Using Analytics to Drive Customer-Centric Sales Decisions

Let’s be honest, the “Listen, Analyze, Act” model just isn’t enough anymore. CX teams need to move faster, focus sharper, and deliver results everyone in the business can see. That means making outcomes core to your approach, and making sure you energize the entire organization around what matters. How do you deliver on “Outcomes > Action” as the new mantra over “Listen—> Analyze —> Act?” First, unify your data. Easier said than done, but you have to pull together every signal from surveys, tickets, chats, ops data, and social feedback. Use AI to create a real-time, connected customer view, so you’re not just looking at snapshots, but seeing the bigger story as it unfolds. Second, interpret what you find. AI can surface intent, risk, and opportunity in ways traditional methods miss. Zero in on what actually drives the experience and impacts the business. This is where you separate noise from the signals that count. You should also be thinking about how this impacts revenue, cost-to-serve, and your company’s culture (not just customers). Third, orchestrate targeted action. AI can help you prioritize and automate interventions, whether that’s routing cases, suggesting next-best actions (or product), or personalizing experiences at scale. Every action should have a clear line of sight to the business outcome you’re after. Measurable. Fourth, focus on the outcome. Set non-negotiable, measurable goals: revenue, retention, cost to serve, or employee engagement. Every initiative, every improvement, should be traced back to these metrics. Celebrate when you move the needle and be honest about what didn’t work. Finally, energize the business. Change only sticks when you bring others with you. CX leaders have to rally stakeholders, share early wins, and make progress visible. This is about building belief and momentum so everyone feels ownership of the results. How does this look in real life? Imagine that renewal rates among small business customers are falling. You unify data across channels and use AI to interpret that a recent product change is causing confusion. You orchestrate a fix by launching in-app tutorials or targeted outreach, and equip the frontlines with talking points. You measure the outcome by tracking renewal rates, then energize the business by celebrating the improvement, sharing the story, and holding teams accountable for continued results. Listening, Analyzing, and Acting are important. But the framework is what, 15 years old or more at this point? It needs to evolve given businesses, technology, and customers have evolved. Don’t keep following the same old script. Challenge the status quo. Action with purpose, a business energized around outcomes, and AI as the catalyst for lasting impact is the start. #customerexperience #leadership #ai #changemanagement #outcomesoveraction

Subscription services need strong analytics to build smarter & strategically strong plans. 🚀 Subscription models aren’t just a trend anymore—they’re shaping the future of eCommerce. 🛍 But are you leveraging data & analytics sufficiently, to iteratively build your strategy, & have your customers coming back? Here’s why you should make data analytics an integral part of your business approach: 🎯 Customer Retention Isn’t a Guessing Game Many eCommerce businesses still rely on gut feeling & high level market trends when deciding what keeps their subscribers happy. What if you could make smarter, data-driven decisions instead? Here’s how: 1️⃣ Understand User Behavior at a Granular Level Accurate analytics helps you spot patterns in how your subscribers behave. 👉 For example, a fitness app found that users who completed daily workouts stayed subscribed longer. With this insight, the app focused on features that encourage consistent engagement, boosting retention. 2️⃣ Personalize the Experience Analytics isn’t just about numbers—it’s about the people behind them. By segmenting your customers based on their behavior & psychographics, you can create personalized experiences that drive loyalty. 👉 Example: Netflix tailors its show and movie recommendations at a segment of one level, making subscribers feel seen and valued, while also making their life easier! 3️⃣ Track Key Metrics Keep an eye on crucial metrics such as Churn Rate, Average Order Value (AOV), & Customer Lifetime Value (CLTV). These metrics tell you what’s working, & where you need to pivot. 👉 For instance, a music app discovered that users who created personalized playlists were less likely to churn. Now they focus on promoting playlist creation to keep users engaged. 4️⃣ Leverage Predictive Analytics Want to predict churn before it happens? Predictive analytics can highlight warning signs of disengagement so you can take action before your subscribers leave. 👉 Takeaway: With predictive analytics you can send personalized reminders, special incentives, or tips to at-risk users, keeping them engaged. 5️⃣ Test, Learn, Optimize Don’t settle for your first plan. A/B testing helps you experiment with different subscription models, pricing, & features to arrive at the best. 👉 Example: A video streaming service can test different pricing structures & tiers, & find the best pricing plans that maximize sign-ups, market share, & retention. Bottom line: Subscription analytics give you the insights you need to understand, retain, & grow your subscriber base. Embracing smart data, & analyzing it while keeping the people behind it in your mind can create more personalized, engaging, & profitable subscription model. At Appstle Inc. there are 30,000+ eCommerce businesses that hands-on use our granular analytics to make impactful data driven customer retention strategies. The analytics are an integral part of Appstle Subscriptions. Because there is no better way to profitably scale!

Revolutionizing Sales & Partnerships with AI: Introducing the AI Sales and Partnership Leadership Series I'm incredibly excited about the potential of AI, particularly tools like Google's NotebookLM, to transform how we approach sales and partnerships. Imagine instantly summarizing key insights from client calls, proposals, and market research, empowering our teams to focus on what truly matters: building strategic relationships and closing deals. This isn't just about streamlining workflows; it's about uncovering hidden opportunities and driving significant customer success and revenue growth. To explore this potential, I'm launching the AI Sales and Partnerships Leadership Series, a platform for sharing and learning best practices from our community. Let's dive into a powerful use case: Use Case 1: Unlocking Strategic Client Insights with AI-Powered SWOT Analysis Imagine having a comprehensive understanding of your client's business, including their competitive landscape, strategic opportunities, and potential gaps. And imagine also being able to get the insights you need to assess your team's ability objectively and coach them to drive strategic partnership impact over time. With NotebookLM, this is now achievable. Here's how: 1) Client-Centric Notebooks: Create a dedicated NotebookLM page for each key client in your portfolio. 2) Capture Every Interaction: Ensure all client conversations are transcribed (consider using Gemini for this!). 3) Centralize Key Documents: Upload all relevant source materials: meeting transcripts, joint business plans, external publications, market reports—everything that paints a complete picture of the client's business. 4) Time-Stamped Insights: Crucially, ensure all documents are date-stamped to track relationship evolution and emerging trends over time. 5) Strategic Prompt Engineering: Experiment with targeted prompts to extract valuable insights. Here are some examples: "Provide a SWOT analysis for this customer/partner." "How are they competitively positioned in their industry?" "Evaluate our team's ability to consultatively sell growth opportunities for this client. What coaching opportunities exist for our managers?" "Where can the Google team double down on what's working with this client?" "What are the client's key pain points that we haven't addressed yet?" "Evaluate our relationship quality with this client (1-10 scale). If less than 10, what steps can we take to improve it?" "How does our team stack up against the competition? What are our strengths and weaknesses?" 6) Maintain and Iterate: Keep your NotebookLM pages updated. The more you use them to uncover insights, the more valuable they become. Share your learnings too; Let's unlock the future of sales together! #AISalesLeadership #SalesEffectiveness #SalesLeadership #AI #SalesTools #Partnerships #NotebookLM #GoogleAI #Innovation

Here’s EXACTLY how our best customers (fast-growing b2b companies like Iterable, Ashby, Thoropass) are thinking about account selection going into 2025: First, here’s what they’re NOT doing. - NOT spraying & praying to their TAM. Growth at all costs died in 2022. - NOT treating this as a one-time project. ICP is an ongoing program. - NOT guessing on ICP. They’re using data & statistics to validate an ICP model. Here’s how (5 simple steps): 1.) Describe your ideal accounts (with words, not filters) This template might help: ”We are best for {{specific types of}} companies, in {{specific markets or situations}}, with {{specific problems}}.” Starting with a vivid and detailed description of who you serve best helps you turn that detail into an ICP Model that actually works. 2.) Use “better if” statements to get deeper. This will help you get more concrete and translate into signals. Here are some examples for my business: - Better if growing AE and/or SDR teams. - Better if using Salesforce as source of truth. - Better if selling to multiple verticals. - Better if a territory planning project is coming up. - Better if RevOps team in-house. 3.) Translate into an ICP scoring model. Once they have a vivid description of their ICP, they translate that description into a model. The model is based on both their market insights AND customer analysis. The model is backtested against historical pipeline and customers. You can use Keyplay for this part or build something in house. 4.) Pick accounts and segments. Use their scoring model as the key input, they build account lists, territories, and prioritize plays to the best-fit accounts and segments. They use back-testing data to find segments with the best long-term economics (CLV) and/or the areas with high short-term potential (win rates, ACV, velocity). 5.) Practice “surround sound” marketing. Now they know where to focus. So instead of “spray and pray” they can double or triple down on the top tier accounts. They can create a surround sound effect for the best accounts, rather than a faint murmur for their entire TAM. Account selection isn’t the most glamorous work. But selecting the right accounts is some of the highest leverage work a gtm team can do. It’s upstream of everything. Working on this right now and want some help? Feel free to dm me. #b2b #marketing #sales