Customer churn is a vital metric for any subscription business, especially SaaS companies. It’s a measure of how many customers (sometimes referred to in sales shorthand as “logos”) do not renew at the end of their subscription. Churn can occur prior to the expiration of the subscription term, but this type of turnover is less frequent because it typically requires breaking terms of a contract. Customer churn can also be thought of as the inverse of customer retention.
There are two types of churn: revenue churn and customer churn.
Revenue churn measures the financial impact of lost customer contracts, and is usually expressed in dollar value of contracts not renewed.
There are several types of revenue churn:
Customer churn is commonly expressed as the percentage of customers who don’t renew their contracts. This type of churn focuses on the number of customers lost rather than the revenue impact. Types of customer churn include:
Churn (in all its forms) is such a critical health metric for SaaS businesses because customer acquisition costs are typically high for subscription software companies. So high, in fact, that it’s not uncommon for a vendor to not recoup its acquisition costs until several years into the contract. As a result, early churn means the company lost money on that customer. Similarly, understanding churn is a prerequisite to understanding customer lifetime value, which is another foundational metric for SaaS businesses.
To help identify potential churn before it happens, many companies are turning to product analytics. Restaurant365, a restaurant management software, measures usage across its platform and if an account goes dark or exhibits abnormally low usage, customer success reaches out to find out why and proactively intervene.
Beyond these basic distinctions, churn can also be viewed through more nuanced lenses:
Preventable churn: Customers who leave due to dissatisfaction, poor customer experience, or lack of engagement. Preventable churn can often be mitigated through targeted retention efforts at unhappy or inactive users:
Structural churn: Customers who churn due to reasons beyond the company’s control, such as going out of business or being acquired by another company.
By recognizing the specific reasons behind churn, companies can implement targeted measures to reduce preventable churn and better understand structural churn’s inevitable impact.
Calculating customer churn rate is more complicated than meets the eye: Should it include free trial users? Month-to-month contracts? Should it isolate only customers up for renewal? As a result, SaaS companies vary greatly in the way they answer a question as seemingly direct as, “How many of your customers didn’t renew in a given period of time?”
Because there are dozens of competing formulas for calculating churn, what matters more than the formula(s) a company chooses is that it benchmarks itself consistently. Churn is a moving-target KPI. It can be affected by seasonality, product changes, competitive factors, pricing expectations, customer support, and even PR events. Changing one’s churn calculation regularly will impede the ability to understand what’s causing a company to lose customers and make changes to its business, which, in the end, is why one tracks the metric in the first place.
Not all customer churn is preventable. If a company goes out of business or gets acquired, there’s little chance of saving that customer. This is often referred to as “structural churn.” The opposite of structural churn is preventable churn, and in these cases, companies and decision-makers tend to look at a few consistent criteria when deciding whether or not to renew a product or service. Questions they’re likely to ask themselves include:
Predicting customer churn requires two things: a thorough understanding of your customers’ interactions with your brand, and key operational metrics like product usage data. By unifying your data, businesses can identify early indicators of churn and develop proactive strategies to retain customers.
To accurately predict churn, creating a predictive model is crucial. This involves integrating product data (like user stickiness and feature adoption) with experiential data (like Net Promoter Scores and user feedback). By analyzing these combined datasets, the model can assess the likelihood of churn for each customer, allowing businesses to act preemptively.
Product experience platforms like Pendo make understanding your customer health dramatically easier. Usage data, feedback, session replays, and more help you understand and segment users to pinpoint at-risk customers and craft personalized retention strategies.
With your product’s insights, companies can foresee potential churn and implement timely, targeted measures to improve customer loyalty and retention.
Pendo’s data science team wanted to see if we could predict whether a customer would churn, renew flat, or grow its contract with only PES. We found that PES is strongly correlated with customer retention: Months before contract renewal, accounts with the highest PES were most likely to renew and expand, while accounts with the lowest PES were most likely to churn.
Reducing customer churn involves not just rescuing at-risk customers but proactively creating a positive experience throughout their journey. Here are key strategies to help reduce churn and keep your customers engaged:
Enhance your product and customer experiences
Educate and empower customers
Reward loyalty to incentivize repeat business
Show appreciation for your high-value customers
Listen and act on implicit and explicit feedback
An all-in-one product experience platform, Pendo gives product leaders the tools and data to understand and act on customer satisfaction.
By integrating your product’s analytics, in-app guides, feedback capture, roadmapping, and session replay data, you can get a 360-view into customer health, proactively reduce churn, and improve your bottom line.