Meridian alternatives

2 tools to consider instead of Meridian, shown against it.

Meridian Robyn Recast
Vendor Google Meta Recast
Pricing model Open source + paid options Open source + paid options Quote only
Free tier Yes Yes No
Deployment Self-hosted Self-hosted Cloud
Open source Yes (Apache-2.0) Yes (MIT) No
Best for Teams with a data scientist comfortable in Python and Bayesian statistics who want full control over their MMM rather than a managed vendor. Teams with an in-house data scientist and multi-year weekly spend history who want full control over their MMM rather than a managed SaaS. Advertisers wanting rigorous MMM output without building and maintaining the statistical model in-house.
Pricing

Free, open-source Python library; the only cost is compute and the data scientist's time to build and maintain the model.

Pricing has not been verified yet — see the vendor's site.

Free, open-source R package; the only cost is the compute and the data scientist's time to run and maintain it.

Pricing has not been verified yet — see the vendor's site.

Custom quotes based on ad spend and number of channels modeled; pricing is not published.

Pricing has not been verified yet — see the vendor's site.

Features
  • Bayesian marketing mix modeling in Python
  • Optional geo-level modeling for regional data
  • Incorporates reach and frequency signals where available
  • Budget optimization and scenario simulation
  • Successor to Google's LightweightMMM project
  • Model diagnostics and posterior-uncertainty reporting
  • Ridge regression with adstock and saturation transformations
  • Genetic-algorithm-driven hyperparameter search
  • Budget allocation optimizer output
  • Support for multiple media and non-media variables
  • Model diagnostics and one-pager output plots
  • Community Python port available
  • Managed Bayesian media mix modeling
  • Geo-experiment design to validate model estimates
  • Diminishing-returns and saturation curves by channel
  • Budget allocation and scenario simulation
  • Regular model refreshes as new data arrives
  • Statistician-assisted setup and interpretation

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