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google/lightweight_mmm

LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information. observed · 2026-08-28

github.com/google/lightweight_mmm · homepage · Python · Apache-2.0 (permissive) · archived observed · 2026-08-28

Health v2 · maintenance only

10/100

  • Activity 27
  • Release rhythm 8
  • Longevity 100

Flags: archived

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1665
  • days_rel: n/a
  • days_push: 442
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1052 stars · 234 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LightweightMMM is a Python library for Bayesian Marketing Mix Modeling (MMM) built on JAX and Numpyro, helping advertisers measure media channel effectiveness and optimize budget allocation. It has been deprecated in favor of Google's successor library, Meridian, and is no longer supported.

Use cases

  • estimate optimal marketing budget allocation across media channels
  • measure advertising effectiveness with Bayesian marketing mix modeling
  • attribute sales KPI changes to online and offline media channels
  • model media spend impact with uncertainty quantification
  • build hierarchical MMM models across geographies

When to choose

  • maintaining or reproducing legacy models originally built with LightweightMMM
  • studying the library's approach to Bayesian MMM before migrating to Meridian

When to avoid

  • starting a new marketing mix modeling project - use Google Meridian instead
  • expecting bug fixes or support, since the project is officially unsupported
  • needing production-grade MMM tooling with active maintenance

Facets

library · maturity abandoned

machine-learning data-science analytics data-science analytics python cross-platform bayesian marketing-mix-modeling media-attribution jax numpyro budget-optimization deprecated marketing-science

2 sources

Member repositories

RepositoryRoleHealth v2
google/lightweight_mmmmain10

For agents

markdown · JSON · MCP: product_card(name="google/lightweight_mmm")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem