ParetoNBDModel.expected_purchases_new_customer

ParetoNBDModel.expected_purchases_new_customer(data=None, *, t=None)

Compute the expected number of purchases for a new customer across t time periods.

In a model with covariates, if data is not specified, the dataset used for fitting will be used and a prediction will be computed for a new customer with each set of covariates. This is not a conditional prediction for observed customers!

Adapted from equation (27) in Bruce Hardie’s notes [1], and lifetimes package: CamDavidsonPilon/lifetimes

Parameters:

dataDataFrame, optional

Dataframe containing the following columns:

• customer_id: unique customer identifier

• t: Optional column for t parametrization.

• All covariate columns specified when model was initialized.

If not provided, predictions will be ran with data used to fit model.

tarray_like, optional

Number of time periods over which to estimate purchases. Not required if data Dataframe contains a t column.

References

[1]

Fader, Peter & G. S. Hardie, Bruce (2005). “A Note on Deriving the Pareto/NBD Model and Related Expressions.” http://brucehardie.com/notes/009/pareto_nbd_derivations_2005-11-05.pdf