed are few examples. That only works if the review actually surfaces who’s in the room on the buyer’s side, which depends on the buying committee being visible in the first place. 5. Develop sales reps through targeted coaching A deal review tells a manager exactly where a rep needs help, not in the abstract, but on this specific deal, this specific gap. A rep who hasn’t followed up in 30 days needs different coaching than one who’s engaged the wrong stakeholder. Specific coaching, from specific data, is what actually moves a rep’s win rate. Why Most Deal Reviews Still Fail 1. Poor data to begin with This is still the root cause behind most failed deal reviews, and it matters more now than ever. Most organizations’ deal data lives in silos across sales, marketing, and customer success, and a large share of what actually happens in a deal never makes it into the CRM at all. That used to mean a deal review ran on an incomplete picture. Now, with AI agents reading and acting on that same CRM data, an incomplete picture doesn’t just produce a bad meeting. It produces bad automated decisions with nobody checking the work first. 2. No consistent process Deal
5 Reasons for Low AI Sales Tool Adoption (And How to Fix It) RevOps 11 min Updated: July 16, 2026 AI sales tools are everywhere in the stack now. AI SDRs for outbound, conversational assistants that summarize calls, AI-powered forecasting layers, AI note-takers, AI enrichment tools bolted onto the CRM. Adoption of the category has grown fast: 43% of sales reps now actively use AI tools in their daily work, up from 24% in 2023, a real jump in two years. It still hasn’t grown as deep as the buying pattern suggests. 42% of sales and marketing professionals report real dissatisfaction with the AI tools they’ve used, mostly citing data quality and hallucination issues. Gartner projects more than 40% of current AI sales pilots will be cancelled outright due to unclear value or runaway costs. Teams are buying AI sales tools faster than they’re getting reliable value out of them. That gap, bought fast, adopted slowly, is the story of this post. It maps onto five specific, well-documented reasons, each with a fix that doesn’t require waiting for a better model. Get our latest insights into your inbox The AI Sales Tool Adoption Gap, in Numbers 70% of sales organizations say data quality is the single biggest obstacle to getting real value from AI sales tools, ahead of cost, integration difficulty, or which vendor they picked. 42% of sales and marketing professionals report dissatisfaction with the AI tools they’ve used, citing data quality, security, and generative AI “hallucinations” as the main drivers, per ZoomInfo’s State of AI in Sales & Marketing 2025 report. 56% of sales professionals use AI daily, and those who do are roughly twice as likely to exceed their targets than reps who don’t, so the upside is real for the teams that get past the adoption barrier. 24% of sales organizations report low user adoption specifically, with 41% of reps actively resisting the AI tools they’ve been given, a rep-level resistance rate well above what most other sales tech categories see. None of these are model-quality problems. They’re data, trust, and rollout problems that happen to be wearing an AI label. 5 Reasons for Low AI Sales Tool Adoption (and How to Fix Them) 1. The Problem: The AI Tool Is Only as Good as the CRM Data Feeding It This is the most consistently cited barrier specifically for AI sales tools, and it’s the least visible until something visibly breaks. An AI forecasting tool, AI deal-risk flag, or AI-generated account summary built on stale contacts, missing stakeholders, and unlogged activity doesn’t produce a cautious, hedged answer. It produces a confident, wrong one, since the AI tool amplifies whatever data it’s given rather than correcting for what’s missing from it. This is also where an old, familiar problem gets new stakes. Dirty CRM data used to just slow a rep down doing a manual lookup. Fed into an AI sales tool that surfaces a recommendation or, increasingly, acts on the data directly, the same dirty record can now produce a wrong output at machine speed, before anyone reviews it. The Fix: Fix the Data Foundation Before You Add an AI Layer on Top Don’t bolt an AI sales tool onto a stack you already know has gaps in contact and activity data. Fix your data foundation as a first step. Nektar’s Data Foundation automatically captures every email, meeting, call, and calendar event across a team and writes it natively into Salesforce, HubSpot, or Dynamics, with zero rep effort required. Whatever AI sales tool sits on top of that data, Nektar’s or anyone else’s, only gets more reliable once the foundation underneath it is complete. 2. The Problem: Multiple AI Sales Tools Lead to Mixed Priorities Selling doesn’t get easier just because more of the stack is now labeled “AI.” MuleSoft’s 2026 Connectivity Benchmark found the average organization now runs 957 applications, and only 27% of them are actually integrated. And organizations already using AI agents run even more on average, 1,103 apps versus 957. Adding an AI SDR, an AI note-taker, and an AI forecasting layer on top of a stack that already doesn’t talk to itself just gives a rep three more disconnected tools to check, each with its own partial view of the deal. The same research found this is now a governance problem specifically, not just a sprawl one: 50% of AI agents currently operate in isolated silos, disconnected from any cohesive system, and 86% of IT leaders agree that without proper integration, AI agents introduce more complexity than value rather than less. If the head of sales asks which AI tool actually flagged a deal as at-risk, a rep might have to check three separate AI features across three separate tools to find out, which defeats most of the point of automating it in the first place. The Fix: A Unified Data Layer the AI Tools Actually Share An AI sales tool is only as useful as the data it’s working from, and that data has to be the same data every other tool in the stack sees, not a fourth silo with a chatbot interface on top. A unified data layer automatically captures contact, activity, and intent data, the same underlying record every AI tool in the stack should be reasoning over, instead of each one working from its own fragment. Platforms like HubSpot’s Dashboard and Reporting Software show what this looks like when it’s done well: sales, marketing, service, and revenue data centralized under one dashboard, so an AI-generated forecast or attribution report is drawing from the same complete picture a rep sees, not a narrower slice of it. That consistency is what determines whether an AI tool layered on top of the stack actually reduces the number of places a rep has to check, or just adds one more. 3. The Problem: Reps Who Get Burned Once Stop Trusting the Tool at All Trust, not raw capability, is the actual bottleneck for most AI sales tools, and
Winning Multi-Stakeholder Deals in the Modern Buying Journey A conversation with Marty Overman, EVP of Americas Sales at Darktrace. Executive Summary Enterprise buying has fundamentally changed. Most sales teams haven’t caught up. In this episode of The Revenue Lounge, Marty Overman, EVP of Americas Sales at Darktrace, draws on two decades in cybersecurity to explain why the old playbook is broken and what the best sellers are doing instead. The core shift: buyers arrive informed. By the time they engage a rep, they’ve researched the product, talked to peers, and formed a view. The rep who shows up to pitch has already lost the room. What buyers need now is a sense maker. Someone who understands their specific problem well enough to show how a solution actually works in their environment, not just on a spec sheet. Marty’s framework centers on the distinction between product experts and problem experts. Product expertise is table stakes; problem expertise requires genuine curiosity, the right questions, and the discipline to orchestrate the right internal resources at the right moments across a long buying cycle. The conversation also covers the deal signals that matter most (single-threaded engagement is a red flag; multi-functional coverage is the fix), the metrics most teams get wrong (pipeline is the easiest to fake; retention is the hardest to recover from), and what sales leaders need to build right now to stay ahead of a market changing faster than any enablement program can keep up with. Introduction The enterprise sales environment has changed. Buyers are more informed, CFOs are more skeptical, and the old playbook of showing up with a data sheet and running a demo is no longer enough. Marty Overman, Executive Vice President of Sales for the Americas at Darktrace, has spent two decades navigating the cybersecurity market. From Cisco in its early days through Palo Alto Networks, McAfee, and now Darktrace’s AI-driven platform. In a recent conversation on The Revenue Lounge, she offered a candid look at what’s broken in enterprise selling today, and what the best teams are doing differently. The Buying Environment Has Fundamentally Shifted To understand where we are, you have to understand how we got here. During COVID, enterprises spent aggressively on remote access, cloud solutions, and SaaS tools, often without the time or discipline to evaluate whether purchases fit together. The result was a lot of tech debt, half-deployed products, and frustrated security teams overwhelmed by tools they never fully adopted. Now, the pendulum has swung. Marty OvermanExecutive Vice President of Sales CFOs are looking at it, CISOs are looking at it, anybody who’s got any responsibility for a P&L is saying, do we actually have to spend this money? Because we bought that stuff four or five years ago, we overbought, we overspent. That scrutiny isn’t going away. Marty is quick to point out that this isn’t primarily a macroeconomic story. Companies still have the capital. The shift is behavioral. Every dollar now has to justify itself against competing growth investments, and buyers have learned from their own missteps. Sellers who don’t account for this reality will lose deals they used to close easily. Buyers Don’t Need You Early. They Need You Smart Research consistently shows that buyers now prefer to conduct significant research before engaging a sales rep. A widely-cited Gartner figure puts roughly 60% of buyers preferring a rep-free experience up to a certain point in their journey. Marty doesn’t push back on this. She builds her coaching around it. The implication isn’t that sellers are irrelevant. It’s that the moment they enter the conversation has changed, and so has the value they need to bring. Marty OvermanExecutive Vice President of Sales The more information that’s available, the more a human has to help cut through some of that and help make sense of it. You don’t necessarily need a salesperson anymore, you need a sense maker. By the time a buyer wants to engage with a rep, they’ve already checked the spec sheet. They’ve talked to peers. They may know your product better than a junior rep does. What they can’t get from a spec sheet is clarity on whether it actually solves their specific problem, in their specific environment, given everything else they’ve already bought and deployed. That’s the opening for a great seller. https://www.youtube.com/watch?v=3QM2-FVZsGs The Problem Expert vs. the Product Expert Marty draws a sharp line between two types of sellers: product experts and problem experts. Product expertise is table stakes. Anyone can memorize features and fire up a polished demo. Problem expertise requires something harder: genuine curiosity about the customer’s world. Marty OvermanExecutive Vice President of Sales Being a problem expert requires you to ask the questions and to seek to understand. Her analogy here is useful. The best doctors don’t show up already knowing the answer. They ask questions about when the pain started, how the injury happened, what movements make it worse. They’re not doing this to fill time. They’re taking in information that shapes a treatment plan. A seller who rushes to pitch before understanding is like a doctor who prescribes before diagnosing. The practical coaching implication: when you’re talking to a customer, your job is not to inform them about your product. It’s to understand their problem well enough that you can show them what the product actually does for them, how it transforms their workflows, reduces pressure on their team, and integrates with what they already own. Read More See how leading GTM teams build complete buying groups without relying on manual CRM updates with Nektar Demonstrating Operational Reality, Not Just Capability One of the more actionable practices Marty describes is what Darktrace calls a workflow impact assessment, conducted during a proof of value (POV). The problem it solves: buyers have been burned by products that did the thing on paper but never got fully deployed because nobody mapped out how the tool would actually slot into existing operations. Teams are overwhelmed. Nobody’s getting more headcount. A product that adds complexity
The RevOps Playbook for Mastering Sales Forecasting A conversation with Navin Persaud, VP of RevOps at 1Password. Sales forecasting isn’t just about making numbers stretch. It’s about cultivating the insights and systems that make those numbers believable. And in the current hyper-competitive market, reliable sales forecasting can distinguish a thriving business from one that’s treading water. Navin Persaud, Vice President of Revenue Operations at 1Password, has navigated these challenges firsthand. With over 20 years of experience in sales, marketing, and operations, he shares how RevOps can transform forecasting into an engine for strategic advantage. Facebook Twitter Youtube From the Field to the Forecast: The Role of RevOps in Storytelling Picture a live sports broadcast. In that moment, you have the field (the systems and processes), the referee (enforcement and control), and the commentator (analysis and insights). Navin describes RevOps exactly this way: “We build the field of play, we referee what happens, and we provide commentary on the play-by-play.” This vivid analogy sets the tone for the rest of our deep dive: forecasting isn’t just data—it’s the dynamic interplay of infrastructure, discipline, and interpretation. The Forecasting Formula: Predictability vs. Accuracy Many teams chase predictable numbers, but accuracy is the real goal. Navin cautions: “Unless you have an agreed-upon process, reliable metrics, system controls, and CPQ in place, you can’t trust what’s being reported.” Without these, forecasts become little more than educated guesses. The Four Pillars of a Trustworthy Forecast: Standardized Sales Process – A clear methodology with defined stages. Reliable Metrics – Consistent data points that reflect real activity. System Control (CRM/CPQ) – Access restrictions to preserve data integrity. Cross-Functional Buy-In – Alignment among Sales, RevOps, and leadership. These ingredients form the backbone of a forecasting engine. Without any one of them, the forecast risks becoming chaotic rather than credible. https://www.youtube.com/watch?v=FNMSCBUVQuo&t=734s Building Credibility: Earning Street Cred from the Ground Up Forecasting isn’t just structural. It’s political. Navin explains that earning trust within the sales team is non-negotiable. He prefers a bottom-up approach: “If you’re struggling in ops because you can’t get alignment, it’s likely you don’t yet have the credibility with your sales process to guide and enforce change.” He starts by working closely with Business Development Reps (BDRs) and Account Executives (AEs), aligning on how the process impacts their day-to-day. This grassroots validation helps RevOps scale expectations upward without backlash, balancing collaboration with direction (“sometimes it’s a democracy… sometimes it’s ‘this is the way’”). Data Stewardship: Shared Responsibility, Shared Trust Clean data is the lifeblood of forecasting—but nobody owns it in isolation. Navin reframes “data ownership” into a more collaborative model: “I chafe at the word ownership. Data stewardship is shared. Marketing owns their set… but we all share responsibility to ensure it’s reliable and integrated.” Who Stewards What Data: Marketing: Lead and demand data Sales Ops (RevOps): Pipeline and forecast data Finance: Revenue recognition and margin metrics Customer Success: Renewal, retention, and expansion insights This distributed model ensures coherence across the Revenue Operations lifecycle, breaking down siloes and enhancing trust. Technology and AI: Elevating, Not Replacing, Process Forecasting flourishes on the foundation of good process—not glossy tech. Navin emphasizes: “Your CRM must remain the system of record.” Yet, modern advancements like AI add powerful enhancements—real-time pipeline alerts, context-aware insights, and automation of routine tasks: “I don’t need to bug reps anymore. I can now see real-time deal movement and build automation around it.” CRM vs. AI in Forecasting: CRM = structured inputs, stage control, unified pipeline. AI = signal detection, behavioral insights, proactive alerts. Together, they transform forecasting from reactive to predictive. Taming Data Chaos: The CRM Cleanup Checklist Even with systems in place, messy data can derail forecasts. Navin highlights the common pitfalls: Noisy activity capture from multiple systems feeding into CRM (calls, emails, engagement tools). Methodology misalignment, where reps interpret sales stages differently. Forecast Data Cleanliness Checklist: Are opportunity stages standardized and unambiguous? Is every feeder system integrated with clean deduplication? Do reps understand how their entries affect forecasting? Are renewals, expansions, and new business tracked distinctly? This fairness to data clarity is non-negotiable. The Back Door to Forecasting: Don’t Ignore Renewals In tight markets, chasing new pipeline is often harder. That’s why Navin champions the importance of existing customer retention: “Too often companies focus on the front door and ignore the back. Strong companies know growing and sustaining existing customers is the lifeblood of business.” He advocates for early preparation—tracking onboarding health, usage metrics, and expanding mindset long before renewal deadlines: Day 1: Capture analytics on onboarding and early adoption. 6 Months In: Proactively assess health and risks. 90 Days Pre-Renewal: Forecast renewal and surface growth opportunities. Forecasting Culture: Agile, Data-Driven, Evergreen Navin suggests RevOps adopt the rhythm of software teams: plan in sprints, release updates, gather feedback, repeat. “Strong RevOps teams should run like dev teams. Use Agile, release in sprints, test, deploy, monitor.” This continuous-improvement mindset fuels a forecasting culture centered on data—not chatter—and long-term credibility over quick wins. The Forecasting Flywheel: From Clean Data to Predictive Power Putting it all together, we arrive at a virtuous cycle: The Forecasting Flywheel: Clean, trusted data → 2. Reliable forecasting → 3. Leadership alignment → 4. Better planning & execution → 5. Process improvements → 1. Back to cleaner data Each loop reinforces the next, turning forecasting from an internal tool into a growth catalyst. Final Thoughts: Forecasting as Strategic Trust Forecasting isn’t just a report. It’s a signal of organizational maturity. Navin’s insights remind us that: You need process clarity before predictability. Credibility is built through empathy and collaboration with sales. Data cleanliness must be everyone’s responsibility. Technology empowers, but can’t compensate for human alignment. Renewals are not afterthoughts—they’re forecasting opportunities. Change management requires agile methodology and discipline. “Forecasting is the field we play on. If the rules aren’t clear and the commentary isn’t trusted, the game falls apart.” — Navin Persaud Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources
The Evolving Role of SDRs: Navigating Outbound Fatigue & Embracing Buying Groups A conversation with Kelly Lichtenberger, VP Sales Development at HiBob. Sales development is at a crossroads. What once worked—mass sequences, endless dials, and a “spray-and-pray” approach, is now leading to diminishing returns. Buyers are fatigued, inboxes are overflowing, and SDRs are burning out. Yet, building top-of-funnel pipeline is still one of the most critical levers for revenue growth. So, how does the modern SDR team succeed in an environment defined by noise, automation, and shrinking buyer attention spans? In this episode of The Revenue Lounge, Kelly Lichtenberger, VP of Sales Development at HiBob and author of Prospect Like a Girl: Winning in Sales Using Your Emotional Intelligence Over Artificial Intelligence, shared her perspective on building authentic connections, leveraging emotional intelligence, and balancing technology with personalization. Here’s the detailed breakdown of her insights. Facebook Twitter Youtube From Phonebooks to AI: Kelly’s Journey Through Sales Development Kelly’s career started long before SDR platforms and LinkedIn existed. She recalls flipping through phone books, driving past office buildings, and tracking down numbers to call. “When I started my career, there was no Google, no AI. We literally had a phone book. If I drove down a highway and saw a new sign on a building, I’d try to figure out how to call them.” – Kelly Lichtenberger Her path took her from running her own outsourcing company to consulting, and ultimately to leading HiBob’s 60+ global SDR team. That breadth of experience shapes her philosophy today: technology should enhance—not replace—the human connection in sales. The Great Ignore: Why Outbound Fatigue Is Real Kelly calls today’s prospecting environment “heavy.” Before COVID, it took ~11 touches to reach a prospect. During COVID, that ballooned to ~18. Today, SDRs need 25–27 touches across 45 days to break through. And prospects are more sophisticated than ever: They recognize templated, generic messages instantly. They consume information across fragmented channels (email, phone, LinkedIn, mobile). They’re trained to hit “delete” on irrelevant outreach. “If you keep doing the same thing over and over with zero results, it’s the definition of insanity. You have to change it up. Personalization and creativity are the differentiators now.” – Kelly Lichtenberger https://www.youtube.com/watch?v=a8MVl8JiFiE Quality Over Quantity: Rethinking SDR KPIs For years, SDR success was measured in sheer volume—calls made, emails sent, meetings set. But Kelly warns that volume alone creates diminishing returns. At HiBob, her team focuses on: Meetings completed (not just scheduled) Pipeline acceptance rate (ensuring quality over filler opportunities) Multi-threading impact (how many stakeholders they can influence in a buying group) Personalization at Scale: The New SDR Playbook Kelly believes personalization isn’t optional anymore—it’s the SDR’s competitive edge. And it goes beyond “Hi {FirstName}” tokens. Some tactics HiBob SDRs use: LinkedIn signals: tracking job changes, posts, and shared connections. Video outreach: short, phone-friendly videos to stand out in a crowded inbox. Creativity tests: A/B testing creative messages, then templatizing winners into sequences. “Please keep saying the phone call is dead—because that’s where I win. But it’s not about feature dumps on voicemails. It’s about elevating your game and being interested, not interesting.” – Kelly Lichtenberger Emotional Intelligence > Artificial Intelligence Kelly’s book, Prospect Like a Girl, argues that emotional intelligence (EI) is more important than artificial intelligence (AI) in modern sales. While AI helps SDRs save time (e.g., autodialers, transcription, sequencing), the differentiator is still human connection. EI Builds Trust: Asking, “Maybe you can help me?” opens doors faster than product pitches. EI Reads the Room: SDRs must listen, not bulldoze. Prospects already know a lot before taking the call. EI Creates Curiosity: The goal isn’t to close in the first message—it’s to spark interest and earn the next touch. “No is as powerful as yes. Maybe is what kills the deal.” – Kelly Lichtenberger The Buying Group Motion: Moving Beyond MQLs Kelly echoes what many modern revenue leaders believe: the era of the individual MQL is over. HiBob’s team is experimenting with buying group strategies: Creating early-stage opportunity “containers” for accounts showing swarming signals. Engaging multiple champions instead of betting on one lead. Aligning with marketing to ensure SDRs aren’t just chasing scores but confirming initiatives with multiple stakeholders. What Traits Make a Successful SDR in 2025? Interestingly, HiBob often hires SDRs without sales experience. Kelly looks for traits over résumés: Coachability – willingness to be trained. Curiosity – ability to teach even their leaders new tools or perspectives. Resilience – grit to handle rejection and keep evolving. “Sales isn’t Friday golf and making money. It’s really hard work. But if someone shows me their why and willingness to be coached, I’ll give them a chance.” – Kelly Lichtenberger Will AI Replace SDRs? Kelly Says No The elephant in the room: will AI make SDRs obsolete? Kelly’s answer: absolutely not. AI is a productivity booster, not a replacement. Just like Netflix didn’t stop us from watching movies—it changed how we consume them—AI will change how SDRs prospect, not eliminate them. “If you as a human don’t learn how to work in both worlds—AI and human—you’re the one who will get replaced.” – Kelly Lichtenberger Key Takeaways for Modern SDR Leaders Outreach requires 25+ touches—design for persistence. Shift KPIs from activity metrics to pipeline quality. Personalization is a non-negotiable—test, learn, templatize. Emotional intelligence builds trust where AI cannot. Adopt buying group motions—multi-thread every deal. Hire for traits, not résumés. Coachability wins. AI will augment SDRs, not replace them—unless they refuse to adapt. Final Word Sales development isn’t dying—it’s evolving. The SDRs who embrace creativity, curiosity, and emotional intelligence will thrive, while those who cling to outdated, volume-heavy tactics will struggle. HiBob’s Kelly Lichtenberger reminds us that the human touch is still the ultimate differentiator in sales. “Be interested, not interesting.” – Kelly Lichtenberger Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources
10 Best Deal Tracking Software for 2026 RevOps, Sales 10 min Updated: July 27, 2026 A sales team juggling multiple deals at once, meetings, follow-ups, and deadlines, can feel like it’s carrying more than any spreadsheet or memory can reliably hold. Deal tracking software exists to take that weight off, giving a team one place to see exactly where every deal actually stands instead of piecing it together from memory and a dozen open tabs. Get our latest insights into your inbox What Is Deal Tracking Software? Deal tracking software helps sales professionals manage their pipeline by keeping every deal’s status in one central place, from initial contact through to close. If you’ve got dozens of deals in flight, some small, some enterprise-scale, deal tracking software shows you at a glance which ones are in negotiation, which need a follow-up call, and which are genuinely on track to close, rather than requiring a rep or manager to reconstruct that picture from memory. 10 Best Deal Tracking Software for 2026 Nektar EngageBay Kapture CX Salesmate CRM Pipedrive Insightly Nutshell Salesflare BIGContacts Freshsales Suite Overview of the 10 Best Deal Tracking Software for 2026 1. Nektar Nektar makes sure the underlying activity data, every email, meeting, call, and calendar event, is actually captured and structured against the right deal before anything tries to track or score it. Data Foundation does this automatically, with zero rep effort required, writing directly into Salesforce, HubSpot, or Dynamics. Time Travel retroactively corrects historical records as new context arrives, closing gaps a point-in-time capture tool can’t touch. Daisy AI then surfaces the specific signals that matter for deal tracking: buyer engagement scoring, deal risk flags, buying-group coverage, and time-in-stage analysis, directly on the Opportunity tab rather than a separate dashboard nobody opens. Key features: Buyer-seller activity captured automatically as the leading indicator of real deal progression, not a rep’s memory Time-in-stage measurement to identify precisely where deals are stalling, not just that they are Deal risk flags and engagement scoring that surface high-priority opportunities before they go cold Time Travel™ retroactive correction, backfilling up to 12 months of historical activity as new context arrives Buying-group intelligence that auto-detects stakeholders from real email and meeting activity, rather than requiring a rep to log them Vendor-neutral integration, sits alongside Gong, Outreach, Salesloft, and other tools already in your stack rather than replacing them Best for: Salesforce-first, Salesforce, HubSpot, or Dynamics teams that need the underlying deal data trustworthy enough for both reps and any AI layer built on top of it. Pricing: Custom, based on team size and scope. A free CRM scan shows how much of your own pipeline activity is currently missing before you commit to anything. 2. EngageBay EngageBay is an all-in-one CRM and marketing automation platform aimed squarely at startups and small-to-midsize teams that want sales, marketing, and support tools bundled together rather than bought as separate point solutions. It’s trusted by over 150,000 companies, largely on the strength of its price-to-feature ratio relative to HubSpot or Salesforce, and it’s added AI features (email and campaign generation, deal scoring, smart insights) on top of its original bundle over the past couple of years. Key features: Unified sales lead information across marketing, sales, and support in one platform AI-powered deal scoring to prioritize which leads are actually worth a rep’s time Centralized client data with contact tagging, filtering, and custom fields Built-in email marketing, landing pages, live chat, and helpdesk/ticketing Estimated revenue generation forecasting tied to pipeline stage Over 30 native integrations, including Zapier, Mailchimp, Twilio, and Stripe Best for: Startups and small businesses wanting sales, marketing, and support consolidated into one affordable platform rather than stitched together from several point tools. Pricing: Free plan available for up to 15 users and 250 contacts. Paid tiers start around $15/user/month (Basic), scaling to roughly $65/user/month (Growth) and $120/user/month (Pro), with meaningful discounts on annual or biennial billing. Confirm current tiers directly, since EngageBay has adjusted contact limits and feature gating more than once in the past year. 3. Kapture CX Kapture CX (also marketed as Kapture CRM) bundles sales, marketing, operations, and customer service into one platform, with a particular strength in omnichannel support and enterprise-grade customization via 500+ APIs. It’s built for organizations that want centralized control over pre-sale activity and post-sale support from the same system, and it ships with industry-specific configurations for verticals like retail, hospitality, real estate, and healthcare rather than a one-size-fits-all template. Key features: Custom organizational hierarchies with sales performance data broken out by rep, team, or region Omnichannel support spanning email, chat, social, and direct campaigns from one dashboard Integrated sales monitoring with real-time KPI tracking (calls answered, response times, ticket resolution) 500+ pre-built integrations, including SAP, Oracle, Shopify, Dynamics 365, and Salesforce AI-powered live chat and self-service portal for both sales and support use cases Over 500 configurable reports for pipeline, agent, and campaign performance Best for: Mid-market to enterprise teams, especially in retail, hospitality, or field-sales-heavy industries, wanting sales and post-sale support unified in one heavily customizable platform. Pricing: Three tiers, Essential, Professional, and Enterprise, all custom-quoted based on team size and configuration. No published flat-rate pricing; request a demo for a specific quote. 4. Salesmate CRM Salesmate CRM pairs a built-in sales activity tracker with automation for repetitive tasks, follow-up emails, CRM field updates, so managers can monitor rep activity in real time without reps losing time to manual admin. It’s frequently cited by reviewers as delivering enterprise-level features at a noticeably lower price point than HubSpot, Salesforce, or Zoho, which is its clearest differentiator in a crowded category. Key features: Automated sales activities and multi-step playbooks triggered by deal stage or behavior Sales timeline view for tracking every touchpoint on a deal in chronological order Smart calendar view synced across team members for scheduling and follow-up visibility Built-in calling, texting, and email from directly within the CRM record Workflow automation for lead routing, task assignment, and stage progression Native integrations with Meta Lead Ads, Google
Selling to People, Not Personas: Redefining B2B Sales with Buyer-First Intelligence A conversation with Amarpreet Kalkat, Founder & CEO at HumanticAI. In the era of hyper-informed buyers and complex purchasing journeys, traditional sales strategies are crumbling. Outdated, persona-based approaches no longer resonate in a world where buyers are more skeptical, independent, and resistant to generic outreach. In a recent episode of Revenue Lounge, we sat down with Amarpreet Kalkat, Founder and CEO of Humantic AI, to unpack what it truly means to adopt a buyer-first approach. And how personality-driven sales is transforming the way sellers connect, engage, and win. This blog dives deep into Amarpreet’s insights, drawing from his 25+ years of experience in building intelligent products, and explores how his technology is helping sales teams humanize the sales process. Facebook Twitter Youtube The Buyer’s World Has Arrived and Sellers Must Adapt “You don’t sell. You help people buy.”— Amarpreet Kalkat In Amarpreet’s view, sales has always been about the buyer—but never more so than today. With dozens of vendors offering similar solutions, what separates winners from the rest isn’t product features or aggressive pitching. It’s perspective. The problem? Most sales methodologies—whether it’s MEDDIC, Challenger, or SPIN—are seller-centric. They teach sellers to “run their playbook,” not necessarily to understand their buyers as people. But data shows the stark gap: Average seller win rate: 17% Elite seller win rate: 62% That’s not just a small performance delta—it’s a chasm. And Amarpreet believes the secret to closing that gap lies in a true shift to buyer-first thinking. Stop Selling to Personas. Start Selling to People. Sales teams often anchor outreach strategies around personas—job titles, functions, firmographics. But Amarpreet challenges that framework: “A persona doesn’t buy. A person does.” With Humantic AI, sellers can move from broad persona targeting to individual buyer intelligence, understanding not just what a prospect does—but who they are. This includes: Communication preferences Personality traits (based on DISC profiling) Risk appetite Decision-making style Motivators and fears This human layer enables sales reps to craft emails, calls, and presentations tailored to how a specific buyer thinks—not just their role. https://youtu.be/iMDGlZVhaBc How Personality AI Works Behind the Scenes So how does Humantic AI gather this intelligence? It pulls public data from LinkedIn and other online sources It processes that data through proprietary DISC-based AI models It surfaces insights on personality traits, behavior patterns, and communication style These insights are delivered directly into tools sellers already use—Salesforce, LinkedIn, Salesloft, Outlook, and more The goal? Equip sellers with buyer-aware recommendations at every step of the deal. And it’s more than just better email intros. Amarpreet explains how Humantic can even suggest whether to open an email with a friendly “Hope you’re doing well” or skip that for a more concise greeting—based on the buyer’s disposition. The Impact: Real Results from Real Companies Skeptical about the impact of buyer intelligence? The numbers speak for themselves. One client saw win rates jump from 15% to 50% Another reported a 151% increase in pipeline for a test group Public company Domo cited a 15–30% lift in win rates after adopting Humantic AI And it’s not just about closing deals faster. Amarpreet emphasizes how personality data helps navigate complex buying committees. With up to 12–14 stakeholders involved in B2B decisions, understanding the emotional and decision triggers of each person is critical. “Deals are lost in rooms sellers never enter. We help you win in those rooms.” Operationalizing Buyer Intelligence in the Sales Process Humantic AI is designed to work across the entire sales journey—not just top-of-funnel outreach: Stage Tool/Feature Use Case BDR/SDR Chrome Extension / Outreach Integration Personalized email and call scripts AE Meeting Prep Tools Pre-meeting research and message customization Sales Team Buying Committee Map Stakeholder analysis and engagement planning RevOps Platform Integration Insight management within CRM and SEP tools And unlike many AI tools that overwhelm teams, Humantic focuses on enhancing human touchpoints, not replacing them. AI Isn’t Just a Buzzword. It’s a Strategic Lever In today’s crowded AI market, Amarpreet warns against getting distracted by shiny tools: “AI should be wings for the flyers and crutches for the walkers.” For sales leaders evaluating AI, he recommends starting with problems, not features. What’s the root challenge—low CRM usage? Poor email response rates? Ineffective stakeholder engagement? The right AI tool should solve that problem with minimal friction. A Path to Sales Respect and Buyer Trust Amarpreet closes the conversation on a powerful, personal note. Despite being the lifeblood of the economy, sales still lacks social respect. “Nobody grows up saying, ‘I want to be a salesperson.’ But without sales, nothing moves.” He draws an analogy to doctors—once seen as quacks, now among the most respected professions. Amarpreet believes sales can earn that respect too—but only if sellers embrace empathy and buyer-first engagement at scale. Actionable Takeaways for Sales Teams Here’s how to start implementing a buyer-first approach right now: ✅ Audit your current outreach — Are you customizing based on personas or individuals? ✅ Understand your buyers’ decision-making styles — Tools like DISC can help. ✅ Invest in emotional intelligence — Winning trust requires more than just logic. ✅ Use AI to amplify, not automate — Layer intelligence onto your existing workflows. ✅ Map your buying committees — Know the silent killers and what drives them. ✅ Treat sales as a helping profession — Shift your team culture from persuasion to enablement. Final Thoughts Personality-driven selling isn’t a gimmick—it’s a competitive edge. In a world where buyers ghost generic pitches, deep personalization rooted in emotional intelligence is the new table stakes. With tools like Humantic AI and leaders like Amarpreet paving the way, the future of B2B sales looks a lot more human. Want to hear more stories from revenue leaders? Subscribe to The Revenue Lounge podcast to never miss an episode! More Resources
Learn how revenue teams are operationalizing buying groups to escape lead-based inefficiency, multi-thread deals & improve pipeline conversion.
