Title: | Data Sets for Statistical Methods in Customer Relationship Management by Kumar and Petersen (2012). |
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Description: | Data Sets for Kumar and Petersen (2012). Statistical Methods in Customer Relationship Management, Wiley: New York. |
Authors: | Tobias Verbeke, based on datasets provided on the book's website |
Maintainer: | Tobias Verbeke <[email protected]> |
License: | GPL-3 |
Version: | 0.0-3 |
Built: | 2024-11-22 05:21:21 UTC |
Source: | https://github.com/cran/SMCRM |
Acquisition-Retention Data from Chapter 5
acquisitionRetention
acquisitionRetention
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
data(acquisitionRetention) str(acquisitionRetention)
data(acquisitionRetention) str(acquisitionRetention)
Customer Acquisition Data from Chapter 3
customerAcquisition
customerAcquisition
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
data(customerAcquisition) str(customerAcquisition)
data(customerAcquisition) str(customerAcquisition)
Customer Churn Data from Chapter 6
customerChurn
customerChurn
Data frame with the following 11 variables
customer
customer number (from 1 to 500)
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
avg_ret_exp
average number of dollars spent on marketing efforts to try and retain that customer per month
avg_ret_exp_sq
square of the average number of dollars spent on marketing efforts to try and retain that customer per month
total_crossbuy
total number of categories the customer has purchased during the customer's lifetime
total_freq
total number of purchase occasions the customer had with the firm in the customer's lifetime
total_freq_sq
square of the total number of purchase occasions the customer had with the firm in the customer's lifetime
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
data(customerChurn) str(customerChurn)
data(customerChurn) str(customerChurn)
Demographics Data for Customer Retention (Chapter 4)
customerRetentionDemographics
customerRetentionDemographics
Data frame with the following 8 variables
customer
customer number (from 1 to 500)
gender
1 if the customer is male, 0 if the customer is female
married
1 if the customer is married, 0 if the customer is not married
income
1 if income < \$30,000 2 if \$30,001 < income < \$45,000 3 if \$45,001 < income < \$60,000 4 if \$60,001 < income < \$75,000 5 if \$75,001 < income < \$90,000 6 if income > \$90,001
first_purchase
value of the first purchase made by the customer in quarter 1
loyalty
1 if the customer is a member of the loyalty program, 0 if not
sow
share-of-wallet; the percentage of purchases the customer makes from the given firm given the total amount of purchases across all firms in that category
clv
discounted value of all expected future profits, or customer lifetime value
data(customerRetentionDemographics) str(customerRetentionDemographics)
data(customerRetentionDemographics) str(customerRetentionDemographics)
Lifetime Duration Data for Customer Retention (Chapter 4)
customerRetentionLifetimeDuration
customerRetentionLifetimeDuration
Data frame with the following 8 variables
customer
customer number (from 1 to 500)
x
The number of transactions by a given customer over all time periods. Here we assume that it is the sum of the variable Purchase where customers at most made 1 purchase per quarter.
tx
time of the last transaction, i.e. the last quarter where purchase == 1
T
total time between the first purchase and the end of the observation window, i.e. 12 quarters for all customers
customerRetentionTransactions
data(customerRetentionLifetimeDuration) str(customerRetentionLifetimeDuration)
data(customerRetentionLifetimeDuration) str(customerRetentionLifetimeDuration)
Transactions Data for Customer Retention (Chapter 4)
customerRetentionTransactions
customerRetentionTransactions
Data frame with the following 7 variables
customer
customer number (from 1 to 500)
quarter
quarter (from 1 to 12) where the transactions occurred
purchase
1 when the customer purchased in the given quarter and 0 if no purchase occurred in that quarter
order_quantity
dollar value of the purchases in the given quarter
crossby
number of different categories purchased in a given quarter
ret_expense
dollars spent on marketing efforts to try and retain that customer in the given quarter
ret_expense_sq
square of dollars spent on marketing efforts to try and retain that customer in the given quarter
data(customerRetentionTransactions) str(customerRetentionTransactions)
data(customerRetentionTransactions) str(customerRetentionTransactions)
Customer Win-Back from Chapter 7
customerWinBack
customerWinBack
Data frame with the following 10 variables
customer
customer number (from 1 to 500)
reacquire
1 if the customer is reacquired, 0 if not
duration_2
time in days of the customer's second lifecycle with the company, 0 if not reacquired
slcv
CLV of the customer in the second lifecycle
duration_1
time in days of the customer's first lifecycle with the company
offer
value of the offer provided to the customer for reacquisition
duration_lapse
time in days since the customer was lost to when the offer to reacquire was given
price_change
increase (or decrease) in price of the subscription the customer received between the first lifecycle and the second lifecycle, 0 if not reacquired
gender
1 if male, 0 if female
age
age in years of the customer at the time of the attempt to reacquire
data(customerWinBack) str(customerWinBack)
data(customerWinBack) str(customerWinBack)