mbgcnbd.PAlive: (M)BG/CNBD-k P(alive)

In BTYDplus: Probabilistic Models for Assessing and Predicting your Customer Base

Description

Uses (M)BG/CNBD-k model parameters and a customer's past transaction behavior to return the probability that they are still alive at the end of the calibration period.

Usage

mbgcnbd.PAlive(params, x, t.x, T.cal)

bgcnbd.PAlive(params, x, t.x, T.cal)

Arguments

params	A vector with model parameters k, r, alpha, a and b, in that order.
x	Number of repeat transactions in the calibration period T.cal, or a vector of calibration period frequencies.
t.x	Recency, i.e. length between first and last transaction during calibration period.
T.cal	Length of calibration period, or a vector of calibration period lengths.

Value

Probability that the customer is still alive at the end of the calibration period.

References

(M)BG/CNBD-k: Reutterer, T., Platzer, M., & Schroeder, N. (2020). Leveraging purchase regularity for predicting customer behavior the easy way. International Journal of Research in Marketing. doi: 10.1016/j.ijresmar.2020.09.002

Examples

## Not run: 
data("groceryElog")
cbs <- elog2cbs(groceryElog)
params <- mbgcnbd.EstimateParameters(cbs)
palive <- mbgcnbd.PAlive(params, cbs$x, cbs$t.x, cbs$T.cal)
head(palive) # Probability of being alive for first 6 customers
mean(palive) # Estimated share of customers to be still alive

## End(Not run)

Example output

[1] 0.04232571 0.52713148 0.93543151 0.04232571 0.86830898 0.96348392
[1] 0.2557294

BTYDplus documentation built on Jan. 21, 2021, 5:10 p.m.