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MMM Labs

#19 of 31 in Media Mix Modeling Software

MMM Labs: A multi-engine MMM workspace for comparing results and planning media budgets. Ranked #19 of 31 in Media Mix Modeling Software by our editors (7.5/10); pricing: Pricing on request; best for teams comparing several MMM engines.

7.5/10Editor score
MMM Labs7.5 Visit MMM Labs

At a glance

  • Editor score
    7.5 / 10
  • Pricing
    Pricing on request
  • Best for
    Teams comparing several MMM engines
  • Modeling approach
    Hybrid
  • Facts checked
    13 Oct 2026
  • Where it wins

    • Runs Meridian, PyMC and Robyn approaches for model comparison.
    • Reports ROI, marginal ROI and media contribution.
    • Forecasts and optimizes budgets, with exports and MCP connections.
  • Where it doesn't

    • Commercial terms require contacting the vendor.
    • Cloud deployment may not suit teams requiring another deployment model.
    • Support is listed through email rather than multiple channels.

Our verdict on MMM Labs

MMM Labs is a web-based marketing mix modeling platform from ScanmarQED for brands and agencies that need to compare modeling approaches. Teams can upload marketing and sales data, run Meridian, PyMC and Robyn engines, and review results in one place. That multi-engine scope makes the product relevant to analysts and planners who want to compare model outputs rather than commit to a single engine. It also serves different company sizes, from small teams to enterprise organizations, with a cloud deployment and an API platform option.

Its central value is the path from modeling to planning: the platform presents ROI, marginal ROI and media contribution, then supports budget forecasting and optimization. Technical and business reports are available, and users can export model components and data. This breadth is useful when modeling work needs to inform budget decisions as well as analysis. The product also connects with MCP-compatible AI tools and assistants, including Claude, ChatGPT, Gemini, Microsoft Copilot, Perplexity and Cursor. Teams choosing it should assess whether that multi-engine workflow and assistant connectivity match their analytics process.

MMM Labs is not a fit for buyers who need a published, self-serve price to evaluate before speaking with a vendor: commercial terms are handled through contact with ScanmarQED. The listed deployment is cloud, and email is the stated support channel, so organizations with other deployment or support requirements should weigh those constraints before choosing it. The platform is described as GDPR-compliant, and ScanmarQED says MMM Labs is to be integrated into its PulseQED analytics platform. Choose it for comparing MMM engines and connecting model results to media planning; consider alternatives if a single-model workflow, different deployment, or broader listed support options are priorities.

Your product? Our editors can test MMM Labs in depth and publish a review, labelled as paid · from $99/mo →

MMM Labs pricing

Plans Pricing on request No free plan — trial or paid only. Prices checked 13 Oct 2026.
See plans on mmmlabs.ai

MMM Labs fact sheet

Free planNot verified
Paid fromNot verified
Modeling approachHybrid
Budget optimizationYes
Incrementality analysisYes
Model refreshNot verified
Data connectorsNot verified
Managed modelingYes
DeploymentCloud
PlatformsWeb
Compliance & securityGDPR
SupportEmail
Built forSmall business, Mid-market, Enterprise (editorial estimate)
Integrations7 integrations: Claude, ChatGPT, Gemini, Microsoft Copilot, Perplexity, Cursor …
PricingPricing on request
Websitemmmlabs.ai
Facts checked13 Oct 2026

MMM Labs integrations

MMM Labs lists 7 integrations on its own site.

  • Claude
  • ChatGPT
  • Gemini
  • Microsoft Copilot
  • Perplexity
  • Cursor
  • MCP-compatible tools

Alternatives to MMM Labs

See all MMM Labs alternatives →

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Featured on iTechGuides

Featured on iTechGuides — MMM Labs 7.5/10

MMM Labs is listed in our Media Mix Modeling Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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