Customer Churn Insights

Seniority of data people doesn't (shouldn't?) depend on tools, years of experience or degrees But rather on the sophistication of their answers in simple business questions ❓ Sales dropped 10% this quarter. Why❓ 🟥 𝐉𝐮𝐧𝐢𝐨𝐫 "I looked at sales data. Biggest drop was in Athens by 15% and Product B by 20%. Here's a chart showing monthly sales decline. It seems that sales dropped mainly because of fewer orders." 📜 Why it's junior: - Just numbers - Limited data exploration - Key takeout could be deducted by any random non-data person who just has common sense 🟨 𝐌𝐢𝐝 "Sales dropped 10%, mainly driven from Athens which also shows a 12% increase in customer churn. I also found that competitor promotions increased during the same period using market data. A correlation analysis suggests competitor discounts have an impact on user retention. So competition and loss of key customers contributed significantly in the drop" 📜 Why it's mid: -Diagnostic analysis -Use of external data -Key takeout isn't sophisticated enough, but remains solid and supported by reasonable assumptions / stats 🟩 𝐒𝐞𝐧𝐢𝐨𝐫 "The -10% sales decline is primarily driven by a +12% customer churn among our top-tier segment in Athens. Cohort analysis shows that customers acquired 12-18 months ago are churning at a higher rate due to recent competitor pricing strategies. Predictive models indicate that unless retention improves, we may lose an additional 5% next quarter. I recommend immediate targeted retention campaigns for the top decile customers in that region and a reassessment of our competitive pricing strategy. Additionally, I’ve identified early churn indicators we can track going forward." 📜 Why it's senior: -Good summary at the top (Minto pyramid anyone?) -Focus on business impact -Predictive and causal thought process -Proactive and actionable recommendations -Strategic thinking beyond the immediate question 💡 Long story short, if the key findings and suggested actions of an analysis are based on rough estimates and common sense rather than precise numbers, provable assumptions and cross-departmental inputs, "data-driven" approach is an overstatement. Just ask a random employee next time to save time #data #analytics #seniority #sales_are_down_because_orders_dropped #we_should_limit_costs

Everyone wants to correlate NPS with revenue. But here’s the uncomfortable truth: You won’t always find it. We were discussing this with a CX leader recently. They had already tried correlating NPS → revenue. Nothing meaningful came out. So we went one level deeper: -Did you break NPS into promoters, passives, and detractors? -Did you check which segment is churning more? -Did you analyze open-ended feedback themes vs churn? They hadn’t. Then we explored something interesting: Customers who give lower NPS tend to raise multiple tickets for the same issue. Now that’s a signal. Not revenue. Not directly. But a leading indicator of friction → frustration → churn. That’s when it clicked: You don’t always find insights by forcing a straight line to revenue. Sometimes the real value comes from connecting: Feedback → Behavior → Outcomes NPS alone won’t tell you much. CSAT alone won’t either. But combine: Scores Support behavior Ticket reasons Open-text feedback Churn Now you’re getting somewhere. The goal isn’t correlation. The goal is to find what actually moves the needle. #customerfeedback #nps #churn #correlation

Most retention thinking focuses on the wrong moment. The assumption is that customers who churn do so early, before they've really committed. An analysis of 3.7 million product reviews across nearly 30 years points somewhere different. Switching risk peaks in the middle of the customer journey, after someone has built some familiarity with a category but before they've reached genuine expertise. Confidence follows an inverted U: high at the beginning when people don't know what they don't know, drops as they try more and start questioning their choices, then recovers once they've developed real category knowledge. The window in the middle is where brands lose people: → Customers who had reviewed between 2 and 10 makeup products were 4.5% more likely to switch brands. → 54% of those who switched never came back. The pattern held across categories. For brands selling into categories where customers are still building knowledge, the customer who has bought three or four times and starts exploring alternatives isn't disloyal. They're at the phase where confidence is lowest and curiosity is highest. The effect weakened when customers were prompted to reflect on their experience rather than just accumulate it. Helping customers make sense of what they've already tried turns out to be more useful at this stage than encouraging them to try more. So are you helping your customers decide; or just giving them more to try?

Customer churn hit 45% last quarter. The VP blamed onboarding. I blamed who they were selling to VP: "Our onboarding process is clearly broken. Customers aren't seeing value fast enough" Me: "Show me who's churning" VP: "What do you mean? They're all different companies" Me: "Humor me. Pull up the data" 10 minutes of awkward silence while he searched What we found → 70% of churned customers had under 50 employees → 50% were in industries outside their core expertise → 90% had budgets below their sweet spot → 40% were sold features they didn't actually need The real problem wasn't onboarding. It was that sales was closing anyone with a pulse I ran the numbers on their best customers 200+ employees, financial services or healthcare, $50K+ annual budgets. We made 3 changes - Redefined ideal customer profile with hard criteria - Implemented mandatory qualification gates - Changed commission structure to reward retention, not just acquisition The VP pushed back: "We'll miss our numbers this quarter" I told him: "You're already missing them. You're just doing it slower" Six months later customer churn dropped, average deal size increased and sales cycle shortened Your retention problem usually starts in sales, not success You can't onboard your way out of selling to the wrong customers Every "yes" from a bad-fit prospect is a future churn waiting to happen Better to close 50% fewer deals with the right customers than 100% more deals with the wrong ones. P.S. Got a question? Send me a DM

Churn doesn’t scream. It silently kills growth. It’s not just a Customer Success problem. It’s a product problem. A business problem. A growth problem. So if you want compounding growth—start here. Here are 10 proven tactics to reduce churn (that we apply across every product-led business): 1. Drive Paid Feature Usage If users aren’t using what they paid for… They won’t stay. → Highlight key features early. → Guide them to value fast. 2. Don’t Wait for Churn—Prevent It Churn begins at onboarding. → Nail setup. → Get users to their “aha” moment quickly. → Build usage habits, not just logins. 3. Make Reactivation 1-Click Across every channel—app, web, email. → This small change can recover 10% of your cancels before the term ends. 4. Tackle Payment Failures Proactively Dunning flows = money left on the table. → Use email and in-product nudges to update cards. → Catch revenue before it’s gone. 5. Show What They’re Losing When users cancel… → Remind them what they’ll miss. → Visual reminders of usage, saved time, or value. (Canva does this brilliantly.) 6. Score and Save High-Risk Users Use churn prediction to: → Flag risky accounts early. → Offer discounts or extended access. → This can save up to 5% of your churn. 7. Add a “Pause” Option Not every cancellation is final. → Offer a pause instead of goodbye—especially for seasonal or budget-sensitive users. 8. Make Downgrades Easy If they can’t pay full price… → Let them downgrade. → Don’t push them to cancel when a smaller plan fits. 9. Push Monthly Users to Annual After 6–9 months: → Offer an upgrade incentive. → Target 20% conversion to annual plans by year-end. 10. Add a Human Touch for High-Value Accounts AI can’t replace empathy. → For B2B or high-ARPU users, real check-ins from your team matter. → Personal support builds loyalty. 🚨 Final Thought Churn is a growth leak. Fix it early—and everything scales better. Ignore it—and all your acquisition work goes to waste. → DM me “Retention” and I’ll send you the full churn-reduction playbook. #Churn #Retention #CustomerSuccess #PLG #B2BGrowth #SaaSStrategy #UserEngagement #GrowthOps #ProductLedGrowth #RevenueGrowth

𝐅𝐨𝐫 𝐲𝐞𝐚𝐫𝐬, 𝐦𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐫𝐚𝐧 𝐨𝐧 𝐡𝐢𝐧𝐝𝐬𝐢𝐠𝐡𝐭. Dashboards told us what already happened—open rates, MQLs, churn numbers. By the time we saw the problem, it was too late. 𝐋𝐞𝐚𝐝𝐬? 𝐃𝐞𝐚𝐝. 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫𝐬? 𝐆𝐨𝐧𝐞. 𝐁𝐮𝐝𝐠𝐞𝐭? 𝐁𝐮𝐫𝐧𝐞𝐝. But AI and predictive analytics are flipping the game. 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐢𝐬𝐧’𝐭 𝐫𝐞𝐚𝐜𝐭𝐢𝐯𝐞 𝐚𝐧𝐲𝐦𝐨𝐫𝐞. 𝐈𝐭’𝐬 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞. 🔹 𝐋𝐞𝐚𝐝 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭𝐢𝐧𝐠 Traditional lead scoring is broken. A whitepaper download? That’s not intent—it’s noise. When we actually analyzed behavioral data using platforms like HubSpot, we found that multiple pricing page visits and engagement with onboarding content predicted conversions 3x better than generic lead scores. 𝐖𝐢𝐭𝐡 𝐦𝐮𝐥𝐭𝐢-𝐭𝐨𝐮𝐜𝐡 𝐚𝐭𝐭𝐫𝐢𝐛𝐮𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥𝐬 and 𝐛𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐚𝐥 𝐜𝐨𝐡𝐨𝐫𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬 ✔ Leads with 𝐫𝐞𝐩𝐞𝐚𝐭 𝐯𝐢𝐬𝐢𝐭𝐬 𝐭𝐨 𝐭𝐡𝐞 𝐩𝐫𝐢𝐜𝐢𝐧𝐠 𝐩𝐚𝐠𝐞 had a 𝟑𝐱 𝐡𝐢𝐠𝐡𝐞𝐫 𝐥𝐢𝐤𝐞𝐥𝐢𝐡𝐨𝐨𝐝 𝐨𝐟 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧 ✔ Prospects engaging with 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐯𝐞 𝐝𝐞𝐦𝐨𝐬 moved through the funnel 𝟒𝟐% 𝐟𝐚𝐬𝐭𝐞𝐫 ✔ Combining 𝐢𝐧𝐭𝐞𝐧𝐭 𝐬𝐢𝐠𝐧𝐚𝐥𝐬 𝐰𝐢𝐭𝐡 𝐟𝐢𝐫𝐦𝐨𝐠𝐫𝐚𝐩𝐡𝐢𝐜𝐬 increased lead quality 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐢𝐧𝐟𝐥𝐚𝐭𝐢𝐧𝐠 𝐚𝐜𝐪𝐮𝐢𝐬𝐢𝐭𝐢𝐨𝐧 𝐜𝐨𝐬𝐭𝐬 We stopped chasing the wrong leads. And our pipeline? Tighter than ever. 🔹 𝐂𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐑𝐞𝐭𝐞𝐧𝐭𝐢𝐨𝐧 A churn report tells you what you lost. But by then, it’s a post-mortem. Advanced platforms flag disengagement before it happens. A simple tweak—triggering check-ins for inactive accounts—cut churn by 15% in six months. A simple intervention—𝐭𝐫𝐢𝐠𝐠𝐞𝐫𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐫𝐞-𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 when customers showed 𝟑+ 𝐝𝐢𝐬𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐭𝐫𝐢𝐠𝐠𝐞𝐫𝐬—led to a 𝟏𝟓% 𝐫𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐜𝐡𝐮𝐫𝐧 𝐢𝐧 𝐬𝐢𝐱 𝐦𝐨𝐧𝐭𝐡𝐬. 🔹 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐅𝐢𝐭 Guessing what users want is a waste of time. Predictive analytics showed us which features had a 𝟒𝟎% 𝐥𝐢𝐤𝐞𝐥𝐢𝐡𝐨𝐨𝐝 𝐨𝐟 𝐚𝐝𝐨𝐩𝐭𝐢𝐨𝐧 before launch. The result? No wasted dev cycles, no misfires—just 𝐝𝐚𝐭𝐚-𝐛𝐚𝐜𝐤𝐞𝐝 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬. If you’re still relying on past data to drive strategy, 𝐲𝐨𝐮’𝐫𝐞 𝐩𝐥𝐚𝐲𝐢𝐧𝐠 𝐲𝐞𝐬𝐭𝐞𝐫𝐝𝐚𝐲’𝐬 𝐠𝐚𝐦𝐞. 𝐌𝐚𝐫𝐤𝐞𝐭𝐢𝐧𝐠 𝐢𝐬𝐧’𝐭 𝐚𝐛𝐨𝐮𝐭 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐛𝐚𝐜𝐤. 𝐈𝐭’𝐬 𝐚𝐛𝐨𝐮𝐭 𝐤𝐧𝐨𝐰𝐢𝐧𝐠 𝐰𝐡𝐚𝐭’𝐬 𝐧𝐞𝐱𝐭. #PredictiveAnalytics #MarketingStrategy #DataDriven #Growth

By the time churn shows up in your dashboard, it’s already too late. After 17 years of working with B2B SaaS teams — from startups to $50M+ ARR — I’ve learned this: Churn is rarely about price. It’s about disconnection. Here are 3 high-leverage churn signals most teams miss: 1. Your Product Champion Goes Quiet Most teams track aggregate usage. But if your internal advocate stops logging in, engaging in QBRs, or pushing adoption — you’re already in the danger zone. They’re the renewal driver. When they disappear, the contract is next. 2. Time-to-Value Slips Past 14 Days If users don’t hit their “aha moment” in the first two weeks, you’ve likely lost them mentally. High retention SaaS teams obsess over early milestone conversion — not just signups. 3. Health Scores That Mean Nothing Generic green/yellow/red dashboards don’t save accounts. You need a predictive system that combines usage patterns, account behavior, and qualitative CSM input. If you can’t act on it within 24 hours, it’s not a health score. It’s theater. Pro tip: Build a health score around the DEAR framework: • Deployment: Are they technically set up? • Engagement: Are power users actually active? • Adoption: Are high-ROI features in use? • ROI: Are you documenting outcomes with decision-makers? If you’re missing those, you’re solving symptoms — not root causes. I’ve packaged everything into a playbook that includes: • The exact health scoring structure I use with SaaS clients • Product champion tracking logic • Intervention playbooks by risk tier Comment “Churn Map” and I’ll send it your way.

𝗧𝗼𝘅𝗶𝗰 𝗖𝘂𝗹𝘁𝘂𝗿𝗲 = 𝗘𝗺𝗽𝗹𝗼𝘆𝗲𝗲 𝗖𝗵𝘂𝗿𝗻 = 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗖𝗵𝘂𝗿𝗻 A fintech bled 40% of its staff in 6 months due to a “always-on” culture. Within a year, 28% of customers left too. Why? Burned-out employees can’t delight customers. 𝗧𝗵𝗲 𝗖𝘂𝗹𝘁𝘂𝗿𝗲-𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗗𝗲𝗮𝘁𝗵 𝗦𝗽𝗶𝗿𝗮𝗹 – 78% of customers ditch brands after poor service (Zendesk). – Toxic cultures cost U.S. firms $223B/year in turnover (SHRM). – Glassdoor reviews mentioning “culture” impact 35% of customer decisions (BrightLocal). 𝗕𝗿𝗲𝗮𝗸 𝘁𝗵𝗲 𝗖𝘆𝗰𝗹𝗲 → 𝗥𝘂𝗻 𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝗮𝘂𝗱𝗶𝘁𝘀 • Track metrics: Meeting toxicity scores, after-hours email rates. • Zappos pays quitters $4K to leave if they’re culture misfits. → 𝗣𝗿𝗼𝘁𝗲𝗰𝘁 𝘁𝗵𝗲 𝗽𝗿𝗼𝘁𝗲𝗰𝘁𝗼𝗿𝘀 • Empower employees to say “No” to unreasonable demands. • Adobe’s “Check-In” system replaced rankings with growth talks. → 𝗟𝗶𝗻𝗸 𝗰𝘂𝗹𝘁𝘂𝗿𝗲 𝘁𝗼 𝗰𝗼𝗺𝗽 • Tie 20% of leader bonuses to team well-being scores. • Publix shares profits with frontline staff, fueling 89% retention. 𝗖𝘂𝗹𝘁𝘂𝗿𝗲 𝗥𝗢𝗜 𝗨𝗻𝗹𝗼𝗰𝗸𝗲𝗱 Happy employees boost customer satisfaction by 33% (MIT). Companies with strong cultures recover from crises 2x faster (PwC). 94% of investors now vet culture before funding (KPMG). Customers don’t leave companies. They leave broken cultures. #CompanyCulture #Leadership #CustomerExperience

Reality check: It’s not just about customer outcomes. Last quarter, I shared a story about a customer I had worked with for +3 years who churned. (Link to that post below) One of the questions I got from sharing this story was: “Was the customer receiving value, aka... were they meeting their desired outcomes?" It’s the go-to reaction, right? We’ve been conditioned to believe that churn is tied to whether a customer achieved what they set out to do. And I do not disagree. But here’s the thing—that question is too narrow. It misses the broader picture. Churn is complex, multi-faceted, and often not just about whether customers hit their goals. Churn isn’t just about outcomes. It’s about the entire customer journey. Here’s why focusing solely on outcomes is misleading: ✨ Product-market fit You can help a customer achieve goals, but if the product was never the right fit, churn is inevitable. Misaligned expectations start in the sales process—not at renewal. ✨ Onboarding experience A rocky onboarding sets the tone for future dissatisfaction. Churn often starts here, even if it doesn’t show up until much later. ✨ Product experience Meeting outcomes doesn’t mean customers enjoy using your product. If it’s clunky, unreliable, or doesn’t evolve with their needs, frustration grows. ✨ Support quality A customer might hit targets but churn because every issue feels like an uphill battle. Exceptional support can retain customers—even when the product has gaps. And let's be honest, there will always be gaps. But a bad experience can ruin everything. ✨ Strategic alignment Leadership changes, shifting priorities, or lack of executive engagement can drive churn, even if outcomes are met. Relationships at every level matter, even more so at the executive level. ✨ External factors Budget cuts, mergers, economic shifts—sometimes churn is beyond your control. But how you manage those situations impacts future opportunities. TL;DR When churn happens, don’t just ask: “Were they meeting their outcomes?” Ask: “What did their journey look like?” Dive into the details. Because that’s where you will find your answers. Retention is NOT just the CSM's team metric, but an entire organization’s metric. What's one thing your organization has done to make retention a company-wide focus? I'd love to hear your thoughts.

When customers say they’ll churn, most teams panic. And that panic shows up as activity. “Here’s a report.” “Can we meet?” “Want to talk to an executive?” It feels busy, but it’s not a plan. I see this all the time: a customer says they’re going to churn, and instead of building a formal save plan, CSMs throw everything at the wall, hoping something sticks. During a coaching session this week, I helped a team reframe that behavior into something structured and accountable, and a program both sides agree to. Here’s the exact approach we walked through, step by step: 1) Get a live commitment first, not later Book a call and open with a calm reset: “I want to align on a short plan to prove value in the next 30 days. If we do the work and you see the outcomes we agree on, will you continue with us instead of churning?” 𝙋𝙚𝙤𝙥𝙡𝙚 𝙖𝙧𝙚 𝙛𝙖𝙧 𝙡𝙚𝙨𝙨 𝙡𝙞𝙠𝙚𝙡𝙮 𝙩𝙤 𝙨𝙖𝙮 𝙣𝙤 𝙬𝙝𝙚𝙣 𝙖𝙨𝙠𝙚𝙙 𝙡𝙞𝙫𝙚. 𝙂𝙚𝙩 𝙩𝙝𝙚 𝙫𝙚𝙧𝙗𝙖𝙡 𝙮𝙚𝙨 𝙤𝙣 𝙩𝙝𝙚 𝙘𝙖𝙡𝙡, 𝙣𝙤𝙩 𝙫𝙞𝙖 𝙚𝙢𝙖𝙞𝙡. 2) Name the problem in their words Summarize what they said is blocking renewal, then play it back. “You mentioned [X) as the reason- Did I miss anything?” 3) Propose a 30-day proof plan Replace scattered tasks with a simple, shared program. Use bullets, dates, and owners. *Week 1: deliver A, fix B, or show C *Week 2: validate with your stakeholders *Week 3: quantify impact and ROI deltas *Week 4: review, decide, and schedule go-forward 4) Make the commitment explicit Ask the decision question, clearly and directly: “If we do X by [date], and you see Y results and Z ROI, will you move forward with us rather than cancel?” 𝐆𝐞𝐭 𝐚 𝐲𝐞𝐬, 𝐭𝐡𝐞𝐧 𝐫𝐞𝐬𝐭𝐚𝐭𝐞 𝐢𝐭 𝐛𝐚𝐜𝐤 𝐭𝐨 𝐜𝐨𝐧𝐟𝐢𝐫𝐦. 𝐓𝐡𝐢𝐬 𝐜𝐫𝐞𝐚𝐭𝐞𝐬 𝐦𝐮𝐭𝐮𝐚𝐥 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲. 5) Define how value will be shown, not just sent Agree on exactly what you will deliver and how they will validate it. 6) Assign owners on both sides Document who from their team will attend reviews, who gives final sign-off, and who you will avoid single-threading with. Ask for a backup contact. 7) Put it in writing, same day Email the one-pager plan with bullets, dates, and the previously captured “yes.” Reference that the next emails and reports are part of this plan, not random touches. This reframes every follow-up as progress against a shared program. 8) Run weekly proof reviews, live Short calls to show progress, remove blockers, and reaffirm the commitment. Keep artifacts tight: 1-page recap, 3 bullets, 1 decision. 9) Close with the agreed decision On week 4, ask the decision exactly as framed at the start: “We did X, you saw Y results and Z ROI, as agreed. Are we renewing and moving forward?” Because they already agreed to decide on these terms, the close is natural. Why this works: *Random actions feel like noise; a plan creates purpose and timeline. *Verbal commitment on a call reduces ghosting and creates accountability