Sales Analytics for Understanding Customer Needs

Wondering how to design a Scaled Customer Success motion? Leverage your data and reverse engineer what your customers need. Take the customers that you already know are successful, and look at their data to identify what a successful customer journey looks like. We keep the customer at the center, and use the data we have available to better understand our customers en masse. As you look at the data, you might find information that surprises you. Doing a regression analysis across customer data will tell you surprising things around signals that indicate growth potential as well as risk. You might find that the feature you thought was most "sticky" isn't actually used all that much by your growing and successful customers. You might find that the data that correlates to successful business outcomes for customers isn't at all what you would have guessed. After you've looked at this data and put on your detective hat and asked it good questions, you're ready to begin mapping out how to achieve those results at Scale. Start with what channel you're going to use. You can decide what is best delivered via digital channels vs human channels so that customers can grow and better accomplish their goals. You can identify where your CSMs can best spend their time in strategic human intervention as risk mitigation or growth acceleration as they help customers achieve their desired outcomes. You keep customers at the center by listening to what they're telling you: both in what they say and what they DO. That's what data can help you understand: what it is that your customers are actually doing. And then as you build out this Scaled motion, constantly go back to the data and get a better understanding if what you're doing is accomplishing the goals you're looking for. Don't make assumptions, be willing to look at the data and see the results. Because the only thing worse than not having data you need, is ignoring the data you have because you're too comfortable with what you're already doing. #CustomerSuccess #SaaS #Data #DigitalCS

Your website tells you who’s visiting. But do you know what they care about? You’re a multi-product company. Accounts visit your website daily, but all you see is a stream of clicks, page views, and scattered data points. You know who is engaging, but you have no clear insight into what they’re actually interested in. Your sales team is flying blind. Your marketing team is running generic campaigns. And potential buyers aren’t getting the right message at the right time. Most teams try to solve this with lead scoring—but scoring alone doesn’t tell you why an account is engaged or what specific product they care about. That’s where traditional solutions fail. With Interest Groups, Factors.ai consolidates scattered engagement signals into one clear, actionable insight based on what an account is actually interested in. Instead of pouring through raw data, you now get: 1. A consolidated view of an account’s engagement with specific products or features 2.⁠ ⁠Signals from blogs, videos, product pages, search keywords, and G2 intent data (all grouped automatically) 3.⁠ ⁠A single Interest Score showing how engaged an account is with a particular solution What this means for you: 1.⁠ ⁠Sales Teams Walk into every demo knowing exactly which product or feature a prospect cares about. No more generic pitches. Just precise, interest-driven conversations. 2.⁠ ⁠Marketing Teams Run hyper-personalized LinkedIn ads, nurture emails, and campaigns based on real engagement data. No more one-size-fits-all messaging. 3.⁠ ⁠Customer Success Teams Spot existing customers showing interest in products they don’t own yet (turning insights into upsell and cross-sell opportunities). For companies with multiple products or complex feature sets, this is a game-changer. 💡 Your accounts aren’t just "interested". They have specific needs. Interest Groups finally let you see what they are. Excited to see how this changes the way GTM teams operate. How are you currently identifying account interest? Would love to hear! #B2BMarketing #SalesIntelligence #AccountBasedMarketing #RevenueGrowth #GoToMarket

Most businesses today are running on Simple Data Analytics (SDA). -Summing -Averaging -Multiplying -Basic reports It’s enough to track what’s happening. But is it enough to stay competitive? Maybe not. Because while SDA gives you a snapshot of the past, it doesn’t prepare you for the future. Enter Intelligent Data Analytics (IDA). IDA goes beyond basic number crunching. It transforms, standardizes, and enriches data with AI before analysis. That means: ✔ Extracting meaning from unstructured sources (like social media, emails, or customer reviews). ✔ Identifying hidden patterns using natural language processing and machine learning. ✔ Automating complex data processing to surface real insights. Why does this matter? Let’s say your company sees a 10% drop in customer retention. SDA tells you the retention rate is down. But why? With IDA, you can analyze customer call center transcripts, recent product reviews, customer satisfaction surveys, and buying behavior to tell you: → Are customers leaving due to price sensitivity? → Is a competitor offering better service? → Are product reviews highlighting recurring issues? SDA can tell you what happened, but IDA can tell you what actually transpired and provide insights into what to do next. Businesses that stop at simple data analytics are leaving valuable insights on the table. In our AI-driven world, data isn’t just about reporting—it’s the key to smarter, more strategic decision-making. Are you still relying on basic reports, or have you made the shift to intelligent data analytics?