Churn Rate Tracking

Netflix found that users who cancel without saying a word are 2x harder to win back than those who first raise a complaint. Most companies track who complains. But you should be more worried about who doesn’t. If you’re only looking at support tickets to spot churn risk, you’re missing the bigger picture. Some of your most at-risk users are the ones not using the product and not reaching out. They’re quietly slipping away. The real insight comes from joining support data with product usage. But Customer Success teams often don’t have access to usage data. Not because they don’t want it, but because it’s buried in tools they can’t query, stuck behind engineering bandwidth, or siloed away from their daily workflow. Low usage and no complaints? That’s your danger zone. High complaints with high usage? That’s actually a sign they still care. Track complaints, yes. But also track silence. Silence is often the first step to goodbye.

Churn isn't just a customer success problem. Here's how PMs & PMMs can enter the chat: First, 3 things we do to lay down the groundwork: 1) Track churn reasons at the point of exit, even if you have to put down money. Without knowing why customers are leaving, it's hard to figure out whether you need to adapt the product, your messaging or target audience. The biggest mistake is attempting to fix something that's not broken. Use exit interviews or win/loss analysis. 2) Tracking BOTH logo churn & revenue churn gives you a better picture. If you just measure logo churn, you won't be able to differentiate between the weight of those lost accounts. It could be a high-value segment or a barely lucrative one. Similarly, tracking just revenue churn hides how your revenue is distributed across customers. You can have low revenue churn simply because a few high-value accounts are still intact, which implies a high-risk portfolio. 3) Churn analysis is a vital input into your acquisition strategy. Understanding churn not only helps you understand complaints but also poor-fit customers. Looping this intel into your GTM allows you to refine messaging and pursue better-fit segments. -- So, how do PMs and PMMs act here? Get ready for a lot of ifs: If there is high logo churn + low revenue churn: - If small customers struggle with activation, PMs can seek to simplify onboarding and add more value to entry-level tiers. - If certain low-value segments struggle, PMMs can adjust messaging to laser-focus on stronger personas and use cases. If there is low logo churn, high revenue churn: - If enterprise needs are unmet, PMs should prioritize filling gaps like security, scalability, advanced modules. - PMMs can partner with marketing & customer success teams to develop educational programs and personalized customer marketing campaigns. If the product has stable growth (low logo & revenue churn): - PMs can focus on expansion features and growth loops. - PMMs can help build customer advocacy and referral programs. If the company is burning down (high logo & revenue churn): - Both PMs and PMMs will have to partner together to conduct discovery, audit the product experience, do a gap analysis etc. - Figure out where the product falls short and/or where the GTM is flawed. Customer success can orchestrate some of this for sure. But PMs and PMMs can deliver a lot of concrete value faster. -- Does your team discuss churn regularly?

🙈 Confession: My startup Curata once faced a dismal 60% churn rate, renewing only 40% of revenue. It was tough & we were on the brink of losing hope. 🚀 But guess what? We managed to turn the tide and double our renewal rates in just nine months! How did we do it? Through a game-changing approach called "Critical Care" that we developed in conjunction with our advisor, Mark Roberge (of Stage 2 Capital & founding CRO of HubSpot). We all strive for customer success, but did you know there are four distinct means to achieve it? Let's explore them: 💊 Customer Support (Urgent Care): Reactive support is essential for addressing customer issues, just like visiting an urgent care clinic when you're unwell. 🍼 Onboarding (Neonatal Care): Onboarding ensures a smooth start for customers, much like neonatal care for infants, setting them up for a healthy journey. 🩺 Business Reviews (Routine Checkups): Regular checkups through business reviews help understand customer needs, like routine checkups with a doctor. 🚑 Critical Care (The Advanced Approach): Here's the game-changer! Critical Care is an advanced form of customer success that proactively detects subtle issues and provides urgent attention -- like dispatching an ambulance out to the patient if anything seems wrong. 🚨 What is Critical Care? It's like having remote diagnostic monitors on a patient, allowing us to identify potential churn risks early on and take immediate action before it was too late. Here are just a few some Critical Care triggers to track: 📉 Drop or no recent product usage 🔗 Broken integrations 👤 Champion left the organization 🆕👥 New users created in product 🏢🔄 Acquisition of customer's company 🔄📝 Change in use case ⏳💸 Overdue payments Most companies typically just do the support, onboarding, and business reviews, but these aren't enough. By the time that it's time for a quarterly business review, often the customer has churned already (at least mentally). That's why critical care is so important. Identifying these triggers early gave us the power to take swift action, preventing churn and strengthening customer relationships. In short, we adopted attitude of extreme ownership where any customer problem became our problem. We had to retool our process, technology and most importantly the culture to make this change, but once we did the results followed in our renewal rates. 👉 If you're facing similar challenges in your SaaS business, I hope that you can turn things around from what I went through the hard way -- and what worked. Read the full post to learn how we did this & how you can too 👇 https://lnkd.in/gVtzwZXr #SaaS #CustomerSuccess #RenewalRates #BusinessGrowth #CustomerRetention Special thanks to the dedicated former members of the Curata customer success team: Matt Cordaro, Craig Blum, Brady Delahanty, Andrew Cleak, Jesse Meeks, ALM, Keegan Hinson, Derek Jacobson, Brian Felschow, Tyler Beeson, Erica Ayotte Favorito, Dave Wigder.

Why are companies so often at the extreme ends of "using Data Science & AI"? Many startups and scale-ups either don't do any Data Science or they throw predictive models at everything. Personally, I made both mistakes. We once spent hundreds of hours on a data-science-powered recommendation engine only to throw it away and turn to semi-manual recommendations. Churn is another example. I often see a tendency in startups to determine "churn" by choosing a number of days since the last purchase of a customer based on gut feel. If the customer has not bought anything in the last X days we consider that customer churned. It's usually a round number like 30 days, 90 days, 180 days. On the other hand, I have seen many startups prematurely building super sophisticated churn scores and never using them. Here's a data-driven way to do it - without building complex predictive models. 🤓 👉 1. Look at all purchases for each (repeat) customer 👉 2. Determine the maximum number of days between two purchases for each customer (max_interpurchase_interval) 👉 3. Count the number of customers per max_interpurchase_interval and plot them on a chart like below. In the chart, you can see that 60% of all customers who haven't made a purchase in 32 days will not make another purchase. Or in other words, 40% of customers will still purchase if they haven't done so for 32 days. After 65 days of inactivity, only 20% of customers will make another purchase. You could use the 60% marker for a "Soft-Churn" definition and the 80% marker for a "Hard-Churn". The markers can be adjusted up or down based on the cost of re-activation and lifetime value lost in case of churn. How are you approaching customer churn measurement?

Dispensaries are usually tricked by strong retention numbers and assumes everything is fine. But is it? Many cannabis retailers overestimate their customer loyalty because their data is skewed by a small group of frequent shoppers. These VIPs visit often, spend more, and make retention rates look better than they actually are, while new and casual customers quietly disappear. → Where Most Dispensaries Get It Wrong X They focus on overall repurchase rates instead of breaking them down by customer type. X They assume a high repeat purchase rate means all customers are coming back. X They don’t see how many first-time buyers never return. If 20% of your customers are consistent buyers, they might be carrying your retention numbers while the other 80% churns. That’s a big problem for long-term growth. If 20% of your January customers are New and 80% are returning, you do not have an 80% Retention Rate. → How to Measure Retention the Right Way 1. Segment Retention by Customer Type ▸ Look at first-time customers vs. repeat buyers vs. VIPs. ▸ Are new customers coming back, or is your business relying on a small group of loyal shoppers? 2. Track Churn at Every Visit ▸ What percentage of first-time customers make a second purchase? ▸ How many second-time buyers make it to a third visit? ▸ The biggest retention drop-off often happens after the first or second visit. 3. Identify Where You’re Losing Customers ▸ Are people churning because of pricing, experience, product selection, or lack of engagement? ▸ Look at drop-off points and test win-back emails, personalized recommendations, and better onboarding strategies for new customers. → What to Do Next Pull your retention data and break it down by customer segment. If VIPs are keeping your numbers afloat while new customers churn, you have a growth problem. It might be why your monthly revenue has become stagnant. If you want to truly understand your retention and fix hidden drop-off points, my Team and I specialize in advanced customer lifecycle analytics for dispensaries. Let’s take a deeper look at your numbers.

Risks in your customer base are the starting point for churn. If you’re not actively tracking and addressing them, you’re leaving retention to chance. Here’s how to get a clear view of the risks that could lead to churn—and, more importantly, how to mitigate them. 1. Define the Risks You Want to Track Start by identifying the key risk factors in your customer base. A great way to do this is by analyzing your churned or downgraded customers—what were the root causes? For example: -> Decreasing product adoption (customer using your product less) -> Bugs (customer flagging issues with your product) -> No engagement (not engaging with your customers) -> Termination risks (customer -> Competitor risks (customer contemplating or testing competitors) -> Financial risks (customer not paying invoices or delayed payments) -> Champion leaving (key stakeholder leaving) Clearly define each risk so your team knows what to look for. 2. Create a System to Track These Risks -> If you're just starting out or managing a small book of business (fewer than 20 customers per CSM), a spreadsheet can work. Use your predefined risk categories and add a rationale for each risk you track. -> As you scale, manual tracking becomes unrealistic. Automate risk tracking through your CRM (like HubSpot) or a customer success platform. Use data-driven signals—such as product usage trends, support tickets, and engagement scores—to surface risks proactively. 3. Continuously Refine Your Risk Tracking The risks that caused churn six months ago may not be the same today. Regularly review churned customers, update your risk categories, and adjust your playbooks. 4. Track all these risk categories in your CRM and make a plan to tackle them For every risk, define an impact driver—a proactive action that reduces the likelihood of churn. For example: Low adoption → Define key use cases & track milestone achievement No executive engagement → C-level to c-level outreach Declining engagement → Schedule recurring meeting or find a new stakeholder

Today, let's tackle one of the most puzzling questions in the SaaS universe. When do we actually count churn? 💡 Let's dive in... 📅 Churn Reporting Timing: - Finance Perspective: 🏦 Finance teams report churn in the month the revenue disappears. But that's a bit confusing. If revenue stops mid-month (for example, subscription stopped April 15, half month of rev rec), this is recorded as contraction. We see a decrease in MRR but it's not 0. In the following month, when the MRR is 0, the formulas will capture this month as the churn month. Even if the full month was recorded in April, the formulas capture the churn in the following month (May). - Customer Success Perspective: 🤝 - Customer success teams may record churn when the customer indicates their intent to churn, even if the revenue continues until a later month. Knowing the indicated churn helps FP&A teams forecast future revenue accurately. 💸 Revenue Retention Formulas: - Finance relies on revenue retention formulas to determine churn by identifying the month when revenue from a customer stops. These formulas are based on monthly recurring revenue (MRR) schedules. This is a key item in due diligence. 📊 Indicated vs. Actual Churn: - Indicated Churn: 🗓️ This occurs when a customer communicates their intention to leave at a future date. Customer success teams track this to aid in forecasting. Or accounting may track this. - Actual Churn: ✅ - This is when the customer's revenue actually stops, and finance teams use it for accurate revenue tracking, reporting, and metrics. 🧮 Churn Impact on Forecasting: - Tracking both indicated and actual churn is essential for accurate financial forecasting and maintaining the health of the SaaS business. Any different thoughts on this? #SaaS

Nobody talks about this. High growth companies are getting killed by their churn, and they're not noticing it. Here's how: Most b2b customers churn year 2. Which won't show up in the results until year 3. This means that the churn of one year's new business will not be visible in the results until 2 years later. With me so far? High growth companies tend to have a significant increase in new business every year. This means that your churn is disproportionally taken into account to the increased revenue of that year. A simplified example: Year 1 renewal: New business added: 100 000 ARR on 10 customers. Total ARR: 100 000. Churn: 0 ARR on 0 customers. Year 2 renewal: New business added: 300 000 ARR on 30 customers Total ARR: 400 000. Churn: 30 000 ARR on 3 customers. Counts as 7.5% but is actually 30% of the customers acquired before year 1 renewal. This is where it gets interesting. What ends up happening is that you think you're losing 7.5% annually, which seems manageable. But actually, you're losing 30% of your acquired customers each year, a rate that's alarmingly high. As long as you keep growing rapidly year after year, it will be hard to spot this. But as soon as your growth stagnates this effect will be seen in everything, everywhere, all at once. Suddenly, it's clear that churn isn't just a small issue -- it's been a significant problem all along. But then it will be too late. So how do companies get around this? 1. Be aware of this "lagging churn" effect. 2. Prioritise retaining customers over acquiring new ones 3. Scrutinise the customers you bring in early. Are they the right fit? Will they get value from the product? Will they stay? Will they be high or low maintenance? And take this seriously. I've seen so many companies fall into this trap. Usually around year 5-6 is when the effects really get overbearing. What are your views on this effect? Any suggestions on how to tackle it? #customersuccess #churn #growth #b2b

If you're tracking Repeat Purchase Rate, you're already late. Most brands treat RPR as a north star for retention. But it’s a lagging indicator — it tells you what happened, not what’s about to happen. By the time your RPR drops, churn has already occurred. You’re in recovery mode, not optimization mode. So what should you track before churn shows up? Here are three leading indicators that are giving us far more predictive insight across the brands we’re working with: 1. Time-to-Second-Purchase (T2P) Your best early signal of habit formation. • T2P < 21 days → High retention probability • T2P > 45 days → Intervention window: • Loyalty trigger • Reminder • Friction removal Great retention programs are built around this clock — not arbitrary cadences. 2. Post-Purchase Engagement Rate The % of new customers who interact with any loyalty or brand touchpoint in the first 7 days: • Visited rewards dashboard • Clicked a referral link • Engaged with brand content or email • Redeemed a bonus or offer This shows whether customers are mentally subscribed to your brand — not just transactionally. 3. SKU-Driven Retention Mapping Not all products create loyalty. Some create habits. Others just create one-time spikes. We’re seeing brands track retention likelihood based on the first purchase SKU. Patterns include: • Product A → 2.5x higher repeat rate • Product B → 80% never return Use this to optimize: • Ad targeting • Onboarding flows • Post-purchase journeys RPR is still worth tracking. But if it’s the only thing you’re watching, you’re flying blind. Leading indicators help you act before the drop-off. So what signals are you watching?