Marketing Mix Modeling (MMM) has become a vital tool for businesses looking to optimize their marketing investments. In a world where attribution tools are still broadly used in cross-channel budget allocation, MMM provides an alternative for measuring media ROI based on true incremental sales impact of each channel.
Modern MMM tools are more accessible and powerful than ever. But how should one choose which tool to adopt? In this article, we'll revisit our evaluation criteria for choosing an MMM tool, as well as provide alternatives you can start evaluating.
Marketing Mix Modeling (MMM) is a statistical analysis technique to measure how marketing campaigns and channels are driving sales. By analyzing historical data, MMM is able to explain how different channels, such as Google Performance Max and Meta Advantage+, contribute to sales. It quantifies the return on investment (ROI) for media spend, enabling data-driven media budget optimization decisions. Below is an illustration of how MMMs work:
Next Gen MMM solutions have evolved beyond traditional time-series models: they leverage incrementality tests and attribution data to uncover the true ROI of each channel. For an in-depth overview of MMM, check the Sellforte Marketing Mix Modeling guide.
Sellforte’s Buyers Guide to MMM Tools provides a full in-depth explanation of what to look for when evaluating Marketing Mix Modeling tools or platforms. Below you'll find the summary with icon ✅ indicating a basic feature in most MMMs, and icon 💎 indicating features you typically find from most advanced MMM platforms, Next Gen MMMs.
Your primary goal in is to ensure that the Marketing Mix Modeling solution includes optimization capabilities that improve marketing ROI and enhance sales performance. Here’s a checklist covering key optimization levers:
Basic MMM features:
✅ Advertising channel-level optimization
Next Gen MMM features:
💎 Campaign-level optimization
💎 Optimal weekly budget pacing
Once you've checked that the Marketing Mix Modeling tool you're evaluating has the required optimization capabilities that help you drive more sales, you need to determine whether you can trust the MMM results sufficiently to make data-driven decisions based on its recommendations.
Here’s the reality: many Marketing Mix Models on the market produce low-quality, unreliable results. Why? While generating MMM results has become easier than ever with free-to-use modeling libraries, the real challenge remains: MMM datasets are often noisy and plagued by multicollinearity. This makes building stable, high-quality models that generate accurate results challenging.
Fortunately, there are indicators that can help you assess whether an MMM vendor delivers high-quality results. Here’s a checklist:
Basic features:
✅ Statistical model validation
✅ Bayesian approach
Next Gen MMM features:
💎 MMM is calibrated with informative priors
💎 In-built Causal Attribution Model for generating informative priors
💎 Advanced model validation based on model outputs
Now that you’re sure that your MMM provides the right optimization insights and delivers high-quality modeling results, the next step is to assess how easy it is to get started with the platform. At Sellforte, we’re particularly passionate about ensuring that MMMs are both user-friendly and accessible—without sacrificing the accuracy and reliability of the results. Here's your checklist:
Basic features:
✅ Data connectors
Next Gen MMM features:
💎 Delivers high quality results in 1-2 weeks
💎 Provides a Free Trial
While choosing a Marketing Mix Modeling tool is ultimately a decision for you to make, the evaluation framework in the previous chapter should provide a good starting point for comparing different MMM tools and companies. To get you started here's a list of 23 Marketing Mix Modeling tools:
Sellforte is a Next Gen Marketing Mix Modeling platform for Retailers, eCommerce businesses and DTC brands:
Sellforte offers a free trial for qualifying eCom / DTC brands and retailers to test the platform.
Meridian enables organizations to develop customized Marketing Mix Models. Like Sellforte, Meridian leverages Bayesian MMM approach. It incorporates several advancements studied by Google Research teams over the years, providing a powerful toolkit for skilled analysts and data scientists. With Meridian, users can:
Meridian accelerates the process of developing Bayesian Marketing Mix Models, saving data scientists the effort of manually implementing essential MMM components like adstock effects and diminishing returns.
This solution is best suited for companies with experienced data science and software development teams looking to build a highly customized MMM framework almost from scratch. However, compared to a comprehensive MMM platform like Sellforte, Meridian lacks a user-friendly interface for marketers to conduct analyses and optimize media budgets. Additionally, it does not include built-in data connectors for ad platforms, automated data processing pipelines, or automated model calibration workflows.
Robyn, developed by Meta, is an open-source Marketing Mix Modeling (MMM) library that allows businesses to create customized marketing mix models. It leverages Facebook’s Nevergrad optimization library along with the Prophet time-series forecasting library. Nevergrad applies advanced machine learning techniques—such as Bayesian optimization and genetic algorithms—to fine-tune model parameters. Robyn also utilizes hyperparameter optimization, running thousands of model variations with different parameter settings to identify the most accurate configuration.
Like Meridian, Robyn is best suited for companies with experienced data science and engineering teams looking to build a fully customized MMM solution from the ground up. However, compared to a complete MMM platform like Sellforte, Robyn lacks a user-friendly interface for marketers to analyze results and optimize scenarios. Additionally, it does not include built-in data connectors to ad platforms, automated data processing pipelines, or automated model calibration workflows.
PyMC-Marketing is an open-source library built on PyMC. Like Sellforte and Meridian, PyMC-Marketing leverages a Bayesian Marketing Mix Modeling (MMM) approach.
PyMC-Marketing is best suited for companies with experienced data science and engineering teams looking to build a fully customized MMM solution from the ground up. However, it lacks features typically found from full MMM solutions, like built-in data connectors, automated data processing pipelines, automated model calibration workflows, or a user-interface for analysis and optimization.
Uber’s Orbit library is a lightweight, scalable framework designed for time-series forecasting, making it useful for Marketing Mix Modeling (MMM) applications. Like Sellforte, Orbit leverage Bayesian MMM approach. Orbit's use in MMM was illustrated in Orbit's paper “Bayesian Time Varying Coefficient Model with Applications to Marketing Mix Modeling“
Since Orbit is primarily a forecasting library, it lacks some critical MMM features, such as modeling diminishing returns or adstock. It also lacks features typically found from full MMM solutions, like built-in data connectors, automated data processing pipelines, automated model calibration workflows, or a user-interface for analysis and optimization.
Israeli-based Incrmntal is a 2020-founded MMM Saas startup, with several gaming companies mentioned as their reference customers, such as Sega, Supercell, Gameloft.
Incrmntal headline: "Welcome to the Future of Measurement"
Recast is an MMM SaaS that highlights rigorous modeling and model validation as its strength.
Recast headline: "Recast is the world’s most rigorous incrementality platform"
Cassandra is an Italian MMM SaaS startup, founded in 2022.
Cassandra headline: "Measure and Optimize your Media Mix with AI"
Keen Decision Systems is an MMM SaaS alternative.
Keen Decision Systems headline: "Forecast, optimize, and analyze your marketing investment"
Prescient AI is an MMM SaaS alternative.
Prescient AI headline: "The world’s smartest marketing decision engine, powered by the most dynamic MMM."
Measured is an MMM SaaS company.
Measured headline: "Unlock the incremental power of your media"
LiftLab is an MMM SaaS alternative.
Liftlab headline: "Maximize Your Marketing P&L for Growth and Profitability."
Paramark is 2023-founded MMM SaaS alternative.
Paramark headline: "Invest in marketing with confidence & predictability"
Lifesight is an India-based MMM SaaS alternative.
Lifesight healine: "Fix the marketing attribution that is killing your growth"
Mutinex is an Australian MMM SaaS company.
Mutinex headline: "Mutinex is your business growth co-pilot. Your best decisions start here."
Rocker is originally a multi-touch-attribution company, who has later expanded to providing MMM SaaS.
Rockerbox headline: "Rockerbox unifies your marketing measurement, marketing data, marketing decisions making, entire business"
Objective Platform is a Neatherlands-based company offering MMM consultancy services and an MMM platform.
Objective Platform headline: "Elevate your marketing with data-driven insights, cross-channel optimization, holistic data overview, next gen attribution modeling, advanced budget forecasting, customizable reporting"
Circana is a marketing analytics consulting company, who also provide Marketing Mix Modeling consulting services.
Circana headline: "We measure and accelerate demand."
Analytic Partners is a marketing analytics consulting company with a broad offering, which also includes Marketing Mix Modeling consulting services.
Analytics Partners headline: "We help global brands maximize success with impactful marketing decisions"
Kantar provides Marketing Mix Modeling consulting services through a sub-brand called Blackwood Seven, which it aquired in 2022.
Blackwood Seven headline: "LIFTROI x HamiltonAI. Unified Marketing Measurement & Optimization."
Aryma Labs is an India-based company offering Marketing Mix Modeling projects. They are active in MMM-related publications, emphasize the frequentist MMM approach (instead of Bayesian).
Aryma Labs headline: "Marketing Measurement For The Privacy First Era."
Proof Analytics provides Marketing Mix Modeling consulting services.
Proof Analytics headline: "Proof-as-a-Service. Make smarter decisions in a volatile marketplace with Proof CausalAI™"
Nepa is a Sweden-based marketing analytics consultancy, also offering Marketing Mix Modeling.
Nepa headline: "Big data, human touch. At the nexus of data analysis and marketing mastery, Nepa translates complex information into clear direction."
Marketing Mix Modeling reveals the true ROI of all of your channels, and enables you to optimize your media spend based on true incremental impact of each media.
If you are ready to unlock the full potential of your media budget, start your free trial with Sellforte today.
What is Marketing Mix Modeling? A Complete Guide. Link
Ultimate Buyer's Guide to MMM: How to Choose the Best Platform in 2025. Link
From Last-click to Marketing Mix Modeling (MMM): Unlock +6.5% more sales. Link