Budgee vs PyMC-Marketing

Budgee is web-based software for marketing teams to plan budgets, track spending, and reconcile expenses without spreadsheets. It covers annual planning through monthly reconciliation and tracks actual spend against planned amounts in real time, with visual variance alerts. Listed capabilities include planning, expense tracking, alerts, reports, AI, imports, and an audit log. Marketing expenses can be imported from Xero or QuickBooks for reconciliation. Individuals can manage their own budgets while executives retain oversight. The service has no free plan, but signup advertises a 14-day trial with full access and no credit card required. Starter costs $25 a month and includes unlimited users, 30 day audit history, one alert, and 10 transaction imports monthly. Pro costs $45 a month, also with unlimited users, and includes 12 month audit history, unlimited alerts, and unlimited transaction imports. Starter includes standard support; Pro lists priority support. The terms say customers retain ownership of uploaded financial data and budget plans, while granting Budgee a license to host, use, process, and display that data to provide and improve the service.

PyMC-Marketing is an open-source Python library for Bayesian marketing analytics, with tools for marketing mix modeling (MMM) and customer lifetime value. Its MMM API supports custom priors and likelihoods, adstock and saturation transformations, time-varying effects, diagnostics and out-of-sample predictions. Models can be calibrated against empirical experiments such as lift tests, and built-in budget optimization allocates spend across channels to maximize ROI. Bayesian outputs include posterior distributions and credible intervals for predictions. The library also includes customer choice, Bass diffusion and alpha-stage predicted incrementality by experimentation models, alongside predictive CLV, cohort analysis and customer segmentation. It runs on Linux and can be self-hosted. Current documentation requires Python 3.12 or later, PyMC 6.0 or later and ArviZ 1.2 or later; installation is available through pip with `pip install pymc-marketing`, without requiring a conda environment. The library is free under the Apache 2.0 license. PyMC Labs and PyMC core developers maintain it, and learning resources include a guided path, example notebooks and an API reference.