Top 5 Trends That Will Impact Sales Operations in 2025 RevOps 10 min Imagine having a machine. A machine with all the parts in working condition, it’s even run daily but produces suboptimal outputs.  The issue is – ‘Oiling.’ Without proper and regular oiling, the various parts of the machine can’t function properly. To make the machine work cohesively, oiling is required.  Sales optimization tools can help with the oiling. It is done so that the sales function produces optimal results.  What is sales process optimization? Sales process optimization refers to refining and improving the steps in selling a product or service to a customer. The process typically includes steps such as lead generation, lead qualification, needs assessment, proposal creation, negotiation, and closing the sale. Sales process optimization aims to increase efficiency and effectiveness, resulting in more successful sales and increased revenue. How do Sales Optimization Tools Work? Sales process optimization is essential in B2B sales, where the sales cycle is often longer and more complex than in B2C sales. In B2B sales, the process typically involves multiple decision-makers and influencers, and the sales rep needs to demonstrate how the product or service will address the business’s specific needs. Here are some key ways in which sales process optimization works in B2B sales: 1. Identifying and targeting the right prospects Sales process optimization in B2B sales involves identifying and targeting the most promising prospects with customized messaging and outreach. This involves using data analytics to identify businesses that are a good fit for the product or service and creating targeted marketing campaigns to reach them. 2. Understanding the buying process B2B sales often involve multiple decision-makers and influencers, and it’s important to understand the buying process for each prospect. Sales reps need to identify the key decision-makers, understand their needs and priorities, and tailor their messaging accordingly. 3. Creating a value proposition In B2B sales, it’s important to demonstrate how the product or service will provide value to the business. Sales reps need to articulate a compelling value proposition that addresses the prospect’s specific needs and pain points. 4. Managing the sales process B2B sales often involve a longer sales cycle than B2C sales, and it’s essential to manage the process effectively. This may include using CRM software to track leads and opportunities, setting up regular touchpoints with the prospect, and managing the negotiation and closing process. 5. Analyzing and optimizing the sales process Finally, sales process optimization in B2B sales involves analyzing sales data and feedback to identify areas for improvement. Sales reps need to be able to adjust their approach based on what works and what doesn’t and continually refine their sales process to improve outcomes. A Closer Look At a Sales Optimization Process Now that we have understood the role of sales optimization in B2B segment, let’s understand the process in a step-by-step format:   1. Define your goals The first step in sales optimization is to define your goals. This may involve setting specific targets for revenue, number of sales, or other metrics that are important to your business. 2. Analyze your current sales process The next step is to analyze your current sales process to identify areas for improvement. This may involve reviewing your sales data, talking to your sales team, and gathering feedback from customers. 3. Develop a plan Based on your analysis, develop a plan for optimizing your sales process. This may involve making changes to your sales strategy, implementing new tools or technologies, or providing additional training to your sales team. 4. Implement your plan Once you have a plan in place, it’s time to implement it. This may involve rolling out new processes or tools, providing training to your sales team, or adjusting your sales strategy. 5. Monitor your results As you implement your plan, it’s important to monitor your results. Track your progress against your goals, analyze your sales data, and gather feedback from your team and customers to identify areas where you can continue to improve. 6. Continuously improve Sales optimization is an ongoing process, so it’s important to continue refining and improving your sales process over time. This may involve making small adjustments based on feedback and data analysis or making larger changes if your goals or market conditions shift. Let’s have a look at some sales optimization examples to understand the use cases of the above processes in real-life.  Use Cases of Sales Optimization Tools Sales optimization has a wide range of use cases in B2B sales, including automating lead generation, personalizing the sales experience, improving group intelligence, and implementing a sales enablement strategy. By leveraging sales optimization tools and techniques, businesses can improve their sales outcomes, increase efficiency, and drive revenue growth. Here are some examples of sales optimization that businesses implement to improve their sales outcomes: 1. Automate lead generation Businesses can use automated lead generation tools to identify potential customers based on specific criteria instead of relying solely on manual prospecting. This can help streamline the sales process and reduce the time and effort required to find new leads. 2. Personalize the sales experience Personalization can help sales teams better understand the specific needs and preferences of the stakeholders in a buying committee. This allows them to tailor their messaging and approach to each stakeholder, increasing the likelihood of resonating with each individual and ultimately closing the deal. By having insights into all the stakeholders, sales teams can also multithread better, meaning they can engage with multiple stakeholders simultaneously and build a rapport with each of them.  3. Open more doors with more active contacts Encourage multithreaded conversations by equipping your reps with additional contacts. Provide your representatives with more contacts automatically discovered from all sales tools.  4. Improved group intelligence Instantly grant your reps the knowledge of a buying committee map, so they know whom to engage, how, and when to best influence deal progress. 5. Real-time activity intelligence Automatically capture both structured and unstructured data and update it in real-time against active opportunities

Revenue leader’s guide to successful board meetings! GTM RevOps 10 min It’s quite common for sales leaders to get invited to board meetings. So, what do you do when called in to present your sales strategy and report card to the board? At Nektar.ai, we spoke to 72 professionals who have been Board members, VP Sales, Founders and CEOs and asked them this very same question. This playbook is a result of those responses and best practices. Just like for any deal in your CRM system, where you define your sales process, you need to break your board interaction as well into logical stages. Pre-meeting: What’s the construct of the board? Research about the board members and the role they play. What’s the preparation required for the board meeting? In-meeting: What’s the approach one can take to handle the board meeting successfully and build one’s credibility? Post-meeting: How should revenue leaders engage with boards and their CEO post-board meetings? Pre-Meeting Checklist Understand the dynamics of the board. A VP of sales must analyze his/her board similar to how they would draw an account plan and relationship map for a strategic prospect. Eg. Which board members are very involved in the strategy side and carry a big influence on the board? Which members are functional experts and tend to get operationally involved? What are the backgrounds of the various members? What role do they play? Know what matters. Spend time in advance or at the beginning of the meeting asking the question “What are the top 3 things you want to know about our sales strategy?” Going prepared with an answer to this question will help you to save a lot of time and trepidation. Begin with the end in mind. Before you begin, understand what they want. It can be tempting to spend a lot of time to prepare for every possible scenario of what they could ask for. You should know that there are probably only a couple of key things they want to know. In-Meeting Checklist Keep it contextual & crisp. They will never have the context, but you do. When you share your strategy, you need to meet them at their level. Most investors usually fly around 30k feet & do not have the time or interest in coming down. They need to be able to grasp your strategy easily & not get over-involved in a barrage of details. Remember, Less is More! Use frameworks. Your strategy needs to be at a framework level. The key question to answer is, can this strategy be applied to ‘N’ number of different companies or scenarios? A framework always helps! Articulate clearly and simply. Board members generally try to ascertain if the sales leader delivered the quarter because of some lucky save or it was a quarter-end “home run” deal, or because of a predictable sales playbook that’s well integrated into the revenue management system that is put in place leading to repeatable results. Build credibility. Building credibility with the board is important, once it’s lost, it’s hard to recover. Sales leaders should be forthcoming on the key problems in the business. You should be willing to tell and not just sell! Be critical: Even if it’s a great quarter, a VP Sales must take a critical view on what could be the areas of improvement. Board members want sales leaders to demonstrate that they are continuously iterating and finding ways to improve results, even when they are hitting the quota. Be a business leader & not just a functional leader. Boards of directors value sales leaders who can take ownership over the business instead of just demonstrating mastery of the sales function. Keep the presentations simple and consistent. Use a small set of leading and lagging data indicators to demonstrate the progress being made against the intended benchmarks and consistently highlight them during quarterly board presentations. Be prepared to wear a suited armor of data, trends, insights and examples to handle the spear-shaped questions thrown at you like – How do we win in the market? Why do we lose deals? What are the win/loss reasons in each deal? What is our action plan to fix the reasons we lose? What are the biggest objections we get from potential customers? How often do we hear them? Is our sales team enabled with the battle card responses to these objections? How do we train our reps to respond? Where conversations are going off the track during the sales process? What discovery questions should we eliminate or add to qualify the prospect better? Do we identify and engage the right influencers and decision-makers in the opportunity? Have we identified the Ideal Customer Profile and do we sell to the right persona? Why are you waiting till the end of the quarter to make the changes to the sales process? Why not do them earlier? For you to be prepared with these responses, you must have a well-defined sales process and playbook. If implemented and tracked well, the sales playbook and the deviations to the same will give you enough insight into: Why sales reps go off script during the calls? How do prospects respond to the discovery questions? When prospects ghost you during the sales cycle? Which reps are single-threading on key deals? or Which deals are at risk even though the internal effort on them is already higher than the deal value itself? Now imagine, if you can operationalize and track your sales process and usage of the winning playbooks, the answers to the probing questions with data-backed responses can be like: Based on the 15 deal reviews, we found a trend in discovery calls going off-script when sales professionals get to budget-related conversations. To fix this, we have modified our calling script to help the sales team be more confident when talking about our pricing and value delivered. We have identified the top 3 objections during the sales process, and they are usually asked after the proposal is sent. We have started to address those objections during our first call itself, and we have also

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

Top 7 Data Cleansing Tools Blog Ensure your business decisions are based on accurate data. Discover what data cleansing is, its importance, and how it can transform your messy data into a valuable asset. Learn about top data cleansing software to keep your CRM clean and efficient. Dive into our comprehensive guide to make your data work for you, not against you. 10 min What is data cleansing?   Data. It’s the lifeblood of modern business, fuelling insights, driving decisions, and ultimately, shaping success in the larger picture. But raw data is often messy, riddled with inconsistencies, errors, and duplicates. This “dirty data” can lead to inaccurate analysis, flawed decision-making, and eventually wasted resources. The amount of data around us has increased and so is the need of validating its quality. As this data surge has made room for inevitable errors, companies are dabbling with the subsequent data quality checks. Did you know only 3% of data meets basic quality standards? As per Gartner, Poor data is responsible for an average of $15 million per year in losses. This is why the need for Data Cleansing is at all time high! Data cleansing, also known as data scrubbing, is the process of identifying and correcting or removing corrupt, inaccurate, or irrelevant data from your datasets. It’s essential for maintaining data integrity and ensuring your company can make accurate, informed decisions. Why Does Your Company need it? Just picture your best salesperson enthusiastically pursuing a lead only to get stuck. The phone number is wrong and the email has bounced back. Yes, it’s frustrating. This “dirty data” is battled against by reps every now and then. Inaccurate, missing or duplicated information that are in your CRM system can constitute unnecessary barriers for your reps. It’s like being lost and taking the wrong turns while traversing through a town; you may eventually arrive at your destination but after several hours of wasted efforts. Therefore, dirty data is a silent killer waiting to feast on potential opportunities in your CRM with a possible domino impact such as: Wasted Time & Resources: Data-detective mode takes over for your reps who spend hours following up cold leads, fixing mistakes or verifying details. This means that they lose significant selling time that could have been used to close deals. Missed Opportunities: Inaccurate data can be likened to a blind spot. You cannot reach existing customers via targeted advertising nor find new ones using it more effectively. What if you miss out on a big client simply because their mail account was returning an error message? Poor Decision Making: Dirty data also takes the crown when it comes to generating skewed reports and metrics. This can lead to distorted representation of things, poor business decisions and finally missed opportunities. Strained Customer Relationships: There is hardly any doubt that sending irrelevant emails or reaching out wrong individuals will yield a negative experience for customers. Your company name can be tarnished by bad data while at the same time clients can be left annoyed and made feel like digits. Doing proper data cleansing will make sense out of your chaotic data transforming it into one clean reliable source of truth. Top 7 Data Cleansing Softwares Luckily, you can tame the dirty data with several data cleansing software in the market today. A good data cleansing software can transform your messy CRM into a well-organized filing system, ready to empower your sales team. We have curated a list of top 7 data cleansing softwares for your company to choose their perfect fit. Nektar.ai Salesforce data could end up being a mess of information that can hinder the reliability of your reports. This is where Nektar.ai can help you navigate out of the clutter by putting your data hygiene on auto pilot using AI. Here’s how Nektar.ai solves the problems with data cleansing: Unmatched Sync Accuracy: Nektar.ai does not only import data at basic level, it also analyzes your records using AI algorithms for establishing links between accounts and opportunities and provides confidence scores for correct synchronization. This helps in cutting out redundant entries more importantly by enabling you to view all needed details.Time Travel for Data Retrieval: What if I told you that you can unearth the actuals of an old conversation that happened with a particular client? Nektar helps in identifying interactions like contacts, emails and meetings linked to a given domain which are then added into newly created opportunities. Its “time travel” functionality facilitates knowledge transfer among sales people and adds context to live conversations during ongoing engagement.Easy Report Creation: High-quality reporting is dependent on clean data. Nektar.ai makes it simpler to generate reports by automatically syncing contacts, emails, and meetings directly into standard Salesforce objects.Self-Healing Energy: Nektar.ai is ever learning and adjusting. It updates CRM records in response to new information by appending manual changes made by users into the system automatically.Smart Contact Automation: Nektar.ai can automatically create a contact point as well as eliminate some repetitive tasks. They are created with matching domains such that they connect with previous accounts as appropriate.Contrary to traditional data cleansing that may necessitate manual work or third party tools, Nektar.ai is an AI-powered solution that integrates well with Salesforce and does many tasks automatically. It is self-learning and ensures data always remains clean and accurate. With Nektar.ai, you can liberate your sales team from the grind of data entry and enable them to concentrate on their core function; closing deals.   Openrefine Google Refine, which is now known as OpenRefine, is already a well-known open source tool. It’s an open-source software like python script that can be freely used and modified by anyone. It also helps to maintain your data in a consistent format and sorts it according to your company requirements. Apart from this, you can import data from the web sources and apply its clustering algorithms for solving complex data cleaning jobs. Where all does OpenRefine stands out? Free and Open Source: Cheap to install and allows

9 Sales Commission Software for 2025 RevOps 10 min What is Data Enrichment? The sales landscape in 2025 is defined by hybrid workforces, AI-driven decision-making, and hyper-personalized incentive structures. As companies navigate global expansion and complex compensation models, legacy tools like spreadsheets are being replaced by intelligent platforms that automate calculations, predict outcomes, and align incentives with business goals. Modern sales commission software now integrates seamlessly with CRMs, ERPs, and collaboration tools, offering real-time visibility, compliance assurance, and actionable insights. In this guide, we explore the top 9 platforms reshaping commission management in 2025, highlighting their unique strengths, pricing, and use cases to help you choose the perfect fit for your team. Top 9 Sales Commission Software for 2025 Spiff ElevateHQ Everstage Anaplan QuotaPath Xactly Performio SalesCookie OpenComp What is Sales Commission Software? Sales Commission Software is a type of tool that helps businesses manage their sales commission calculations and payments to their sales representatives. Basically, it helps companies keep track of how well their sales are doing, figure out how much commission their salespeople should be earning based on different factors like sales targets, and even automate the whole commission payment process. Think of it as your reliable companion in the sales world. It takes the guesswork out of the equation and provides a streamlined process for businesses to accurately determine the commissions owed to their sales team. 1. Spiff Spiff dominates the market with its AI-powered “Commission Cortex,” which predicts quota attainment and recommends incentive adjustments. Trusted by high-growth SaaS and fintech companies, it’s ideal for scaling teams needing dynamic, data-driven plans. Key Features: Predictive Analytics: Forecast earnings using historical data and market trends. Dynamic Quota Management: Auto-adjust quotas based on rep performance. Integrations: Salesforce, HubSpot, Slack, Microsoft Teams, Netsuite. Rep Experience: Mobile-first dashboards with gamified progress tracking. 2. ElevateHQ ElevateHQ excels in global compliance, offering automated tax calculations and audit trails for enterprises. New in 2025: Blockchain-powered commission ledgers for tamper-proof records. Key Features: Multi-Currency Payouts: Supports 50+ currencies with real-time FX rates. Compliance Hub: GDPR, CCPA, and SOC2 compliance tools. Approval Workflows: Streamline disputes with in-app resolution channels. ERP Integrations: SAP, Oracle, Workday. 3. Everstage Everstage’s no-code platform now includes AI-driven “Incentive Co-Pilot,” which designs comp plans tailored to rep behavior. Popular among mid-market agencies and consultancies. Key Features: Drag-and-Drop Rules: Build SPIFFs, bonuses, and clawbacks without IT help. Rep Retention Analytics: Identify at-risk reps using engagement metrics. Collaboration Tools: Comment threads and @mentions for plan feedback. Integrations: ZoomInfo, LinkedIn Sales Navigator, Stripe. 4. Anaplan Anaplan’s enterprise-grade platform now offers a “Compensation Workbench” for modeling M&A scenarios and harmonizing plans post-acquisition. Key Features: Territory Optimization: Balance workloads using AI-driven territory mapping. Scenario Modeling: Simulate comp plan changes on revenue and margins. Security: FedRAMP-certified for government contracts. Integrations: Snowflake, Tableau, Salesforce CPQ. 5. QuotaPath QuotaPath remains a top choice for small to medium-sized businesses (SMBs) and remote sales teams in 2025, thanks to its intuitive design, affordability, and focus on transparency. Designed to simplify commission management, it empowers reps to track earnings in real time while giving managers tools to align incentives with business goals. Below is a comprehensive breakdown of its 2025 features, pricing, and use cases: Key Features  AI-Powered CoachBot ChatGPT-4 Integration: Reps receive real-time coaching via an in-app chatbot. For example, asking, “How can I hit 120% quota this quarter?” triggers personalized tips based on historical performance and team benchmarks. Skill Gap Analysis: The AI identifies weak spots (e.g., low conversion rates) and recommends training modules or playbooks. Gamification & Motivation Tools Live Leaderboards: Reps compete for badges like “Closer of the Month” or “SPIFF King.” Milestone Celebrations: Auto-generated shoutouts in Slack/Teams when reps hit targets. Free Tier for Startups Unlimited Plans: Manage up to 10 users at no cost, with access to core features like commission tracking, basic reporting, and QuickBooks/Xero sync. Ideal for Bootstrapped Teams: Perfect for early-stage startups testing comp structures. Self-Service Rep Portals Earnings Simulator: Reps model “what-if” scenarios (e.g., closing 5 more deals) to forecast commissions. Mobile App: iOS/Android app with push notifications for quota progress and payout approvals. Enhanced Integrations (2025) CRM: Salesforce, HubSpot, Pipedrive. Payroll: Direct sync with Gusto, Rippling, and ADP. Collaboration: Slack, Microsoft Teams, Zoom. Advanced Analytics for Managers Quota Attainment Trends: Spot seasonal patterns or team-wide bottlenecks. Payout Accuracy Reports: Flag discrepancies between forecasts and actuals. 6. Xactly Xactly solidifies its position as a powerhouse for enterprise-grade incentive compensation management (ICM) in 2025, combining generative AI, deep compliance tools, and ESG-aligned incentives. Trusted by Fortune 500 companies and global enterprises, Xactly streamlines complex comp plans while ensuring transparency and scalability. Below is a deep dive into its 2025 capabilities: Key Features –  Generative AI for Comp Design Auto-Generated Plan Docs: Describe goals in plain language (e.g., “Create a plan with accelerators after 100% quota attainment”) and let Xactly’s AI draft policies, saving 10+ hours/month. Smart Clause Library: AI suggests compliance-approved clauses for territories, clawbacks, and SPIFs. ESG-Linked Incentives Sustainability Metrics: Tie commissions to ESG goals (e.g., bonuses for reps who onboard eco-friendly suppliers or reduce carbon footprints). DEI Analytics: Track pay equity across gender, ethnicity, and role to ensure fairness. Global Compliance Hub Tax Automation: Auto-calculate VAT, GST, and income tax for 100+ countries. Regulatory Updates: Real-time alerts for changes in labor laws (e.g., EU AI Act, California SB 749). Predictive Territory Planning AI Territory Mapping: Balance workloads by analyzing deal size, rep capacity, and market potential. Scenario Modeling: Simulate mergers, territory splits, or product launches to forecast revenue impacts. Advanced Security & Governance SOC2 Type II & ISO 27001 Certified: Meet strict data security standards for healthcare, finance, and government sectors. Audit Trails: Track every comp plan change with user-level timestamps. Integrations (2025 Expansion) CRM: Salesforce, Microsoft Dynamics, HubSpot. HRIS: Workday, SAP SuccessFactors, BambooHR. Analytics: Tableau, Power BI, Snowflake. Sustainability Platforms: Salesforce Net Zero Cloud, Watershed. 7. Performio Performio emerges in 2025 as a data-first sales commission platform, tailored for enterprises needing real-time analytics, IoT integration, and seamless payroll processing. Designed for

How Nektar Automates Buying Committee Engagement RevOps 10 min In today’s complex B2B sales environment, understanding and engaging with buying groups is crucial for driving revenue. Modern B2B buying decisions are made by groups, not individuals so traditional methods, like tracking Marketing Qualified Leads (MQLs), are no longer sufficient. This shift necessitates a new approach to tracking engagement, one that leverages advanced technology to automate and streamline the process. Nektar offers a powerful solution for sales teams looking to stay ahead. By automating the tracking of Buying Group Engagement, Nektar’s features ensure that every interaction is captured and analyzed, providing deep insights into the buying process. Features such as Automated Opportunity Contact Role Creation, Conditional OCR, Intelligent Meeting Tagging, and Contact Participation (Meeting Intelligence) work together to create a comprehensive and automated engagement tracking system. In this blog, we will explore how Nektar’s advanced capabilities can transform your sales process, making it more efficient and effective by automating the tracking of Buying Group Engagement. We’ll delve into each feature, highlighting its benefits and real-world applications, to show you how Nektar can help your team achieve greater success in today’s competitive market. Understanding Buying Group Engagement Buying Group Engagement refers to the interactions and activities involving multiple stakeholders within an organization who collectively make purchasing decisions. Unlike the traditional focus on individual leads, Buying Group Engagement acknowledges the collaborative nature of B2B purchases, where various roles such as decision-makers, influencers, and end-users all contribute to the final decision. In modern B2B sales, it’s essential to track and manage these engagements effectively. Understanding who is involved in the buying process, their roles, and their level of participation helps sales teams tailor their strategies and communication. This approach not only enhances the relevance of sales efforts but also increases the likelihood of closing deals by addressing the needs and concerns of all key stakeholders. By automating the tracking of these engagements, sales teams can gain comprehensive insights into the buying dynamics, enabling them to engage more effectively and drive better outcomes. How Nektar Automates Buying Group Engagement Choosing From 5 Types of Sales Territory Mapping Nektar’s innovative approach to automating Buying Group Engagement leverages several key features that streamline and enhance the process of managing interactions with multiple stakeholders. Here’s a detailed look at how each feature contributes to a more efficient and effective sales strategy: 1. Automated Opportunity Contact Role Creation Nektar’s Automated Opportunity Contact Role Creation feature automatically identifies and assigns contact roles to opportunities within your CRM. This automation ensures that all relevant stakeholders are accurately documented and associated with each opportunity, reducing the manual effort typically required. Benefits: Time-Saving: Eliminates the need for sales reps to manually input and update contact roles, freeing up their time to focus on selling activities.Accuracy: Ensures that all contact roles are correctly and consistently assigned, reducing errors and improving data integrity.Visibility: Provides a clear view of all individuals involved in the buying process, helping sales teams better understand and manage their interactions. 2. Conditional OCR (Opportunity Contact Role) Conditional OCR allows for the creation of contact roles based on specific, predefined conditions. This feature enables sales teams to customize how and when contact roles are created, based on criteria that are most relevant to their sales processes. Benefits: Customization: Tailors the contact role creation process to fit the unique needs of different sales teams or business units.Efficiency: Automatically applies the right conditions for contact role creation, ensuring that only the most relevant contacts are included.Scalability: Supports the management of complex sales environments with numerous stakeholders and varying engagement scenarios. 3. Intelligent Meeting Tagging Nektar’s Intelligent Meeting Tagging feature automatically tags meetings with relevant information, making it easier to track and analyze interactions with buying group members. This feature leverages AI to identify key details from meetings and associates them with the appropriate contacts and opportunities. Benefits: Enhanced Insights: Provides detailed insights into the content and outcomes of meetings, helping sales teams understand engagement levels and follow up effectively.Consistency: Ensures that all relevant meeting information is captured and tagged correctly, enhancing the quality of data in the CRM.Productivity: Reduces the manual effort required to document meetings, allowing sales reps to focus more on strategic activities. 4. Contact Participation (Meeting Intelligence) The Contact Participation feature tracks and analyzes the participation of contacts in meetings. By monitoring who attends and actively participates in meetings, sales teams can gain valuable insights into the engagement levels of different stakeholders within the buying group. Benefits: Engagement Tracking: Identifies key influencers and decision-makers based on their participation and engagement in meetings. Actionable Insights: Helps sales teams tailor their follow-up strategies based on the involvement and interest levels of different contacts. Data-Driven Decisions: Provides a data-driven approach to understanding and managing buying group dynamics, leading to more informed sales strategies. How GuideCX got Visibility into $1.7Mn Inactive Pipe Every company wants to squeeze out every drop of revenue from its active pipeline. Missing out on achievable quotas and letting potential revenue slip away due to inactivity and poor engagement have become the biggest sins in Sales. But what if there was a way to bring these dormant deals back into the spotlight for the sales teams? This is the scenario we explore—a practical challenge met with a pragmatic question, setting the stage for the journey ahead. This is the story of GuideCX and how they transformed deal prioritization using process automation, powered by customized rules that considered the engagement data that Nektar captured in their CRM. This helped GuideCX gain instant visibility into $1.7M worth of inactive deals, which otherwise would have been lost forever.   Ready to revolutionize your sales process with automated Buying Group Engagement? Discover how Nektar’s advanced features can help your team capture every interaction, gain deep insights, and drive better outcomes. In this blog

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

Top 5 Trends That Will Impact Sales Operations in 2025 RevOps 10 min Sales operations has become one of the fastest growing functions over the last few years. According to LinkedIn’s State of Sales Operations 2021 Report, the number of sales operations professionals increased by 38% around the world between 2018 and 2020. What’s the reason behind this growth? Bradley Gray, Director of Business Development at Enterprise Holdings attributes two reasons for the growth in this role. There has been a significant increase in the amount of data that gets generated within organizations. The proliferation of data is creating a need for sales operations to generate contextualised insights for sales teams to succeed.   RELATED RESOURCE : SALES OPERATIONS TRENDS FOR 2025   A well run sales operations function enables businesses to operate efficiently with data-driven decisions, and also identify gaps that exist in the sales process, and help fill them up through analytical insights.  In short, a great sales operations function can help an organization unlock massive productivity gains.  To make the most out of your sales operations function, it is important to be aware of the trends that will shape in 2025 (and beyond). Let’s take a look. 1. Multithreading Will Be a Key Sales Tactic The world is in the midst of a great reshuffle for talent. The turnover among corporate director-level-and above, that constitutes the majority of B2B buyers, increased by 31% in 2021. With key people in the B2B buying committee quitting jobs so often, many deals fall apart because reps fail to develop strong relationships with more than one buyer. And with an average of 6.8 decision makers in every B2B purchase, not having strong relationships with all of the key players within the buying committee can be a big risk. When a key stakeholder leaves the organization, reps are forced to start from scratch, causing 80% of them to lose deals. Having just one primary contact for an account, or single-threading, thus increases the chances of missing out on deals. This is where adopting multithreading as a sales practice becomes extremely crucial. Multithreading is when reps form relationships with multiple stakeholders on the buying committee of an account.  This way, even if the primary stakeholder quits the organization, reps can capitalize on the relationships they have with the rest of the stakeholders within that account. Multithreading increases the chances of closing a deal by 16%. Successful sales teams in 2025 will master multithreading by gathering champions, influencers and decision-makers, and engaging with them on a regular basis. 2. An Increase in Regulations Will Impact Tech Stack Decisions There has been an increase in the number of regulations across the globe around protection of consumer information and data privacy.  Non-compliance of these regulations can be a huge cost. Organizations lose an average of $4 million in revenue due to a single non-compliance event.  To prevent such events from taking place, sales and revenue leaders must narrow down on their tech investments from a compliance-first lens. With the world increasingly moving towards a cookie-less world, highly compliant first-party data will become key in helping sales teams make data-driven decisions. First-party data is the information that is handed off with consent from a user to a company. This can be from sources like email, calendar, Zoom or other tools that buyers use.  For example, organizations can use their own first-party data to drive contextual insights that can help them make their sales operations function more efficient, while staying compliant with GDPR regulations.  Forward thinking leaders will realize this and take control of their first-party data in 2025, and use it to make powerful data-driven decisions.  Technologies like artificial intelligence can help enrich CRM with first-party buyer and seller interaction data. Nektar has built an advanced data capture solution that intelligently connects first-party data to the CRM and enriches it for sales teams. 3. AI Based Guided Selling Will Help Sellers Win More Deals B2B sales is getting increasingly complex, with buyers getting bombarded with information across channels, and sellers tackling multiple tasks and responsibilities while chasing their quota. AI based guided selling is helping sellers navigate this complex selling environment by helping them improve their sales execution through a data-driven approach.  Along with increasing productivity, AI based guided selling helps identify patterns that lead to more intelligent business decision making, ultimately helping in revenue generation. The pandemic exposed cracks in many organization’s sales processes. Knowing that sales process discipline must be improved to increase the chances of closing new deals, sales leaders are investigating new data-driven, AI-based guided selling functions for improving sales execution. Tad Travis, VP, Gartner AI-based guided selling offers prescriptive as well as predictive insights to sellers to close more deals.  From a prescriptive lens, it recommends the next best actions for sales reps and managers to undertake within the sales process. As an example, organizations can use AI to improve their playbook compliance within teams for consistent selling.  From a predictive lens, it offers insights that help identify lead indicators to make the sales process more efficient.  For example, by having insights on the activity data of sales reps, sales managers can define which deals are real and which need to be eliminated from the pipeline. With such functionalities, sales teams can decide on what to do next to move a relationship, deal or quote forward on the basis of analytics (rather than relying on instinct to make decisions). 2025 will see organizations add AI based guided selling solutions to their tech stack. 4. Training in Consultative Sales Will Take Priority Today’s B2B buyers prefer to conduct their own research before they speak with sales reps.  According to research, most buyers engage with more than 13 pieces of content before connecting with a seller.  Forrester’s research found that buyers went to all forums for information in 2021 – from webinars and online events to learn about the category and competitors, to speaking with peers and industry experts to have their questions answered. These changes in buyer preferences have raised the bar for sales. Understanding the buyer’s intent and offering them personalized solutions

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