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Decoding User Churn - a Behavioural Data Science Approach

Churn is usually treated as a single number to be reduced, which is why most retention efforts miss. Customers leave for very different reasons, some rational, some habitual, some emotional, and those groups coexist inside the same customer base while needing entirely different responses. Telling them apart, predicting who is at risk, and matching the intervention to the reason is what turns retention spend into retained revenue.

Report

Decoding User Churn - a Behavioural Data Science Approach

Churn is usually treated as a single number to be reduced, which is why most retention efforts miss. Customers leave for very different reasons, some rational, some habitual, some emotional, and those groups coexist inside the same customer base while needing entirely different responses. Telling them apart, predicting who is at risk, and matching the intervention to the reason is what turns retention spend into retained revenue.

Report

Decoding User Churn - a Behavioural Data Science Approach

Churn is usually treated as a single number to be reduced, which is why most retention efforts miss. Customers leave for very different reasons, some rational, some habitual, some emotional, and those groups coexist inside the same customer base while needing entirely different responses. Telling them apart, predicting who is at risk, and matching the intervention to the reason is what turns retention spend into retained revenue.