Baremetrics vs CLVTools
Baremetrics
baremetrics.comCLVTools
github.comSide by side
| Figure | Baremetrics | CLVTools |
|---|---|---|
| Price from | $75/mo | Free |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | — |
| Plans published | 5 | 1 |
| Spec score · Customer Lifetime Value Software | 8.3 (#7) | 8.4 (#3) |
| Support | Launch includes chat support, while Scale includes a dedicated support representative. | The project invites bug reports through GitHub Issues and contributions through pull requests. |
Plans
Baremetrics
- Launch$75 a month
- Cancellation Insights add-on$129 a month
- Payment Recovery add-on$129 a month
- Growth$255 a month
- Scale$1,152 a month
In their own words
Baremetrics
Baremetrics is subscription analytics software for businesses that track recurring revenue. It reports more than 28 metrics, including MRR, ARR, churn, upgrades and downgrades, alongside cohort analysis, predictive CLV, profitability metrics and customer segmentation. Forecasting addresses hiring, expansion and departmental budgets. Growth includes custom dashboards. Cancellation Insights collects cancellation feedback, shows revenue lost by reason and can send personalized follow-up emails. Payment Recovery supplies automated tools and reminders for failed payments. Native integrations include Stripe, Shopify Partners, Braintree, Recurly, App Store Connect, Google Play and Chargebee. Other data can enter through the API or Intercom and Zapier integrations. The service runs on the web and through an API. Launch starts at $75/mo with one integration, Growth at $255/mo with two, and Scale at $1152/mo with unlimited integrations. Payment Recovery and Cancellation Insights each cost $129/mo as add-ons. There is no free plan, but a 14-day trial is available.
CLVTools
CLVTools is a free, GPL-3-licensed R package for probabilistic customer attrition modeling when purchases are not governed by contracts. It implements Pareto/NBD, BG/NBD, Gamma/Gompertz/NBD, and Gamma/Gamma models. Using transaction histories with customer IDs and purchase dates, plus prices in its example data, it predicts individual customer behavior such as expected future transactions and the probability that a customer remains active. Forecast horizons can be configured, supporting predictive customer lifetime value work, cohort analysis, and customer segmentation. Time-invariant covariates work across the models, while some models accept time-varying covariates. Extensions include correlated purchase and attrition processes, L2 regularization, and equality constraints for contextual-factor parameters. Stable installation is available from CRAN; a development version uses GitHub and devtools. Linux, macOS, and Windows are supported, though compiling from source requires the external GNU GSL C++ library. Documentation includes a walkthrough, reference manual, and vignettes.