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Customer retention metrics tell you why customers leave, not just how many. Churn rate alone is a fire alarm - loud and obvious, but it won't tell you where the smoke is coming from. The 14 metrics in this guide dig into the who, when, and why behind retention.
This list covers churn, revenue, engagement, and product-specific metrics. From monthly churn rate and CLTV to feature adoption and cumulative cohort revenue, these are the numbers that separate reactive teams from proactive ones.
Built for SaaS teams managing post-sale retention. Whether you're a lifecycle marketer proving program ROI or a product manager connecting user behavior to business outcomes, these customer retention metrics are your operating system.
Acquiring a new customer costs 5 to 7 times more than retaining an existing one. That stat alone should reframe how your team allocates budget and attention. But the case for retention goes beyond cost savings.
Research from Bain & Company shows that a 5% increase in customer retention can boost profits by 25% to 95%. Retention isn't a defensive play - it's a revenue multiplier. Every month a customer stays, they renew, expand their plans, and refer others to your product.
For lifecycle marketers, customer retention metrics are how you demonstrate program ROI to leadership. They shift the conversation from "how many emails did we send" to "how much revenue did we protect and grow." For product managers, these metrics are the signal layer between user behavior and business outcomes - the data that tells you whether your latest release is actually moving the needle.
The challenge is knowing which metrics to track and how to use them together. That starts with the basics.
Understanding how to measure customer retention starts with knowing the numbers. Customer retention rate is a foundational metric that tells you how well you're maintaining customer relationships throughout the customer journey.
The customer retention rate formula is straightforward:
Customer retention rate = (customers at end of period - new customers) / customers at start of period
That formula is easier to read than it looks. Here's an example.
In this example, of the 200 customers who started the quarter with you, 90% stayed, and 10% churned. By tracking this metric over time, you can see how well your customer retention strategies are working. For instance, if you notice a high churn rate and your retention dips to 60% for two consecutive quarters, it's a signal that there's an issue in your customer journey that needs immediate attention.
What is a good customer retention rate? Benchmarks vary by industry and business model. B2B SaaS companies typically see retention rates between 85% and 95%. Consumer apps trend lower. Enterprise SaaS products should target 90% or above. That said, your own trend over time matters more than any industry average - a rising retention rate is a stronger signal than hitting a benchmark once.
Although useful, the retention rate alone doesn't tell you why customers leave. That's where our other metrics come in.
If you want to build a loyal customer base and encourage repeat purchases, these customer retention metrics will help you zoom in on what's happening and why, so you can make informed decisions to grow your business. Understanding the "why" helps you turn high churn into high growth.
Monthly customer churn rate is a high-level metric that tells you what percent of your customers are churning every month. It's the inverse of your customer retention rate - and favored by those pesky glass-half-empty people.
Monthly customer churn rate formula: (number of customers churned in a month / total number of customers at the start of the month) x 100
Example: If Disney+ has a million paid subscribers at the beginning of the month, and of those one million, 10,000 churned, then its churn rate would be 1%.
How to use it: Track monthly churn to spot patterns over time. A consistent increase might signal bigger issues with your product or user experience.
The monthly customer churn rate by itself won't tell you a lot - everyone has the occasional good or bad month. However, churn and retention trends become apparent when you look at them over 6 months or a year. Tracking this metric helps you determine whether all of your retention efforts are working and is a great macro customer retention KPI for your business. If churn is increasing steadily, dive into user feedback to identify pain points or common reasons for leaving.
SaaS benchmark: Average monthly SaaS churn typically falls between 3% and 8%. Above 5% warrants investigation.
To get a clearer picture of how well you're retaining customers, break down your customer retention rate by cohort or segment over a given period.
Cohort retention rates focus on users who started during the same time frame. If you've overhauled onboarding, tracking retention by cohort shows how those users respond over a defined period.
Segment retention rates focus on different segments of your user base. A UI update might be great for beginners but not for power users. Measuring by segment helps you see these differences.
Customer retention rate formula by cohort: (customers in a cohort at end of period / customers in a cohort at start of period) x 100
Example: If Trello has 150 customers starting on May 4th and a week later only has 110 of those customers remaining, its week-1 customer retention rate is 73%.
Customer retention rate formula by segment: [(customers in a segment at end of period - new customers in that segment) / customers in a segment at start of period] x 100
Example: If Notion starts with 200 customers in its small business segment at the beginning of May, gains 10 more throughout the month, and ends the month with 205 total customers, then its retention rate is 97.5%: [(205 - 10) / 200] x 100.
How to use it: Mix and match cohort and segment metrics for even more insight. If you're tailoring experiences for key segments, track how new cohorts within those segments respond. If an update improves the experience for new users but leads to high churn among power users, it may be time for more segment-specific adjustments.
SaaS benchmark: A healthy SaaS week-1 cohort retention is typically 40% to 60%. If you're below 30%, onboarding is likely the culprit.
Monthly recurring revenue (MRR) is simply the sum of all of your recurring revenue sources in a month (so pennies found in the office couch don't count). Your revenue churn rate shows you how much of your MRR is heading for the exit each month.
Revenue churn rate formula: {[(MRR at start of month - MRR at end of month) - upsells] / MRR at start of month} x 100
Example: If Buffer's MRR at the beginning of the month was $1 million, it had $50,000 in upsells, and it ended the month with $900,000 in MRR, then its revenue churn rate would be 5%. {[($1 million - $900,000) - $50,000] / $1 million} x 100 = 5%
How to use it: Segment your MRR by customer value to spot which customer segments contribute most to churn.
The advantage of calculating churn in terms of revenue instead of customers is that it appropriately weights the value of each customer. Customer retention rates value each customer equally, so an influx of smaller accounts can hide that you're losing the big contracts that drive revenue. Focus retention efforts on high-value customers by addressing their specific pain points.
SaaS benchmark: Top-performing SaaS companies target gross revenue churn below 5% annually. At 10% or higher, growth becomes very difficult.
Most retention dashboards stop at churn. Tracking reactivation MRR tells you how much of that lost revenue you win back - and whether your win-back programs are paying off. It's also worth tracking what percentage of your churned customers eventually return via your reactivation rate.
Reactivation MRR formula: Sum of all monthly revenue from customers that formerly churned = Reactivation MRR
Example: SpyFu currently has 12 customers who have reactivated. 4 of them are on an average plan worth $50 a month, while 8 of them are on an advanced plan worth $80 a month. The company's total reactivation MRR would be $840.
Reactivation rate formula: (number of reactivated users / number of churned users) x 100
Example: Ubersuggest had 10,000 churns last year. Of those churns, 200 have reactivated, so its reactivation rate is 2%.
How to use it: Track this to assess how well your win-back campaigns are performing.
Use these metrics to gauge how well your efforts to win back old customers are working. Sometimes customers churn for reasons other than you. If they come back, take it as a vote of confidence in what you're doing. Identify which win-back strategies (personalized offers, new feature updates) are most effective and double down on them.
SaaS benchmark: Typical B2B SaaS reactivation rates fall in the 1% to 5% range. If yours is higher, your product still has pull even with churned users.
Customer lifetime value (CLTV or CLV) is a top-level metric indicating how well you're keeping your customers. The longer they stay, the more months they pay for your subscription, and the higher their lifetime value.
CLTV formula: Average value of customer (monthly or annual basis) x average customer lifespan = CLTV
Example: Netflix's average customer value is $15 a month. If the average subscriber stays for one year, then their CLTV would be $180 ($15 x 12 months).
How to use it: Monitor CLTV to ensure customer acquisition costs are justified and profitable.
CLTV is great to track because it helps you diagnose where things are going wrong (or right) for your retention. When tracking CLTV, keep a record of average value and lifespan to see how these two inputs fluctuate. If your CLTV drops due to lower value, you can start working on optimizing your upselling efforts. If the problem is lifespan, optimizations to your aha moment may be just what the doctor ordered.
SaaS benchmark: A healthy SaaS CLTV:CAC ratio is 3:1 or higher. Below 1:1, you're losing money on every customer.
OpenView Partners developed a formula called cumulative cohort revenue (CCR) - the total revenue earned from a group of customers acquired within a time period (usually 12 months), compared against customer acquisition cost (CAC).
CCR formula: Total cumulative revenue for a specific cohort over a 12-month span / sales and marketing spent in the cohort's initial month = CCR
Example: Semrush has earned $500,000 a year from the cohort of users that started in January. The company spends $100,000 on this cohort in the first month. The 12-month CCR ratio of that cohort is 5x. In other words, this cohort is earning the company 5x on its initial investment in only a year.
How to use it: Compare CCR across different cohorts to optimize acquisition strategies.
This formula includes a span of time, so you're comparing the actual total revenue of any given cohort against the amount of money you spent to acquire them. It gives clear insight into where you break even with your CAC. Comparing your CCR versus CAC across different cohorts shows you whether you're improving over time and how quickly you recoup acquisition spend. Invest more in cohorts that show quicker revenue recovery.
Instead of looking at just retention, you should also be looking at behavioral analytics. This will give you a sense of who's active and who just hasn't gotten around to unsubscribing. For that, you need to look at your activity levels. Depending on your product, you need to pay close attention to one of these metrics:
If your product's core value hinges on daily use (a messaging app, a workflow organizer), look at daily activity numbers. If your product's core value hinges on infrequent check-ins, track WAU or MAU instead.
Users don't just wake up one day and decide to leave your app. Churn is usually preceded by a decline in activity. Set activity benchmarks for your users - if they don't reach them, start re-engaging before it's too late.
DAU/WAU/MAU formula: There is no single formula - your analytics platform calculates this. What matters is setting the right activity threshold for your product's usage model.
SaaS benchmark: For daily-use SaaS tools, a DAU/MAU ratio (stickiness) above 20% signals healthy engagement. Slack targets above 50%.
How to use this metric in your retention strategy: Set benchmarks for engagement and use in-app messaging to re-engage low-activity users.
NPS and CSAT are two ways to measure how much a customer likes your product. NPS asks how likely they are to recommend on a scale from 1 to 10. CSAT asks how satisfied they are on a scale from 1 to 5.
NPS formula: % who are promoters (score 9 or 10) - % who are detractors (score 6 or less) = NPS score
Example: Canva tabulates its NPS scores and finds that of 100 respondents, 12 gave the company a 9 or 10, 30 gave the company a 7 or 8, while 58 gave the company a 6 or less. This would make their NPS score a -46 (ouch).
CSAT formula: (number of 4 and 5 responses) / (number of responses) x 100 = CSAT
Example: Canva tabulates its CSAT scores and finds that of 200 respondents, 112 gave the company a 4 or 5. This would make its CSAT score a 56 (much better).
How to use it: Combine NPS and CSAT feedback with quantitative data to get a fuller picture of customer retention issues.
NPS and CSAT are important because they allow you to keep your finger on the pulse of your customers. Positive trends help justify recent optimizations, while negative trends might send you scrambling for the drawing board to try something new. They also let you collect data on customers' feelings after important interactions, like after they complete onboarding, so you can narrow in on how your most crucial flows are actually performing.
SaaS benchmark: SaaS NPS averages around 31; scores above 50 are considered excellent. For CSAT, 75% or higher is the benchmark for healthy SaaS products.
Appcues lets you deploy NPS and CSAT surveys as in-product experiences, so you capture feedback at the right moment in the customer journey - not days later in an email. After collecting feedback, implement changes and monitor the impact on churn and retention rates.
Average session duration signals how engaged your users are.
Average session duration formula: Total time across all sessions / total number of sessions = Average session duration
Example: Officely's time across all sessions is 500,000 hours this year. Its total number of user sessions is 1,000,000. Its average session duration would be 30 minutes.
How to use it: Identify which features drive longer sessions and promote them.
Good average session durations depend on the purpose of your product. If your product is meant to help people quickly, like Shazam, then a longer session duration may not indicate "more engaged." But if you're running a banking app and people pop on and off in 30 seconds, they're only checking balances. Experimenting with ways to drive adoption of deeper features could increase session duration and create more upsell opportunities.
SaaS benchmark: Average session duration benchmarks vary too much by product type to quote a universal number. The question to ask is: is your average trend going up or down quarter over quarter?
Behavioral analytics tools like Appcues can surface which in-app flows correlate with longer sessions, helping you highlight underused features that add value.
You've invested in building features your customers should be using. It'd be a shame if they didn't. Feature adoption rates measure what percentage of your users take advantage of each of your features so you can push underutilized ones or put your top draws in the spotlight.
Feature adoption rate formula: (number of users of a specific feature in the last month / total number of product users) x 100
Example: Ahrefs has 1,000,000 users, and last month only 200,000 used its backlink tool. Its feature adoption rate for the backlink tool would be 20%.
How to use it: Promote underused but valuable features to the right user segments.
Get more out of this metric by digging into which segments love which features. If segment 1 likes features A and B, and segment 2 likes feature A, it's worth pushing feature B to segment 2 as well.
Low feature adoption often signals poor discoverability, weak onboarding, or wrong-fit users. In-app tooltips can solve discoverability. Checklists and guided walkthroughs address onboarding gaps. And if it's a fit problem, segment-level analysis will tell you which users to stop targeting.
SaaS benchmark: Industry average feature adoption for non-core features in SaaS typically falls around 20% to 30%. Anything below 10% for a strategic feature is a red flag.
Appcues helps product teams surface underused features through in-app tooltips, checklists, and targeted announcements - without an engineering ticket.
How to use this metric in your retention strategy: Analyze user feedback and behavior to tweak feature visibility and accessibility.
If your product is on a subscription model, you need to track your renewal rate - the percentage of customers who choose to renew their contract. It gives you direct insight into how successful you are at retaining current customers.
Renewal rate formula: (number of customers who renew that month / total number of customers up for renewal) x 100
Example: Office 365 has 200,000 customers up for renewal in January. Of those customers, only 150,000 renewed. Therefore, its renewal rate that month was 75%: (150,000 / 200,000) x 100.
How to use it: Monitor renewal rates by customer segment to predict retention success.
Use renewal rate to get out ahead of negative trends that yearly churn KPIs might miss. Look at key segments individually so you never miss the proverbial pebble that kicks off a landslide of churn. Consider early renewal offers or discounts to encourage commitment.
SaaS benchmark: B2B SaaS gross renewal rates of 85% or higher are generally healthy. Net revenue retention (NRR) above 100% means you're growing from your existing base.
An engaged customer is one that is actively using your product regularly. If they're signing in every day, there's a far better chance they're getting value and will stick around longer.
Engagement rates can be calculated based on channel, segment, or cohort:
Engagement rate by channel: (Total number of active users from a specific channel over a defined time period / total number of users from a specific channel) x 100
Engagement rate by segment: (Total number of active users from a specific segment over a defined time period / total number of users from a specific segment) x 100
Engagement rate by cohort: (Total number of active users from a specific cohort over a defined time period / total number of users from a specific cohort) x 100
Example: If Spotify has 100 users that started on January 1st and only 10 of them used the service once in the last week of January, that cohort's engagement rate would be 10%. [(10 / 100) x 100]
What's less obvious is why you'd track it by channel. Tracking engagement by channel lets you see where your most engaged customers are coming from. If you're getting the same number of sign-ups from SEO and PPC, but SEO has a far higher engagement rate, it's more valuable for your company to invest in SEO.
How to use it: Invest more in channels that consistently drive high engagement. Track engagement by acquisition channel to optimize marketing spend.
The repeat purchase rate measures what percentage of your customers make more than one purchase. A high repeat purchase rate shows that your customers see value in your product and are coming back for more.
Repeat purchase rate formula: (number of customers who made more than one purchase / total number of customers) x 100
Example: If Shopify has 10,000 customers, and 3,000 of them made more than one purchase in the last month, the repeat purchase rate would be 30%.
For subscription SaaS, think of "repeat purchase" as a plan upgrade, seat expansion, or add-on purchase. Tracking this tells you whether your customers are growing their investment in your product.
How to use it: Identify products or services with low repeat rates and explore ways to enhance the customer experience, like improving product quality or offering loyalty programs.
Get more out of this metric by segmenting your customers based on their repeat purchase behavior. This will help you understand which customer groups are most loyal and what keeps them coming back. Target loyal segments with personalized offers and exclusive deals to boost retention further.
SaaS benchmark: E-commerce repeat purchase rates of 20% to 30% are considered healthy. For SaaS, track upgrade rate as a proxy - 10% to 20% upgrade rate from free or starter plans is a reasonable target.
Keeping customers around is great, but seeing their spending increase over time is even better. The customer revenue growth rate shows how much more - or less - expansion revenue your existing customers are generating. Finance teams call this net revenue retention (NRR).
Customer revenue growth rate formula: ((revenue from existing customers in the current period - revenue from existing customers in the previous period) / revenue from existing customers in the previous period) x 100
Example: If Slack had $500,000 in revenue from existing customers last quarter and $550,000 this quarter, the customer revenue growth rate would be 10%.
How to use it: Use this metric to gauge how well your upselling and cross-selling efforts are working. If the growth rate is low, consider revisiting your pricing strategies or introducing new services to offer more value.
Get more out of this metric by monitoring it across different customer segments to see which are growing the most. Optimize pricing models and introduce tiered plans that encourage customers to upgrade, combined with personalized communication that highlights the value of higher-tier plans.
SaaS benchmark: Top-performing SaaS companies target net revenue retention (NRR) above 120%, meaning existing customers spend at least 20% more year over year. Below 100% NRR means you are shrinking from your existing base.
These SaaS metrics cover the full retention picture - from churn signals to revenue expansion. Use this table as a quick reference when building your reporting dashboard.
Knowing which customer retention metrics exist is one thing. Building a measurement practice around them is another. Here's a five-step process for SaaS teams ready to move from ad hoc tracking to a real retention measurement system.
1. Define your retention time frame. Monthly, quarterly, or annual? A self-serve tool with monthly billing should track retention monthly. An enterprise product with annual contracts should focus on quarterly and annual views.
2. Choose the right metric mix. Not all 14 apply to every business. Start with a core dashboard (customer retention rate, revenue churn, NPS/CSAT, feature adoption) and a secondary set (CLTV, cohort retention, DAU/MAU) for deeper analysis.
3. Establish your baseline. Pull 6 to 12 months of historical data before benchmarking. Without a baseline, you can't tell whether a number is good, bad, or normal for your business.
4. Set benchmarks. Use industry data as a starting point, but track your own trend as the primary benchmark. A retention rate climbing from 82% to 88% matters more than hitting the industry average of 90%.
5. Build a reporting cadence. Monthly reviews for churn and engagement. Quarterly deep dives for CLTV, cohort analysis, and revenue retention. Share results beyond your immediate team - retention data is a shared language between product, marketing, and leadership.
Behavioral data tools like Appcues can automate several of these signals, surfacing engagement drops, feature adoption rates, and NPS trends without manual data pulls.
If your customer retention metrics aren't where you'd like them to be, you don't have to sit there and accept it. Here are four places to start.
Customer retention starts with the first interaction. Customized onboarding flows give you the best chance to make a memorable first impression on all of your customers - not just your average ones. Find out what each segment expects, then tailor your onboarding to deliver that (and more). A well-built onboarding experience directly improves week-1 cohort retention (metric 2) and feature adoption rates (metric 10).
Learn more about personalized onboarding flows.
Customers might be excited about your product in the first week, but what about after the first month? Use in-app messaging and email campaigns to share new insights, educate them on features, and remind them why they signed up. In-app messaging is particularly effective because your messages never get lost in a spam folder. Targeting users before their DAU/WAU/MAU activity drops (metric 7) is far more effective than waiting for churn.
Learn more about in-app messaging.
Customers remember lousy service. In fact, Zendesk found that 61% of customers would change to a competitor after just one bad experience. The bottom line? Investing in your customer service is an easy way to improve retention metrics and fight off churn. It may not be as flashy as AI-powered this or automated that - but it might just be what boosts your customer retention rates.
Customers who rate support interactions negatively drive NPS scores down (metric 8) and are at higher risk of non-renewal (metric 11).
Learn more about making your business more customer-centric.
Tools aren't everything, but they're a force multiplier. Customer retention tools help you build better onboarding flows, improve your messaging, and boost customer service through automation, data, and product integrations.
Learn more about the best customer retention tools on the market.
These are just some places to start if you want to keep your customers longer. Want more strategies to mull over? Here are eight customer retention strategies that top companies use every day.
It's tempting to throw every retention strategy at the problem and hope something sticks. But if you're not sure what's causing churn, you'll end up wasting time on fixes that don't work. Diagnose before treating symptoms.
Why guess when you can know? With the right data, you're not just retaining users - you're building the kind of relationships that compound. Customers who stick around, refer others, and spend more over time. Dig into the data, listen to your users, and watch your retention rates climb.
