It is a truth universally accepted by every CSM – “There is more to a Customer Health Score than just a red/yellow/green color code against the customers’ names.”
Instead, it’s supposed to be this amazing metric derived by a super secretive formula consisting of numerous variables that enables CS teams to assess the likelihood of an outcome for a customer. Not only should it help predict renewal/churn, but it also acts as an indicator of your customer’s growth, success, and failures and should ideally help a CSM strategize their support appropriately.
But then, why is it that CSMs are still blindsided by sudden termination notices even though they are heavily tracking customer health scores?
Let me confess! This amazing metric that’s supposed to be derived by this super secretive formula does not exist. Actually, it can’t because customer health scores are subjective. They differ from business to business. Health Scores need to be more personalized. A health score can only provide value if the following are known and understood.
Clearly defined Success Criteria:
One must define what success means to them. It can be just one dimension or a combination of a few. For example, account growth/potential, current penetration, referenceability of the customers, etc.
Parameters and variables of the Health Score
It is important that every organization identifies how they want its health score to be calculated. What are the variables they want to prioritize to get a health score that’s accurate to their goal? This stage needs the CS team to have insight into each and every variable. It needs them to be extremely selective and decisive as the variables they choose will determine their health score.
Dashboard to interpret the personalized health score
One needs to understand how to interpret each personalized health score. Just because they have those red, yellow, and green dots next to their customers is not enough. The health score range is unique to each customer, so the CS team needs to know exactly what every health score means. Because only when they know what it means can they determine the next steps to act on this knowledge.
Once these key personalizations are adopted, they can then truly leverage their customer health score. But had one general customer health score calculation method been utilized for different businesses, one can just imagine the chaos that would have come.
Hence, customer health scores, when personalized to a customer’s journey and interpreted correctly, can truly benefit a business by delivering key insights. But in a scoring metric that is this complicated and where multiple success dimensions play a key role, perhaps technology such as AI should help.