Customer Churn Insights

“We hired you 3 months ago? Why has our churn not dropped yet?” That’s a real quote that a CCO I know recently heard from their CEO. Too often, I witness the following 4 act play: Act 1: “We have a big churn problem” Act 2: “Let’s hire a Chief Customer Officer” Act 3: “Why is churn still high?” Act 4: “We didn’t really need a Chief Customer Officer anyways” Putting aside the title, the issue is that Chief Customer Officers OWN operations and INFLUENCE the rest of the company. If I had to list the levers in reducing churn across companies that I’ve experienced, they’d go in descending order: * Product-market fit * Balance of desire for growth with aligning to the Ideal Customer Profile * Product stickiness * Competitive dynamics * Pricing * Product functionality and quality * Post-sales operations “Wait - did Nick say that post-sales operations don’t matter?” Of course not. All I’m saying is that rethinking onboarding, hiring #CustomerSuccess Managers, streamlining support, etc. can only get you so far. Putting numbers on it… - If your Gross Retention is < 80%, I’ve found that strong Chief Customer Officers can reduce churn by 3-5 points, since there is a lot of low hanging fruit. - If your GRR is between 80 and 90%, it’s probably closer to a 1-2 point reduction potential. - If your GRR is above 90%, a 1 point churn drop is massive. What about the rest? The biggest churn drops come from things like the below, which CCOs can identify and then partner with colleagues to implement: * “Customers that use feature [X] have 10 points less churn” => Product: Make feature X easier to deploy * “Clients that buy from us that use [integrated system Y] churn at a high rate” => Marketing: Avoid outbound efforts to [Y] audience * “Our pricing model is causing churn because it becomes unaffordable at high volumes” => Product Marketing: Rethink the high end of the pricing curve The CCO role isn’t just about being a detective and solving churn on your own. It’s also about being a search light - shining visibility onto how the rest of the company can reduce churn.

My biggest takeaways from Jason Cohen: 1. “Too expensive” is never the real reason customers cancel. They already saw your pricing and decided to buy, so something else changed. When customers cite price, dig deeper—the actual reason might be changing needs, integration issues, or feature gaps. 2. Ask “What made you cancel?” instead of “Why did you cancel?” Jason tested both phrasings and saw response quality double with the “what made you” version. The first version directs attention to the product or situation and invites one-word deflections like “budget.” 3. Most companies undercharge because they just guessed at pricing and never revisited it. One founder selling to enterprise charged $300 per year, and Jason advised switching to $300 per month. Signups stayed exactly the same. When you 12x your price and conversion doesn’t budge, you’re not even close to finding the right number yet. 4. Pricing selects your market more than it signals value. When your product costs too little, larger companies assume it can’t be serious: not mature enough, no governance policies, inadequate support. Raise prices and you don’t necessarily lose customers; you enter a different market segment where your price signals credibility. The founder who went from $300 per year to $300 per month and saw no change in signups—he just shifted who was buying. 5. Your churn rate sets a ceiling on your business that most founders underestimate. The math is simple: divide your monthly new customers by your monthly cancellation rate, and that’s the maximum number of customers you will ever have. This is why logo churn is the first metric to examine when growth stalls. 6. Onboarding is the highest-leverage lever to reduce churn. Small improvements in the first 30 days compound into retention gains over the customer lifetime. When you don’t know where to start on retention, start with onboarding. 7. Positioning can allow you to charge an order of magnitude more without changing your product. The same exact product can command higher prices depending on how you frame it. “Cut your ad costs in half” caps what customers will pay—they’ll only give you a fraction of the savings you drive them. While “double your leads” aligns with what executives actually want and opens a much higher budget. CEOs reward growth; they merely acknowledge cost savings. 8. Sometimes the right answer is accepting that not growing is OK. If you’ve optimized churn, pricing, NRR, and channels, maybe growth has natural limits. Bootstrap founders reach a point where healthy annual dividends make further scaling optional. The question “Do you need to grow?” deserves honest examination—not because stasis is fine but because growth at all costs can destroy what made the company good.

Churn isn't a Customer Success problem. It’s a *business* problem. And it might be why you miss the 2026 plan. Just look at the 3-year ARR impact of different growth initiatives^ for a typical $10M ARR SaaS co: - Increase prices by 50% for existing customers: +$1.7M ARR 🙂 - Increase prices by 50% for *new* customers: +$5.4M ARR 😃 - Increase acquisition by 50%: +$5.4M ARR 😃 - Increase prices by 50% for both: +$7.1M ARR 😁 - Reduce churn by 50%: +$8.9M ARR 🤯 Of course, CS teams are on the front lines working with customers. But there's only so much they can do & they're busy creating value in a bunch of other ways: CSAT & referrals, identifying expansion opps, customer insights. What *can* prevent churn: 1️⃣ Sell to the right customer. I've seen products where annualized retention can range from 50% to 90%+ across different types of customers. Selling to the right ICP who values your product is often the top change that moves the needle. 2️⃣ Stop overselling on the 1st deal. It's usually better to start smaller, prove value quickly, and then unlock growth opportunities in the future. This also leads to faster sales cycles. 3️⃣ Market to your customers. Marketing isn't only for prospects. Your existing customers should hear about the latest features, learn best practices and get connected to a peer community. 4️⃣ Nail onboarding. A surprising % of folks who churn never really effectively launched in the first place. (This is especially true for PLG/self-serve). 5️⃣ Set up integrations. When your product is embedded in the customer's workflow & other systems, it's hard to rip-and-replace. Three reasons why: (a) connected data, (b) easier user adoption, (c) use case expansion. 6️⃣ Solve more problems. By broadening use cases for your product, you get more champions who'll go to bat for you at renewal (which is especially important if your original buyer leaves). 7️⃣ Give yourself more time. Moving from monthly to annual (or multi-year) plans can be controversial. But IMO you're usually better off because you have more time to impress the customer & the customer is more motivated to implement the product. --- Every team has a role to play in preventing churn. ^Data comes from the ChartMogul Scenarios feature and is based on a median $10M ARR SaaS company. Check out the full growth levers report here: https://lnkd.in/entFSeJ8 #customersuccess #churn #startup

Yesterday was my last day as Catalyst's CRO. Mark! Catalyst/Totango just merged. Why leave? Here are my reasons and learnings. 1. Mission accomplished → the Chiu brothers brought me in to elevate GTM for an exit event just like this one. I'd never been an exec through an exit and wanted that experience. Box checked. 2. Revenue leaders aren't ready for CS to change → many CS leaders are clamoring to be let loose yet their CRO or CEO is holding them back, scared to make the changes necessary to make CS a revenue engine. 3. Post-sales is in a crisis → scaled down teams, uncertain digital strategies, decreasing investment from the business, and a whole lot of finger pointing has put CS and CS leaders into a no-win situation: You can't increase NRR, yet you are held accountable to it. 4. The best weapon against churn is your product → for over 20 years, CSM super humans have tried to make up for hard-to-use, buggy, complicated, confusing, and impossible-to-understand-the-value products. When you manufacture a lemon of a car, no mechanic can keep it running for long. Many product teams need to be held accountable for churn, not CSMs. 5. Sales kills NRR → the amount of new logo deals brought on as bad fit customers is 5x higher than most execs want to admit. The need for growth and the difficulties of finding good-fit customers in a buying mode (or nurture them into a buying mode) is punitive against NRR. A CEO/CRO would rather sign a bad deal and get a step closer to a missed target and deal with the certain churn later than do the right thing. 6. Product data is a joke → why can nobody understand product telemetry and usage data...much less connect that to customer value. Just bc you know logins (and finding that value in your data warehouse is like finding a needle in a haystack) doesn't mean we are getting signals that alert us to at-risk customers or show us how to help them. 7. Health score proxies → everyone is looking for a health score that predicts churn/renewal. It ain't happening. That's not what they are. It's like looking at a fridge full of ingredients and knowing the exact dishes a chef will make. There are a million directions you can go with the same signals and sometimes you can only figure out you are gonna eat some kind of pasta. 8. Customer journey failure → most journeys are nothing more than a selfish way to see if your internal onboarding checklist is completed. It's not a "customer" journey bc the customer goes nowhere on said journey. 9. Gainsight → I have a huge respect for Nick and what he's done, but their ideas and product are slowing change and evolution. They have vested interest in things staying the same, most people are missing that. Excited for the "new" Catalyst. Proud of what we did. Missing my teams already.

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

Two years ago, I helped a startup launch a new conversational AI feature. At launch, every metric looked good: DAUs and engagement up, longer sessions, ‘Helpfulness’ was scoring 4.2/5. But four weeks later, we discovered the problem:   14D and 30D 𝗿𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 was <5% 𝗧𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺? While, the product answered ALL of the users’ questions. And the answers 𝘴𝘰𝘶𝘯𝘥𝘦𝘥 correct. But they weren’t accurate enough to be useful. As a result, users never came back. We had spent six figures and four months building a feature that users abandoned immediately. That’s when we realised what went wrong: We focused on 𝗽𝗿𝗼𝗺𝗽𝘁𝗶𝗻𝗴, did “𝙫𝙞𝙗𝙚 𝙘𝙝𝙚𝙘𝙠𝙨”, and thought metrics like “𝗵𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻” and “𝘁𝗼𝘅𝗶𝗰𝗶𝘁𝘆” were enough. But the real challenge was not prompting. It was 𝗲𝘃𝗮𝗹𝘀 We didn’t have an evaluation strategy. We didn’t even know how to build one. That’s when I took Hamel H. and Shreya Shankar's course, "𝗔𝗜 𝗘𝘃𝗮𝗹𝘀 𝗳𝗼𝗿 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝘀 & 𝗣𝗠𝘀." What I learned in that course shaped how I build AI products. Here are my top learnings: 1. Top 1% of AI teams master one skill: 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻-𝗖𝗲𝗻𝘁𝗿𝗶𝗰 𝗘𝘃𝗮𝗹𝘀.     2. They build systems that tell them exactly WHERE the product fails to meet user needs.     3. Asking "Is it good?" is not enough.     4. Use 𝗘𝗿𝗿𝗼𝗿 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 to find the 20% of failures causing 80% of churn.     5. You need to 𝗱𝗲𝗳𝗶𝗻𝗲 𝘄𝗵𝗮𝘁 “𝗴𝗼𝗼𝗱” 𝗺𝗲𝗮𝗻𝘀. And then align your whole team on the definition.     6. 𝗕𝘂𝗶𝗹𝗱 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗲𝗱 𝗟𝗟𝗠-𝗮𝘀-𝗷𝘂𝗱𝗴𝗲 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗼𝗿𝘀 𝘆𝗼𝘂 𝗰𝗮𝗻 𝘁𝗿𝘂𝘀𝘁. Then validate them against human judgment to correct for bias. This enables testing at scale. Every AI feature you ship without evals is a 𝗴𝗮𝗺𝗯𝗹𝗲. One failed feature can cost you 𝘀𝗶𝘅 𝗳𝗶𝗴𝘂𝗿𝗲𝘀. This course costs $𝟮,𝟱𝟬𝟬. Even if it saves you from just one failure, the ROI is great. That’s the tradeoff. And it’s obvious. Link in comments. P.S. Get a 𝟯𝟱% 𝗱𝗶𝘀𝗰𝗼𝘂𝗻𝘁 on the course with the link below P.P.S Attached: cheat sheet with top my top learnings

Most SaaS companies focus on acquiring new customers. But the real revenue driver? Retention. - Acquiring a new customer costs 5X more than retaining an existing one. - Selling to a current customer has a 60-70% success rate. - Selling to a new prospect? Just 5-20%. The math is clear: If you’re not optimizing for renewals and reducing churn, you’re burning money. Every SaaS company eventually hits a wall where churn compounds. More customers leave → Higher acquisition needed → Growth stalls. David Skok puts it best: Churn is a leaky bucket. The bigger you grow, the more customers you need just to stay in place. So, how do you plug the leak? 1️⃣ Customer Success > Customer Support Proactive beats reactive. Retention starts before problems arise. - Onboarding, engagement, and expansion must be intentional. - Companies with dedicated CS teams cut churn by 41% in a year. 2️⃣ Measure the Right Metrics Not all churn is created equal. Track: - Customer churn rate → % of customers lost. - Revenue churn rate → % of revenue lost (more meaningful If the contract value varies a LOT!). - Net Revenue Retention (NRR) → Renewal + expansion revenue (gold standard for SaaS growth). 3️⃣ Design for Retention from Day 1 First-session success = Long-term retention. - Groove found that users who spent less than 2 minutes on their first login had a 60% churn rate. - The fix? Optimize Time-to-Value (TTV) to drive early engagement. 4️⃣ Incentivize Longer Commitments Monthly plans = Higher churn. - Annual/multi-year contracts lock in retention. - Offer compelling reasons to commit (discounts, premium features, exclusive support). 5️⃣ Use Behavioral Triggers - Buffer’s re-engagement emails for inactive users led to a 22% churn reduction. - HubSpot's CHI (Customer Happiness Index) predicted at-risk accounts before churn. What This Means for You Retention isn’t a support function—it’s a growth strategy. The best SaaS companies: - Build cross-functional retention teams. - Align Product, Sales, and CS to drive ongoing value. - Treat renewals as a natural progression, not a last-minute pitch. If you solve churn and renewals, you unlock sustainable, profitable growth. How is your SaaS business tackling retention? Let’s discuss. __ ♻️ Reshare this post if it can help others! __ ▶️ Want to see more content like this? You should join 2238+ members in the Tidbits WhatsApp Community! 💥 [link in the comments section]

I had coffee with a founder who sends every churned customer a $50 Amex gift card and a handwritten note. The note says: "Thanks for giving us a shot. Would you be willing to spend 15 minutes telling us what we got wrong?" 68% of churned customers take the call (they get the gift card whether they take the call or not) More than 2/3 of the customers who left his product voluntarily get on the phone to explain why... pretty crazy when you think about it. He records every call (with permission) and tags the reasons into a database. After two years, the he used that data to completely change the business and reduce his churn by 20%. The top reason for churn wasn't what he expected either. It was "we couldn't get our team to use it." An adoption problem, not a product problem. So he rebuilt onboarding from scratch. Added a mandatory training session. Built an adoption dashboard that flags accounts where usage drops below a threshold within the first 60 days. Churn dropped by 40%! The $50 gift card costs him ~$6,600/year but the are worth exponentially more to him long term. Most companies survey churned customers with an automated email that gets a 4% response rate and congratulate themselves like they did a good job. This founder treats every lost customer like a consulting engagement. The difference in data quality is unbelievable.

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