ShiftedBetaGeoModel.expected_retention_rate

ShiftedBetaGeoModel.expected_retention_rate(data=None, *, future_t=None)

Compute expected retention rate for each customer.

This is the percentage of customers who were active in the previous time period and are still active in the current period. Retention rates are expected to increase over time.

The data parameter is only required for out-of-sample customers.

Adapted from equation (8) in [1].

Parameters:

future_tint, array_like

Number of time periods in the future to predict retention rate.

dataDataFrame

Optional dataframe containing the following columns: * customer_id: Unique customer identifier * T: Number of time periods customer has been active * cohort: Customer cohort label * Covariate columns specified in dropout_covariate_cols (if using covariates)

References

[1]

Fader, P. S., & Hardie, B. G. (2007). “How to project customer retention.” Journal of Interactive Marketing, 21(1), 76-90. https://faculty.wharton.upenn.edu/wp-content/uploads/2012/04/Fader_hardie_jim_07.pdf