clvkit vs WorthSignal
clvkit
github.comWorthSignal
github.comSide by side
| Figure | clvkit | WorthSignal |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | — | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| Self-hosted | — | Yes |
| Plans published | 0 | 1 |
| Spec score · Customer Lifetime Value Software | 7.1 (#30) | 7.9 (#12) |
| Intended users | The README describes it as a narrower tool for analysts who want model parameters and a CSV through a maximum-likelihood workflow. | The maker describes WorthSignal as a tool for marketers to examine customer value, retention, and marketing ROI. |
| License | The package metadata identifies its license as BSD-3-Clause. | The repository states that WorthSignal is licensed under AGPL-3.0-or-later and that commercial use is allowed subject to the license conditions. |
| Purpose | clvkit is a Python library for estimating customer lifetime value and cohort retention from transaction logs for non-contractual businesses. | WorthSignal turns Excel, CSV or JSON customer data into customer segmentation, lifetime value, retention and marketing ROI analyses. |
| Support | The project links to its GitHub Issues page for issue reporting. | Security reports are reviewed on a best-effort basis and the volunteer project does not promise a formal response-time SLA. |
Plans
In their own words
WorthSignal
WorthSignal is a free, open-source toolkit that turns spreadsheet and data files into customer value analyses for marketers. It reads XLSX, XLS, XLSM, CSV and JSON files, suggests column mappings and lets users correct them without changing the uploaded file. Its analyses cover nine areas, including RFM targeting, customer lifetime value, customer equity, acquisition and retention budgets, Markov switching ROI, contractual retention, BG/NBD, BG/BB and complaint recovery. Results can be downloaded as Excel or JSON. In local mode, analysis runs in memory on the user's computer; WorthSignal says uploaded customer data is not intentionally sent to its maintainer or a third-party API. Hosted deployments process files on the chosen server, and that operator is responsible for access controls, logs, retention and privacy obligations. The app requires Python 3.10 or newer and can be launched on Windows or Mac, through terminal instructions for any operating system, or with Docker. Its documented methods are described as classic, deliberately simple models. The project uses the AGPL-3.0-or-later license, with commercial use subject to its conditions.