Marketing Mix Modeling with Google’s Lightweight MMM Library | Latest Update from Google

What is Marketing Mix Models (MMMs)

Marketing Mix Models (MMMs) measure the effectiveness of marketing campaigns and how different media (and non-media) channels contribute to a business goal (e.g. sales). Yet, it’s complex, expensive, and often intrasparent to set up an MMM.

What is Lightweight MMM

Lightweight MMM is an open source bayesian*marketing mix modeling library that allows users to esily train MMMS and obtain channel attribution insights.

Discover the latest breakthrough in marketing analytics as Google introduces the groundbreaking  “Lightweight MMM” library. This open-source solution revolutionizes Marketing Mix Modeling, offering marketers a user-friendly approach to training MMM models and gaining valuable insights.


Marketing Mix Modeling (MMM) plays a pivotal role in measuring the effectiveness of advertising campaigns and facilitating informed budget allocation decisions. However, the complexity of MMM has often limited its accessibility to data scientists with specialized expertise in modeling.

Now, with the introduction of Google’s Lightweight MMM library, marketers of all levels can harness the power of MMM without the need for extensive technical knowledge. This game-changing solution simplifies the training process and empowers marketers to derive meaningful insights from their marketing data.

Are you excited to embrace the potential of MMM models but unsure where to start? We’re here to guide you every step of the way. Our team of experts is ready to assist you in leveraging the full capabilities of this cutting-edge tool.

Don’t miss out on this incredible opportunity to enhance your marketing strategies and drive better results. Connect with us today and embark on a journey of maximizing the potential of Marketing Mix Modeling with the user-friendly Lightweight MMM library from Google.

Use cases

  • Estimate the optimal budget allocation across media channels
  • understand how media channels perform with a change in spend
  • investigate effects on your target KPI (e.g sales) by media channel


  • Full model ownership
  • Robust and statistically sound
  • Simple and easy to use
  • Transparent and open source


  • At least 2 years of weekly spend and impression data
  • Python and statistics knowledge

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