Customer health scoring for a DTC digital health product
Does anyone have experience with customer health scoring for a DTC digital health product. I am trying to determine the best approach to calculating our subscriber health score (for a digital health fitness product) particularly around reducing member churn and would love to pick someone's brain about this topic!
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- Interview consumers to learn why they renew or cancel
- If possible, quantify these factors using a required field in the cancellation workflow to collect data for Pareto analysis
- Look upstream in your process or in your consumers' behavioral data for possible factors related to churn
- Identify and collect any missing data
- Perform factor analysis to ascertain validity (covariance) of each factor
- Develop a predictive model, using a classifier such as logistic regression
Hi @kristinhaluch We recently implemented a health score. I will reach out to my our main resource who managed it and invite them to this conversation!
Hi @kristinhaluch--
In my experience, health scores for DTC are actually more accurate than B2B because the consumer alone is the decision maker. The process for calculating a data-driven health score is the same:
Logistic regression will predict the probability of churn given some set of factors X1, X2, .. Xn. A confusion matrix will give you the predict accuracy of the model.
Hope that helps!
In my experience, health scores for DTC are actually more accurate than B2B because the consumer alone is the decision maker. The process for calculating a data-driven health score is the same:
Logistic regression will predict the probability of churn given some set of factors X1, X2, .. Xn. A confusion matrix will give you the predict accuracy of the model.
Hope that helps!