The BTYDplus R package provides advanced statistical methods to describe and predict customer's purchase behavior. It uses historic transaction records to fit a probabilistic model, which then allows to compute quantities of managerial interest on a cohort- as well as on a customer level (Customer Lifetime Value, Customer Equity, P(alive), etc.).

This package complements the BTYD package by providing several additional buy-till-you-die models, that have been published in the marketing literature, but whose implementation are complex and non-trivial. These models are: NBD, MBG/NBD, BG/CNBD-k, MBG/CNBD-k, Pareto/NBD (HB), Pareto/NBD (Abe) and Pareto/GGG.

• NBD Ehrenberg, Andrew SC. "The pattern of consumer purchases." Applied Statistics (1959): 26-41. \doi{10.2307/2985810}

• MBG/NBD Batislam, E.P., M. Denizel, A. Filiztekin. 2007. Empirical validation and comparison of models for customer base analysis. International Journal of Research in Marketing 24(3) 201–209. \doi{10.1016/j.ijresmar.2006.12.005}

• (M)BG/CNBD-k Reutterer, T., Platzer, M., & Schroeder, N. (2020). "Leveraging purchase regularity for predicting customer behavior the easy way." International Journal of Research in Marketing. \doi{10.1016/j.ijresmar.2020.09.002}

• Pareto/NBD (HB) Ma, Shao-Hui, and Jin-Lan Liu. "The MCMC approach for solving the Pareto/NBD model and possible extensions." Natural Computation, 2007. ICNC 2007. Third International Conference on. Vol. 2. IEEE, 2007. \doi{10.1109/ICNC.2007.728}

• Pareto/NBD (Abe) Abe, Makoto. "Counting your customers one by one: A hierarchical Bayes extension to the Pareto/NBD model." Marketing Science 28.3 (2009): 541-553. \doi{10.1287/mksc.1090.0502}

• Pareto/GGG Platzer, Michael, and Thomas Reutterer. "Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity." Marketing Science (2016). \doi{10.1287/mksc.2015.0963}