How To Spot Trends In Customer Churn Rates

Every sales org has a pipeline: Stage 1. Stage 2. Forecast. Commit. You can recite it in your sleep. But when it comes to renewals? Crickets.... There’s no real-time view of customer risk. No weekly trendline. No forward-looking model that projects retention. Isn't that kinda bonkers? You FORECAST growth, but you DISCOVER churn...usually when it’s too late to fix. The big mistake is presuming retention is a lagging indicator, when it would be more accurate to define it as a neglected one. Think about it...most CS dashboards read like a rearview mirror: - Usage metrics. - Ticket volume. - NPS. Useful? Sure. Predictive? Nah. Because churn doesn’t start when a customer says they’re leaving. It starts months earlier when their exec sponsor stops showing up. If you can spot the risk early, you can unlock more levers: - Re-engage power. - Reset the value narrative. - Escalate to commercial. - Offer roadmap visibility. - Re-map success metrics post-reorg. But none of that works if your team can’t see it coming, which is why you need a churn forecast...just like you do for revenue. Build a churn pipeline. Treat it like sales. Some things to build into this: 1. Define churn stages. Just like deals, risk evolves: - Stage 1 (Early): No exec alignment, lagging adoption, stakeholder turnover. - Stage 2 (Mid): Value not realized, weak champion, limited engagement. - Stage 3 (Late): Renewal live, buyer pushing back, pricing/legal blockers. Assign clear criteria. Surface it in Gainsight, CZ, or Salesforce. Manage it like opportunity stages. 2. Assign prevention plays. Each stage should trigger a play: - Stage 1 = exec outreach + roadmap session. - Stage 2 = commercial review + value plan. - Stage 3 = C-level call + tailored retention offer. Codify this. Don’t let reps improvise. 3. Forecast it weekly. Revenue leaders inspect pipeline weekly. CS should do the same with churn. Ask: - How many accounts moved stages? - What’s projected retention by segment? - What % of at-risk logos have exec visibility? Also, share your churn forecast with the CFO. If the CFO sees new logo pipeline every Monday, but doesn’t see churn risk until Q4? That's no bueno. Start sending a weekly churn report with: - Total ARR at risk. - ARR by churn stage. - Stage progression. - Active recovery plays. - Forecasted retention (with confidence levels). This reduces surprises while also forcing accountability. Why? Because churn is rarely a CS failure, but it's often a product gap, pricing mismatch, or sales promise that aged poorly. When churn is forecasted, it becomes EVERYONE'S problem. Which it is. tl;dr = you don’t “discover” churn. You forecast it. You stage it. You act on it. Just like sales.

No engagement = churn risk. You think an unanswered check-in is "neutral." It's not. It's a soft downvote on your relationship. And the more of those you collect, the faster you slide into churn territory. The pattern is almost always the same: Customer disengagement isn't an event - it's a gradual fade. First, they're a bit slower to respond. Then, they start rescheduling meetings. Then, they stop showing up altogether. By the time your CRM flags them as "at risk," you've already lost them. This is especially true in today's product-led economy, where switching costs are lower than ever. Your champion might be updating their LinkedIn profile as you read this. The fix? "Silent rescue campaigns" → Target accounts before they hit 45-60 days of declining engagement metrics → Don't panic with escalations or discount offers. Try recalibration: "Let's reset: what does success look like for you NOW vs. when we started?" "I noticed your team's usage pattern has changed. Have your priorities shifted?" Give them control = acknowledge their evolving needs = improve retention. The key insight? Almost no customer wakes up one day and decides to churn. They disengage gradually. Your customer relationship is a living entity that requires constant adaptation. If you treat all accounts with the same playbook regardless of their engagement signals, you're programming churn into your model. The most brutal truth in CS: By the time they tell you they're leaving, they made that decision 3-6 months ago. What's your strategy for catching that decision window before it closes?

𝗘𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝘆𝗼𝘂'𝗿𝗲 𝘁𝗿𝗮𝗰𝗸𝗶𝗻𝗴 𝗶𝘀 𝘁𝗼𝗼 𝗹𝗮𝘁𝗲. 𝗔𝗻𝗱 𝗶𝘁'𝘀 𝘄𝗵𝘆 𝘆𝗼𝘂𝗿 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 𝗶𝘀𝗻'𝘁 𝗶𝗺𝗽𝗿𝗼𝘃𝗶𝗻𝗴. In Customer Success, most teams rely on lagging indicators:  • Logins dropped  • Customer ghosted for 30+ days  • Customer says, “𝘞𝘦’𝘳𝘦 𝘦𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘯𝘨 𝘰𝘵𝘩𝘦𝘳 𝘷𝘦𝘯𝘥𝘰𝘳𝘴…” These are all accurate signs of churn. But by the time they show up? 𝗧𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗵𝗮𝘀 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗳𝗮𝗶𝗹𝗲𝗱. 𝗬𝗼𝘂’𝗿𝗲 𝗻𝗼𝘄 𝗶𝗻 𝘀𝗮𝘃𝗲 𝗺𝗼𝗱𝗲 — Low odds. High effort. And emotionally draining for your team. Here’s the fix: 𝗦𝘁𝗮𝗿𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗼𝘄𝗻 𝙡𝙚𝙖𝙙𝙞𝙣𝙜 𝗶𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿𝘀. Few companies ever create them because the truth is: Leading indicators don’t naturally exist in your business. You have to 𝗰𝗿𝗲𝗮𝘁𝗲 𝘁𝗵𝗲𝗺. So what 𝘪𝘴 a leading indicator? It’s a signal that appears before the customer knows they’re in trouble (that you know is associated with churn risk) And while you still have the time (and relationship strength) to do something about it. 𝗛𝗲𝗿𝗲’𝘀 𝗵𝗼𝘄 𝘁𝗼 𝗯𝘂𝗶𝗹𝗱 𝘁𝗵𝗲𝗺: 𝟭. 𝗦𝘁𝘂𝗱𝘆 𝘆𝗼𝘂𝗿 𝗯𝗲𝘀𝘁 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀: Pick 2–3 accounts with clear, measurable success.    𝟮. 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝘆 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲𝘆 𝗱𝗶𝗱 𝗲𝗮𝗿𝗹𝘆: What were the key processes, decisions, or actions that led to their results?    𝟯. 𝗔𝘀𝘀𝗶𝗴𝗻 𝘁𝗶𝗺𝗶𝗻𝗴: When should every new customer do the same things? (7 days in? 30 days in?)    𝟰. 𝗕𝘂𝗶𝗹𝗱 𝗰𝗵𝗲𝗰𝗸𝗽𝗼𝗶𝗻𝘁𝘀: Use your product, CRM, and QBRs to confirm: Did it happen? Or is a risk forming? 𝗘𝘅𝗮𝗺𝗽𝗹𝗲 𝗳𝗿𝗼𝗺 𝗼𝗻𝗲 𝗼𝗳 𝗺𝘆 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 (𝗲𝗺𝗮𝗶𝗹 𝗺𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴 𝗦𝗮𝗮𝗦): Leading indicators of future churn:  • No single owner of email strategy assigned - by Day 7  • No sales email sent - by Day 7  • Marketing calendar isn’t filled out 6 weeks ahead by Day 90 If any of these are missing — no, the customer won’t churn tomorrow. But they 𝘸𝘪𝘭𝘭 eventually. And if you wait, you’ll be stuck in a low success rate “save mode”. When you act on leading indicators:  • You prevent problems while they’re still small  • You keep your team proactive, not panicked  • You shift retention from firefighting to forecasting 𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗹𝗲𝗮𝗱𝗶𝗻𝗴 𝗶𝗻𝗱𝗶𝗰𝗮𝘁𝗼𝗿𝘀 𝗼𝗳 𝘆𝗼𝘂𝗿 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗿𝗶𝘀𝗸? #customersuccess

Why does churn so often surprise us? Because we’re measuring health wrong - “Healthy” customers suddenly churning We’re not seeing the whole picture. - Not getting ahead of it in time We look at: - Number of support tickets - Product usage metrics Without looking at: - HOW they use the product - Executive engagement - Champion turnover - Payment history - Etc. Waiting until 30 days before renewal - To find out they’re churning - When it’s too late to save As an AE at Salesforce, I got to see how this machine can work when running on all 8 cylinders. I could see everything outlined above and then some, throughout the year, to not only get ahead of the renewal but also to expand the account. I could see how they were using or not using Salesforce and infer what might be happening. I could get a holistic view many B2B SaaS companies don’t have. I could form a point of view. More importantly, I could score my accounts and plan accordingly. Creating a Customer Health Score is one of the best ways to improve renewals, and a prerequisite to having a well oiled renewal process. But, the best health scores aren’t built in a silo. They’re reverse-engineered from churn. - What patterns showed in usage, behavior, payment, or sentiment? - What did churned accounts look like 90 days before they left? - What data did you already have — but didn’t act on? Start there and then iterate. - Just like a Lead Score - It's not set it and forget it - It requires lots of fine tuning A good CHS doesn’t just tell you who’s healthy today. - It tells you who’s about to churn tomorrow. In tomorrow’s newsletter we’ll breaks this down in more detail — including how to weigh metrics, validate the score, and make it actionable across GTM. Get the high-res image below and a thorough breakdown in tomorrow’s 📰 𝙍𝙚𝙫𝙊𝙥𝙨 𝙒𝙚𝙚𝙠𝙡𝙮 📰 Subscribe to get it here: https://bit.ly/49RCm0h ✌️ Which signals have been most predictive of churn for you? What would you add to this? 🤔

Churn risks do not show up in bold letters. They evolve quietly, hidden in changes to product usage, new faces at your customer’s table, or a little too much silence during a renewal cycle. Thanks to Steve Fiore for sparking a great question on whether we use automated or manual ways to spot these risks at LinkedIn. The answer: Both, tightly linked together. We monitor data signals including usage insights, AI-powered Gong call analysis, and account and stakeholder risk alerts through LinkedIn Sales Navigator. At the same time, our Customer Success Managers dig deep with annual Renewal Risk Assessments, long before renewal is even a discussion. They sit with the data, then ask: - Who are our champions, and are those relationships still strong? - Has anyone in the stakeholder group changed roles or left? - Is our product sufficiently integrated into their tech stack, workflows, and enablement? - Do their priorities align with the value we provide? - Can our stakeholders articulate and prove that value? They act on what they learn, setting action plans, holding program owners accountable to implementing the action plans, re-engaging drifting contacts, tailoring value conversations to new decision-makers. Tools help us spot signals; people shape the response. Being early and intentional, not just reactive, sets up a higher likelihood of renewal, builds trust, and often surfaces new growth opportunities. Retention happens all year through smart monitoring, curiosity in every interaction, and clear action when needed. For every leader building a churn prevention playbook:  1. Start with your data  2. Empower your people  3. Make every insight actionable