Summary method for objects of class clv.data that provides information about the estimation and possible holdout sample, and descriptive statistics of the transaction data.

# S3 method for clv.data
summary(object, ...)

# S3 method for summary.clv.data
print(x, digits = max(3L, getOption("digits") - 3L), ...)

# S3 method for clv.data.dynamic.covariates
summary(object, ...)

# S3 method for summary.clv.data.dynamic.covariates
print(x, digits = max(3L, getOption("digits") - 3L), ...)

# S3 method for clv.data.static.covariates
summary(object, ...)

# S3 method for summary.clv.data.static.covariates
print(x, digits = max(3L, getOption("digits") - 3L), ...)

Arguments

object

A CLV data object containing transactional data and potentially also contextual factors.

...

Ignored.

x

An object of class "summary.clv.data", usually, a result of a call to summary.clv.data.

digits

The number of significant digits to use when printing.

Value

This function computes and returns summary statistics of the transactional and covariates data given in object. This is a list of class summary.clv.data and contains the elements:

name

Human readable description of the type of data.

summary.clv.tim

Summary information about the stored clv.time object.

descriptives.transactions

A data.table with summary statistics of the transactions overall and in the estimation and holdout sample.

For static covariates data, the list additionally is of class summary.clv.data.static.covariates and further contains the elements:
names.cov.data.trans

Names of the covariates for the Transaction process.

names.cov.data.life

Names of the covariates for the Lifetime process.

See also

plot for how to plot a clv data object

clvdata for how to create a clv data object

SetStaticCovariates for how to add static covariates

SetDynamicCovariates for how to add dynamic covariates

Examples

# \donttest{ data("apparelTrans") clv.data.apparel <- clvdata(apparelTrans, date.format = "ymd", time.unit = "w", estimation.split = 40) # summary of transaction data and split summary(clv.data.apparel)
#> CLV Transaction Data #> #> Time unit Weeks #> Estimation length 40.0000 Weeks #> Holdout length 39.71429 Weeks #> #> Transaction Data Summary #> Estimation Holdout Total #> Number of customers - - 250 #> First Transaction in period 2005-01-03 2005-10-11 2005-01-03 #> Last Transaction in period 2005-10-10 2006-07-16 2006-07-16 #> Total # Transactions 1311 946 2257 #> Mean # Transactions per cust 5.244 8.226 9.028 #> (SD) 6.082 8.934 12.603 #> Mean Spending per Transaction 39.436 38.519 39.051 #> (SD) 42.649 59.723 50.503 #> Total Spending 51700.490 36438.640 88139.130 #> Total # zero repeaters 77 135 65 #> Percentage # zero repeaters 0.308 0.540 0.260 #> Mean Interpurchase time 7.361 5.756 9.462 #> (SD) 6.791 6.394 12.266 #>
# add contextual factors data("apparelStaticCov") clv.data.apparel.cov <- SetStaticCovariates(clv.data.apparel, data.cov.life = apparelStaticCov, names.cov.life = "Gender", data.cov.trans = apparelStaticCov, names.cov.trans = "Gender") # additional info about the covariates summary(clv.data.apparel.cov)
#> CLV Transaction Data with Static Covariates #> #> Time unit Weeks #> Estimation length 40.0000 Weeks #> Holdout length 39.71429 Weeks #> #> Transaction Data Summary #> Estimation Holdout Total #> Number of customers - - 250 #> First Transaction in period 2005-01-03 2005-10-11 2005-01-03 #> Last Transaction in period 2005-10-10 2006-07-16 2006-07-16 #> Total # Transactions 1311 946 2257 #> Mean # Transactions per cust 5.244 8.226 9.028 #> (SD) 6.082 8.934 12.603 #> Mean Spending per Transaction 39.436 38.519 39.051 #> (SD) 42.649 59.723 50.503 #> Total Spending 51700.490 36438.640 88139.130 #> Total # zero repeaters 77 135 65 #> Percentage # zero repeaters 0.308 0.540 0.260 #> Mean Interpurchase time 7.361 5.756 9.462 #> (SD) 6.791 6.394 12.266 #> #> Covariates #> Trans. Covariates Gender #> # covs 1 #> Life. Covariates Gender #> # covs 1 #>
# }