What is customer churn analysis?
Customer churn analysis is the process of identifying when and why customers stop using a product or service, and determining patterns that can predict future churn. By analyzing customer behavior and interaction data, product managers can uncover the root causes of churn and develop strategies to retain users.
Understanding churn at scale requires large sets of customer data to reveal trends and pain points that might not be visible on an individual level. This is where data becomes indispensable—tracking user engagement across touchpoints helps create a comprehensive view of the customer journey.
AI plays a critical role in sifting through these vast amounts of churn data, uncovering hidden patterns, and generating insights that enable product managers to make data-backed decisions. With AI-driven tools like Sprig’s Surveys and Replays, product managers can better understand user frustrations to predict churn more effectively and focus on retaining high-value customers at scale.
How do you calculate customer churn?
The basic formula for calculating churn is:
Churn Rate = (Number of Customers Lost During a Period) / (Total Number of Customers at the Start of the Period) × 100
For example, if you started the month with 1,000 customers and lost 50, your churn rate would be:
(50 / 1,000) × 100 = 5% churn rate
Another common variation is calculating revenue churn, especially for businesses that rely on subscription models:
Revenue Churn = (Lost Revenue from Churned Customers) / (Total Revenue at the Start of the Period) × 100
This formula accounts for not just the number of customers but also the potential impact of losing higher-value customers.
Median churn rates by industry
Understanding when and why customers churn is just as important as calculating churn itself.
- Early churn—when customers leave shortly after joining—often indicates a mismatch between customer expectations and the product experience.
- Later churn, on the other hand, may suggest dissatisfaction with long-term value, features (or updates to functionality), customer support, or even pricing.
Identifying whether customers are churning early or later in their journey helps product managers pinpoint the stages of the experience that need attention to improve customer retention. For example: Early churn may require optimizing onboarding processes, while later churn might call for better feature engagement or customer support strategies.
Average churn rate benchmarks:
For context, the average churn rates vary significantly by industry:
- SaaS (Software as a Service): Typically between 5-8% annually for larger, mid-market businesses. However, startups may experience rates as high as 10-15%.
- Mobile apps: Can see churn rates upwards of 70-80% within the first 90 days of download, especially for freemium models.
- E-commerce: Monthly churn often falls between 3-5%.
For mid-market SaaS businesses, an acceptable churn rate is generally around 5%, but product managers should aim for lower—closer to 3%—as they grow and mature. Lower churn rates indicate stronger customer retention, which is essential for long-term success in competitive sectors like SaaS.
When they understand these benchmarks and where churn is happening, product managers can prioritize efforts to reduce churn and maximize customer lifetime value.
Typical causes of customer churn
Customer churn is typically the result of friction points within the user experience on websites and mobile apps. Left unchecked, they can damage customer relationships, and lead to higher future customer acquisition costs by driving down things like your net promoter score (NPS).
Identifying and resolving these issues is crucial for product managers to reduce customer churn rates and drive customer loyalty, and Sprig’s analytics tools can provide clarity by uncovering hidden behavioral patterns across your whole customer base.
Below are some of the most common causes of churn (and how you can use Sprig’s tools to help diagnose and address them).
1. Unclear or misleading messaging on key pages
When users land on a page with unclear messaging, they may feel confused about the product's value or purpose, leading to a high churn rate.
For example, a visitor arriving at a pricing page may expect to see straightforward options but instead encounters vague descriptions that fail to communicate the value behind each tier. This can lead to quick exits or bounce rates.
2. Confusing or unintuitive navigation paths
Poorly designed navigation often results in poor customer experience—like users taking unintended actions, or worse, leaving your site or app altogether. This leads to confusion for new customers and a higher risk of churning.
For websites, this could mean repeated backtracking or clicking on the same elements without success. In apps, users may abandon the session out of frustration.
3. Ineffective or missing call-to-action elements
A well-designed call-to-action (CTA) is essential for converting visitors into customers. When CTAs are poorly placed, lack contrast, or are too generic, users may abandon the flow without taking the desired action, whether it’s completing a form or making a purchase.
4. Overwhelming or cluttered page design
Too much information, overly complex design, or competing elements can overwhelm users and lead to low customer satisfaction—or worse, lost customers. A cluttered interface makes it difficult for users to focus on the primary action they’re supposed to take, and this friction can result in high exit rates.
5. Lack of engagement due to irrelevant content or features
When users aren’t met with content or features relevant to their needs, they’re more likely to churn. Personalization is critical in retaining existing customers, and a lack of relevant experiences can drive them toward canceling or—oh no—competitors who better meet their expectations.
When you diagnose these specific causes of churn with Sprig’s tools, you can better understand where friction occurs—and proactively address issues that are killing your retention rates across your whole user lifecycle.
Figure out why customers are churning in 6 steps
As we’ve covered, when it comes to solving churn, the key is understanding what’s reducing customer engagement.
Fortunately, tools like session replays, heatmaps, and surveys can make it easier to pinpoint the problem areas, zero in on key demographics, identify at-risk customers, and work on addressing them.
This step-by-step guide will walk you through how to use these tools to get clear insights into why your subscribers are leaving—and how to stop them before they go.
Step 1: Understand user behavior to identify friction points
First things first: You need to know exactly where your users are hitting roadblocks. Session replays let you watch real user journeys and spot the moments they struggle, drop off, or get frustrated. Maybe they're stuck on the checkout page, or perhaps they're getting lost trying to navigate to key product features.
Being able to see where things go wrong makes it easier to identify those friction points and uncover the root causes of churn.
With Sprig Replays, you can scale your cohort analysis by defining triggers for session replays based on specific types of customers (demographics) or actions—then, Sprig’s AI analysis can quickly categorize your datasets by theme, helping you see (and understand) what’s going on faster, and share your results with your team.
Results page of a Replay study in Sprig — Sprig AI instantly analyzes and groups session clips into themes to uncover patterns in your users' behavior.
Step 2: Pinpoint areas of low engagement or confusion
Heatmaps are your next best friend. They give you a visual breakdown of where people are actually interacting with your site or app, and more importantly, where they’re not.
This can help uncover areas that users are ignoring or where they’re getting confused. Maybe an important CTA isn’t getting clicked or users keep bouncing from a key feature page. These are key metrics for understanding customer engagement.
For example, frequent rage clicks or mouse movements associated with pricing buttons may be signs that users are unsure or frustrated by unclear messaging. Sprig’s Surveys and customer feedback tools can be deployed to collect immediate data when a user exits the page, helping you refine content to better match their expectations.
Again, Sprig Heatmaps help you take it further—Sprig’s AI-generated insights help you both scale and hasten your approach to addressing user experience issues, and empower your customer success team to better collaborate with developers to resolve user problems.
The results page of a Heatmap study in Sprig — including the AI Summary and heatmap, scrollmap, and clickmap data.
Step 3: Collect direct feedback to uncover user concerns
Session replays and heatmaps show you what’s happening, but feedback surveys tell you why.
By gathering direct feedback through well-timed, targeted surveys based on customer segmentation, you can understand users’ specific pain points and expectations straight from the source.
For example, if users consistently exit at a certain point in the funnel, you can trigger a Sprig survey when the user exits. A quick survey can help uncover what’s not clicking for them—whether it’s pricing, unclear instructions, or missing features.
Survey results page in Sprig — Sprig AI analyzes all responses to generate a study summary and key takeaways.
Step 4: Monitor ongoing user sentiment for early warning signs
User sentiment doesn’t stay static. It's important to stay in touch with how your users feel as they continue to engage with your product.
Regular check-ins through surveys help you track evolving sentiments and catch any early warning signs of dissatisfaction. If you wait too long, the feedback you’re getting might come too late—by then, they’ve already churned.
By segmenting your customers according to demographics, you can check in with loyal customers at regular intervals using Sprig’s ever-present feedback widget, and use that feedback to gauge customer sentiment over a given period of time—allowing you to understand broader trends.
Sprig AI automatically summarizes open-text Feedback study responses to give you actionable learnings and product optimizations.
Step 5: Analyze data patterns to derive actionable insights
Once you’ve collected all this data, it’s time to make sense of it.
Sprig’s suite of AI tools can analyze user behavior at scale, helping you spot patterns and anomalies that might otherwise get missed. This is where AI-driven insights can be a game changer, processing huge amounts of information to give you clear, actionable insights that can inform predictive modeling, reduce all types of churn, and shape your next (big) moves.
Step 6: Optimize the user experience based on data-driven recommendations
Now comes the fun part—optimizing your product! Using AI recommendations (like Sprig's AI Explorer), you can refine the user experience to address specific issues.
Whether it’s simplifying navigation, tweaking a call to action, or reworking your onboarding flow, these AI-powered suggestions will help you make data-driven decisions that keep users engaged and loyal.
Scale your customer churn analysis, and reduce churn rates faster with Sprig’s industry leading tools
Ok, now for the big pitch! (We warned you! But seriously—stick around.) Sprig enables your team to not only see and understand the what and the why more quickly, but also collaborate and iterate more effectively with your whole team.
Sprig’s suite of AI-infused tools capture the data you need to identify root causes of customer churn, while also enabling smooth cross-functional collaboration by allowing your teams to easily zero in on key metrics and share their findings.
Get started with Sprig today to speed iteration and improve functionality faster while always keeping your customers at the center.