lifetimes

Spec sheet

Support

The documentation directs questions, comments, and requests to issues in the Lifetimes repository.Read 11 Oct 2026 · lifetimes.readthedocs.io

License

The GitHub repository identifies the project as MIT licensed.Read 11 Oct 2026 · github.com

Customer lifetime value

The Gamma-Gamma submodel estimates average customer value, and the docs demonstrate combining it with a purchase model to estimate lifetime value.Read 11 Oct 2026 · lifetimes.readthedocs.io

Customer status

The library can estimate a customer's probability of still being active and visualize it in a probability matrix.Read 4 Oct 2026 · lifetimes.readthedocs.io

Data preparation

Utility functions transform transaction-level records into customer summary data and split data into calibration and holdout periods.Read 11 Oct 2026 · lifetimes.readthedocs.io

Installation

The documented installation command is `pip install lifetimes`.Read 11 Oct 2026 · lifetimes.readthedocs.io

Lifetime value

The Gamma-Gamma submodel estimates customer lifetime value and assumes monetary value is independent of purchase frequency.Read 4 Oct 2026 · lifetimes.readthedocs.io

Maintenance status

The project repository was archived on June 28, 2024, and is read-only; its maintainers say they will not add features, improvements, or answer issues.Read 4 Oct 2026 · github.com

Model assessment

The documentation shows comparing fitted-model simulations with actual purchases and checking predictions against a holdout period.Read 4 Oct 2026 · lifetimes.readthedocs.io

Model assumption

The Gamma-Gamma model assumes monetary value and purchase frequency are unrelated, and the documentation recommends checking their correlation before using it.Read 11 Oct 2026 · lifetimes.readthedocs.io

Product type

Lifetimes is a Python library for calculating customer lifetime value.Read 4 Oct 2026 · lifetimes.readthedocs.io

Project status

The repository was archived on June 28, 2024, and its maintainers say they will not add features or answer issues there.Read 11 Oct 2026 · github.com

Purchase prediction

The BG/NBD model predicts expected purchases from customer frequency, recency, and age data.Read 4 Oct 2026 · lifetimes.readthedocs.io

Repeat purchase model

The quickstart demonstrates the BG/NBD model to estimate expected purchases from customer frequency, recency, and age data.Read 11 Oct 2026 · lifetimes.readthedocs.io

Successor

The repository points users to PyMC-Marketing as a successor project.Read 11 Oct 2026 · github.com

Use cases

The documentation describes predicting repeat visits, patient returns, app churn, repeat purchases, and customer lifetime value.Read 11 Oct 2026 · lifetimes.readthedocs.io

Visualization

The library includes plots for purchase counts, expected purchases, active probability, customer history, and transaction-rate heterogeneity.Read 4 Oct 2026 · lifetimes.readthedocs.io

Visualizations

The library includes plots for purchase predictions, probability a customer remains active, transaction histories, and model comparisons.Read 11 Oct 2026 · lifetimes.readthedocs.io

What it is

Lifetimes is a Python library for analyzing repeat customer activity and calculating customer lifetime value.Read 11 Oct 2026 · lifetimes.readthedocs.io

Where Specifiction places it

• Customer Lifetime Value Software#31 of 377.1