Account health score is a hot topic in Customer Success circles. With more data available than ever to teams across your organization, building a churn risk model allows your Customer Success Managers to quickly identify and proactively engage at-risk accounts.
What is churn in customer success?
Churn is the percentage of customers who stop using your product or service within a given period of time.
Churn mitigation can oftentimes be thought of as a reactive motion: CSMs kick into high gear when things go awry. But with a gold mine of your customers’ product usage data, billing history and support tickets in your data warehouse, you can easily flip the script to make this a proactive motion and engage accounts before reaching an inflection point.
By implementing churn risk flags, you can:
Many startups develop sophisticated AI models for health scoring. But the reality is that you can start with a basic model including only the key factors that contribute to churn.
For example, one of our early stage SaaS clients knew that “customers are 50% more likely to churn when their product usage is lower than 50% of the license limit and the customer has late payments”. Their data team created a simple model from this logic and passed it to their CS tool. Inside the CS tool, the team created automated playbooks for their CSMs to reach out.
With a proactive churn reduction strategy enabled by the data warehouse and Census data activation, your Customer Success team will be equipped to turn things around before churn is inevitable.