customerAcquisition: Customer Acquisition Data from Chapter 3

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

Description

Customer Acquisition Data from Chapter 3

Usage

  customerAcquisition

Format

Data frame with the following 17 variables

customer

customer number (from 1 to 500)

acquisition

1 if the prospect was acquired, 0 otherwise

first_purchase

dollar value of the first purchase (0 if the customer was not acquired)

clv

the predicted customer lifetime value score. It is 0 if the prospect was not acquired or has already churned from the firm.

duration

time in days that the acquired prospect has been or was a customer, right-censored at 730 days

censor

1 if the customer was still a customer at the end of the observation window, 0 otherwise

acq_expense

dollars spent on marketing efforts to try and acquire that prospect

acq_expense_sq

square of dollars spent on marketing efforts to try and acquire that prospect

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

ret_expense

dollars spent on marketing efforts to try and retain that customer

ret_expense_sq

square of dollars spent on marketing efforts to try and retain that customer

crossbuy

the number of categories the customer has purchased

frequency

the number of times the customer purchased during the observation window

frequency_sq

the square of the number of times the customer purchased during the observation window

Examples

data(customerAcquisition)
  str(customerAcquisition)

Example output

'data.frame':	500 obs. of  16 variables:
 $ customer      : num  1 2 3 4 5 6 7 8 9 10 ...
 $ acquisition   : num  1 0 0 1 1 0 0 0 1 1 ...
 $ first_purchase: num  434 0 0 226 363 ...
 $ clv           : num  0 0 0 5.73 0 ...
 $ duration      : num  384 0 0 730 579 0 0 0 730 730 ...
 $ censor        : num  0 0 0 1 0 0 0 0 1 1 ...
 $ acq_expense   : num  760 148 253 610 672 ...
 $ acq_expense_sq: num  578147 21815 63787 371771 452068 ...
 $ industry      : num  1 1 1 1 1 0 0 0 1 1 ...
 $ revenue       : num  30.2 39.8 54.9 45.8 69 ...
 $ employees     : num  1240 166 1016 122 313 ...
 $ ret_expense   : num  2310 0 0 2193 801 ...
 $ ret_expense_sq: num  5335130 0 0 4807451 641825 ...
 $ crossbuy      : num  5 0 0 2 4 0 0 0 1 1 ...
 $ frequency     : num  2 0 0 12 7 0 0 0 11 14 ...
 $ frequency_sq  : num  4 0 0 144 49 0 0 0 121 196 ...

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