ModifiedBetaGeoModel.expected_purchases#

ModifiedBetaGeoModel.expected_purchases(data=None, *, future_t=None)[source]#

Compute the expected number of future purchases across future_t time periods given recency, frequency, and T for each customer.

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

Adapted from equation (6) in [1], and the legacy lifetimes library: CamDavidsonPilon/lifetimes

Parameters:
future_tint, array_like

Number of time periods to predict expected purchases.

dataDataFrame

Optional dataframe containing the following columns:

  • customer_id: Unique customer identifier

  • frequency: Number of repeat purchases

  • recency: Time between the first and the last purchase

  • T: Time between first purchase and end of observation period; model assumptions require T >= recency

References

[1]

Batislam, E.P., M. Denizel, A. Filiztekin (2007),

“Empirical validation and comparison of models for customer base analysis,” International Journal of Research in Marketing, 24 (3), 201-209. https://works.bepress.com/meltem-denizel/2/download/