Enterprise-Grade
‍Media Mix Modeling

Proprietary PhD-Researched Bayesian MMM that delivers accuracy, clarity, and strategy at $2,000/month.
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Finally, MMM Without the Complexity

Marketing leaders need to know which channels truly drive growth, but traditional MMMs were expensive and confusing. Stella changes that by combining PhD-researched proprietary models with an easy-to-use platform. You get enterprise accuracy without the enterprise overhead.

PhD-Level Statistical Analysis, Made Simple

MMM used to require consultants to interpret results and present them back. Stella automates that process, turning advanced Bayesian modeling into simple dashboards anyone on your team can understand. Your insights are as rigorous as a PhD analysis, but accessible in minutes.

Built to Be Accurate and Affordable

Most MMM providers charge $15K to $80K for a single model because everything is built custom and they give the illusion that the more you pay the better the results will be, this is not true. Stella offers the same level of accuracy at $2,000 per month, with unlimited studies. We made measurement scalable so you never sacrifice quality for cost.

Smarter Planning, Clearer Strategy

Stella doesn’t just show the past, it helps you plan the future. With scenario planning and budget optimization, you’ll see exactly where to spend next to maximize incremental revenue. Marketing measurement becomes an actual growth engine, not just a report.

Your Partner in Precision Marketing Measurement

Collect
Analyze
Optimize
Collect data with our template
Upload up to 27 months of data, including external factors like sales, holidays, and weather, to isolate each channel’s true impact.
Properly analyze MMM results
Stella turns complex MMM charts into plain-language insights, showing exactly what’s driving performance and where to adjust.
Optimize your budget
Use Stella’s budget optimizer to pinpoint where to invest for maximum incremental ROI, factoring in seasonal trends and external variables.

Media Mix Modeling
you can actually afford

Get statistically sound, Bayesian MMM built for brands that need real answers, not consulting fees.
All the rigor of PhD-built models, without the $50,000 price tag.

No long-term contracts
Stella Media Mix Modeling
$2000/month
$4000/month
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Prove campaign lift
Adstock & Saturation Transformation
Proprietary PhD-Backed Bayesian Model
Channel Distribution
Budget & Revenue Optimizer
Weekly Response Curves
Configurable Control Variables
Forecasting based on historical trends

Find the true impact of every single dollar with Stella

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Everything you need to know about Stella

Quick answers to the most common questions from marketers.

Is Stella just using PyMC, Robyn, or Meridian under the hood?

No. Stella’s MMM is 100% proprietary. While we’ve taken inspiration from the best ideas in open-source models like PyMC and Google’s Meridian, our model architecture, optimizer, and UI are built from scratch. This ensures Stella is tailored to marketing teams, not engineers, and gives you enterprise-grade accuracy without needing custom code.

Who built Stella’s MMM?

Stella’s MMM was built by our founding team after years of running custom models for mid-market brands. We combined those learnings with input from three independent PhD data scientists and statisticians who reviewed our methods for accuracy and statistical rigor. The result is a proprietary Bayesian MMM that captures variance well and consistently produces reliable insights.

Why is Stella more affordable than other MMM providers?

Custom MMM builds can cost anywhere from $15,000 to $80,000 per model. Stella’s MMM is delivered as a self-service SaaS tool at a flat $2,000/month. Because we use a flexible upload workflow instead of rigid integrations or custom builds, we’ve eliminated the engineering overhead that drives up costs, without compromising data quality.

What makes Stella’s MMM accurate?

We use a fully Bayesian framework with priors, posterior distributions, and uncertainty checks to ensure accuracy. Each model passes internal diagnostic checks including MAPE, R-squared, and R-hat convergence. Out-of-sample predictions let you validate model fit, while channel-level ROAS posterior curves give you confidence in the results.

What kind of data do I need to run a Stella MMM?

Stella requires 24 - 27 months of weekly data (two full years plus one rolling quarter). You can upload via CSV or Google Sheets, no engineering integration required. We support DTC, Amazon, retail, and geo-level splits, and you can include confounding factors like promotions, holidays, weather, out of stocks, or any custom variable for your business.

What do I get out of a Stella MMM beyond contribution charts?

Unlike most MMMs that stop at attribution, Stella goes further. Every model comes with a built-in budget optimizer and revenue optimizer. You can enter a budget or revenue goal, and Stella recommends the optimal spend allocation by channel. This turns your MMM from a rearview mirror into a forward-looking planning tool.

Clarity in Marketing Performance

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