Churn is a revenue killer. You already spent the S&M cost to acquire that customer and then they churn cutting off a source of cheap, recurring revenue. A high churn rate is also a red flag to potential buyers; it alerts a buyer that at least some aspects of your product fall short of expectations and work needs to be done back at the drawing board to get the product/market fit and value proposition aligned.
To some extent, however, churn will occur. It is your responsibility to put in place a churn identification plan as a predictive tool. By having a system to predict customers who are at risk of churning, you can proactively engage them rather than waiting to be reactive.
With proactive engagement, the goal is to reduce churn.
The Impact: Early identification of high churn risk customers gives your team the opportunity to proactively address value shortfalls and reduce churn rates.
The Goal: Create a system for identifying churn risk and a process for addressing customers who are then identified as churn risk.
How can Golden Section Assist?
Steps
- Meeting 1. Vision and Hypotheses
- Set vision and specific objectives for Churn Identification
- Preview work plan, timeline and needs from stakeholders.
- Brainstorm potential churn predictors. Generally, churn can follow from issues around expectation management, issues with product/use case fit, the loss of a key user, budget or internal changes, competition, or negative customer experiences. To organize your search for the factors that predict churn for your customers, we recommend beginning at a high- level. Using your team's expertise, make hypotheses of the individual factors within each of the following buckets that may predict churn: subscription details, use, support and customer satisfaction.
- Identify at least 10 churn predictor hypotheses.
- Depending on the time and amount of churned customers you have, you may explore more churn hypotheses. The more churned customers you have, and therefore data, the more hypotheses you can include. You will need the number of churned customers to significantly outsize the number of churn hypotheses so that meaningful relationships can be established.
- Assign people responsible for collecting and analyzing data.
- Exploration
- Collect the list of churned customers.
- Collect data indicators for each churn hypothesis.
- Analysis
- Analyze relevant case data from past churned customers to determine any relationships between churned customers and churn hypotheses.
- This is not a rigorous, scientific data review. Rather, you are looking for relationships between variables and quality.
- The relationship does not need to be linear; in other words, as a variable increases, the likelihood of churn does not necessarily need to increase.
- Rather, look for clusters (i.e. all churned customers had Pro subscription plans) to guide your analysis. Support clusters you find by checking to see whether a relationship holds (i.e. are there Pro customers who don't churn?)
- Determine whether each churn hypothesis has a neutral or positive effect on churn.
- Finish the analysis with a final assessment for each factor. This one- line, definitive statement clearly indicates the impact each factor has on customer value.
- Meeting 2. Gut Check and Process Generation.
- After a period to process the information sent, reconvene to discuss the findings.
- Do the churn predictors sit well with the team?
- Are these predictors leading or lagging indicators? Is there a more fundamental predictor you should explore?
- Formally identify the churn predictors you would like your team to use.
- Using these churn predictors, generate a process to proactively identify customers who constitute a churn risk and then engage them to minimize the churn risk.
- Process checks: be sure to include specific, measurable indicators to show whether the process is working. For example, how does the churn rate track over time? What about among the cohorts with risk factors? Is there improvement or did we miss the churn indicators? Does something else need to be tracked or product/process improvements made?
- Codification. Gather your conclusions and process in a document to store and communicate with the appropriate team members.
Questions this play answers
What signals indicate a customer might churn?
Churn is a revenue killer. You already spent the S&M cost to acquire that customer and then they churn cutting off a source of cheap, recurring revenue. A high churn rate is also a red flag to potential buyers; it alerts a buyer that at least some aspects of your product fall short of expectations and work needs to be done back at the drawing board to get the product/market fit and value proposition aligned.
How do I build a customer health score?
Build a systematic process to identify at-risk customers before they churn—analyzing usage patterns, engagement signals, and health scores to trigger retention interventions.
When should I escalate at-risk accounts?
Build a systematic process to identify at-risk customers before they churn—analyzing usage patterns, engagement signals, and health scores to trigger retention interventions.
How do I reduce customer churn?
Churn is a revenue killer. You already spent the S&M cost to acquire that customer and then they churn cutting off a source of cheap, recurring revenue. A high churn rate is also a red flag to potential buyers; it alerts a buyer that at least some aspects of your product fall short of expectations and work needs to be done back at the drawing board to get the product/market fit and value proposition aligned.
What's a healthy churn rate by customer segment?
Churn is a revenue killer. You already spent the S&M cost to acquire that customer and then they churn cutting off a source of cheap, recurring revenue. A high churn rate is also a red flag to potential buyers; it alerts a buyer that at least some aspects of your product fall short of expectations and work needs to be done back at the drawing board to get the product/market fit and value proposition aligned.