NEWS.md

In CLVTools: Tools for Customer Lifetime Value Estimation

CLVTools 0.10.0

NEW FEATURES

• We add an interface to specify models using a formula notation (latentAttrition() and spending())
• New method to plot customer's transaction timings (plot.clv.data(which='timings'))
• Draw diagnostic plots of multiple models in single plot (plot(other.models=list(), label=c()))
• MUCH faster fitting for the Pareto/NBD with time-varying covariates because we implemented the LL in Rcpp

CLVTools 0.9.0

NEW FEATURES

• Three new diagnostic plots for transaction data to analyse frequency, spending and interpurchase time
• New diagnostic plot for fitted transaction models (PMF plot)
• New function to calculate the probability mass function of selected models
• Calculate summary statistics only for the transaction data of selected customers
• Canonical transformation from data.frame/data.table to transaction data object and vice-versa
• Canonical subset for the data stored in the transaction data object
• Pareto/NBD DERT: Improved numerical stability

CLVTools 0.8.1

BUG FIXES

• Fix importing issue after package lubridate does no longer use Rcpp

CLVTools 0.8.0

NEW FEATURES

• Partially refactor the LL of the extended Pareto/NBD in Rcpp with code kindly donated by Elliot Shin Oblander
• Improved documentation

BUG FIXES

• Optimization methods nlm and nlminb can now be used. Thanks to Elliot Shin Oblander for reporting

CLVTools 0.7.0

NEW FEATURES

• Refactor the Gamma-Gamma (GG) model to predict mean spending per transaction into an independent model
• The prediction for transaction models can now be combined with separately fit spending models
• Write the unconditional expectation functions in Rcpp for faster plotting (Pareto/NBD and Beta-Geometric/NBD)
• Improved documentation and walkthrough

BUG FIXES

• Pareto/NBD log-likelihood: For the case Tcal = t.x and for the case alpha == beta
• Static or dynamic covariates with syntactically invalid names (spaces, start with numbers, etc) could not be fit

CLVTools 0.6.0

NEW FEATURES

• Beta-Geometric/NBD (BG/NBD) model to predict repeat transactions without and with static covariates
• Gamma-Gompertz (GGompertz) model to predict repeat transactions without and with static covariates
• Predictions are now possible for all periods >= 0 whereas before a minimum of 2 periods was required

CLVTools 0.5.0

• Initial release of the CLVTools package

NEW FEATURES

• Pareto/NBD model to predict repeat transactions without and with static or dynamic covariates
• Gamma-Gamma model to predict average spending
• Predicting CLV and future transactions per customer
• Data class to preprocess transaction data and to provide summary statistics
• Plot of expected repeat transactions as by the fitted model compared against actuals

CLVTools documentation built on Oct. 24, 2023, 1:06 a.m.