How to use churn data to build stickier products

Note: All opinions expressed are my own and not affiliated to my current or past employers.

Picture this: You just launched a cool new cloud-native product and your product’s top line (gross revenue) and bottom line (net profit) show significant promise. Before you rush to report on your product’s perceived success to leadership, stop and take a closer look at how sticky your product is. 

In my experience leading a portfolio of B2B cloud-native products, I learnt this lesson first-hand when a product I had launched hit impressive early revenue targets. We were ready to celebrate, but a deeper look at the month over month churn data showed that we were losing customers almost as fast as we were gaining them. That moment taught me that stickiness—not just growth—is what determines a product’s long-term success.

What is product churn?

To measure the true success of a product, there are two product stickiness metrics that product managers should keep an eye on: customer retention rate and churn rate. The customer retention rate measures how successful the product has been to retain its customer base over a given period (making customers stick to the product). The churn rate measures the percentage of customers lost (through product uninstallation or termination of subscription) over a defined period.

Why is churn concerning for cloud products?

Churn negatively impacts every product, but what I have observed is that the consequences of churn are amplified more in the world of cloud product management for a few reasons. 

First, most cloud products—including SaaS, PaaS, or IaaS—operate on a pay-as-you-go usage model. With no contractual obligations holding them back, customers can exit anytime they feel a cloud product falls short of their needs, leading to unpredictable swings in monthly adoption and revenue growth metrics. 

Second, it takes considerable time and investment in customer acquisition cost (CAC) to onboard B2B customers as compared to the B2C sector, resulting in a longer sales cycle. For instance, when I led customer growth for a 0-to-1 cloud automation product, I spent several weeks training our field sales teams on product messaging, leading customer demos with technical and business executives, and guiding sign-off from multiple decision-makers in the customer organization to approve the product for use. Churn in such B2B cloud products not only reduces revenue predictability but also wipes out the value of extended sales cycles and go to market efforts—making growth far more expensive to sustain.

Third, the rise of multi-cloud environments has lowered switching costs and increased competitive choices for customers. This increases the risk of churn, as customer loyalty is no longer secured by vendor lock-in but earned continuously through differentiated value and consistent product improvement.

The antidote - Using churn data to beat churn:

At the outset, churn rate may seem to be beyond the scope of what a product manager can control, and they should probably let bygones be bygones. But here’s is a little secret I have learnt – the product churn data provides a wealth of information into why customers stopped using the product and can be vital to making your product better and winning back customers. Here are five actions you can take to handle product churn.

Collect feedback on problem areas through customer exit surveys and interviews:

You can configure the product to display an exit survey before customers cancel a subscription or uninstall your product, to seek feedback on problem areas within the product’s end-to-end experience that influenced them to leave the product. You can also set up exit interviews with churned customers to deep dive on reasons for the churn. To organize feedback collection, allow customers to choose from multiple categories of ‘problem areas’ across the product’s user experience and provide additional feedback in a free text field. Here is an example of how the ‘problem areas’ field could look like:

I’m uninstalling the product because:

• Product setup was difficult 
• Pricing is too high
• Upgrade process was poor
• Too many ads
• Not accessible for my special needs
• Too slow 
• Just need it for one-time/ad-hoc use
• Poor product support
• Does not fit my business/personal needs
• Does not show relevant content or hallucinates (for AI products)
• My friends and family are on a different product (network effect)
• Promotes hate speech or bias
• Search experience is poor
• Have concerns with the product’s security and data privacy
• Better alternative available

When I introduced exit surveys for a cloud FinOps product I was leading, I discovered that customers weren’t leaving because it did not fit their business needs (as I had initially assumed) but because setup was confusing. This meant that many customers uninstalled the product even before experiencing the product’s core value. That insight made me completely revamp the product deployment experience and user guides with my engineering team, which significantly improved customer retention. 

Analyze churn data from a ‘10,000-foot view’ 

Identify the descending order of problem areas by analyzing the aggregated data from interviews and surveys with churned customers. You can further correlate this with their product spend history in the last 6 months or 1 year and extrapolate it, to quantify the future revenue potential that is lost, owing to each problem area. For example, if 5 customers who spent $1000 each on your product in the last year, chose to uninstall the product due to poor product support, the projected (1 year) lost revenue potential would be $5000. If a customer had chosen multiple problem areas, you could evenly split their last year’s spend across the selected problem areas, so that you don’t double count lost revenue. 

In one churn analysis for a cloud security product, when I overlaid the churn data with customer spend history, I realized that even though only a handful of customers stopped using the product, they represented some of our highest-value accounts. Quantifying the lost revenue opportunity helped me reframe the priority of the problem areas to leadership and turn it into a strategic investment for the product.

Inspect your product from a ‘1-foot view’

Now that you have identified the high-priority problem areas (pick the top 5), you will need to deeply inspect your product to understand how you can improve the customer experience. For example, to improve the product setup experience, you can introspect ways to reduce/automate the number of steps, implement interactive visual mechanisms to guide customers on setup progress, or provide better documentation on prerequisites/dependencies. Lead collaborative sessions with your UX, engineering, support, data science, and related teams to identify ways to bridge the gaps in the problem areas. 

Invest in product improvements

You can now weave your product magic by incorporating the customer feedback to enhance your product! You will need to prioritize the identified improvements across the top problem areas, create product backlog items with acceptance criteria, size it with your engineering team, and update your product roadmap to stagger the release of the prioritized improvements, and conduct A/B testing for your planned features to measure the reduction in churn rate, before launching the updates to your product. 

For instance, based on churn insights for a cloud monitoring product, I prioritized onboarding automation by offering fewer simplified deployment options for various customer setup scenarios instead of one long deployment experience and delivered a guided setup experience with contextual prompts for each option. Within one quarter, I saw a double-digit drop in churn, proving that targeted product improvements directly linked to churn data could move the needle on retention.

Renew and strengthen customer relationships

After you launch a revamped version of your product to address specific problem areas, try reconnecting with churned customers to show them that you listened to their feedback, acted on it, and encourage them to reconsider using the product – the conversion rate for returning customers may surprise you.

Wrapping up

Customer retention and churn rates are Yin and Yang forces that can make or break a product, with the end goal to achieve a low churn rate and high retention rate. Ignoring churn and solely focusing on product growth will lead to a ‘leaky bucket’ scenario, where you spend time and effort to acquire customers but fail to retain them. In my product experience, correlating churn feedback to revenue impact enabled me to prioritize roadmap investments and realign product direction around customer needs, ultimately winning back key accounts. By proactively addressing churn with early, data-driven insights, you can turn retention into a powerful engine for sustainable growth.