acquisitionRetention: Acquisition-Retention Data from Chapter 5

In SMCRM: Data Sets for Statistical Methods in Customer Relationship Management by Kumar and Petersen (2012).

Description

Acquisition-Retention Data from Chapter 5

Usage

  acquisitionRetention

Format

Data frame with the following 15 variables

customer

customer number (from 1 to 500)

acquisition

1 if the prospect was acquired, 0 otherwise

duration

number of days the customer was a customer of the firm, 0 if acquisition == 0

profit

customer lifetime value (CLV) of a given customer, -(Acq_Exp) if the customer is not acquired

acq_exp

total dollars spent on trying to acquire this prospect

ret_exp

total dollars spent on trying to retain this customer

acq_exp_sq

square of the total dollars spent on trying to acquire this prospect

ret_exp_sq

square of the total dollars spent on trying to retain this customer

freq

number of purchases the customer made during that customer's lifetime with the firm, 0 if acquisition == 0

freq_sq

square of the number of purchases the customer made during that customer's lifetime with the firm

crossbuy

number of product categories the customer purchased from during that customer's lifetime with the firm, 0 if acquisition = 0

sow

Share-of-Wallet; percentage of purchases the customer makes from the given firm given the total amount of purchases across all firms in that category

industry

1 if the customer is in the B2B industry, 0 otherwise

revenue

annual sales revenue of the prospect's firm (in millions of dollar)

employees

number of employees in the prospect's firm

Examples

data(acquisitionRetention)
  str(acquisitionRetention)

Example output

'data.frame':	500 obs. of  15 variables:
 $ customer   : num  1 2 3 4 5 6 7 8 9 10 ...
 $ acquisition: num  1 1 1 0 1 1 1 1 0 0 ...
 $ duration   : num  1635 1039 1288 0 1631 ...
 $ profit     : num  6134 3524 4081 -638 5446 ...
 $ acq_exp    : num  694 460 249 638 589 ...
 $ ret_exp    : num  972 450 805 0 920 ...
 $ acq_exp_sq : num  480998 211628 62016 407644 346897 ...
 $ ret_exp_sq : num  943929 202077 648089 0 846106 ...
 $ freq       : num  6 11 21 0 2 7 15 13 0 0 ...
 $ freq_sq    : num  36 121 441 0 4 49 225 169 0 0 ...
 $ crossbuy   : num  5 6 6 0 9 4 5 5 0 0 ...
 $ sow        : num  95 22 90 0 80 48 51 23 0 0 ...
 $ industry   : num  1 0 0 0 0 1 0 1 0 1 ...
 $ revenue    : num  47.2 45.1 29.1 40.6 48.7 ...
 $ employees  : num  898 686 1423 181 631 ...

SMCRM documentation built on May 2, 2019, 2:46 p.m.