Marketing Mix Modeling
Marketing Mix Modeling built for commerce
Continuous MMM that runs on contribution margin, not revenue. Response curves show where each euro works hardest, calibrated by real incrementality experiments.
Trusted by commercial teams at leading brands
Budget optimization
Always-on budget optimization across every channel and market
Response curves show where each euro works hardest. The optimizer recommends the best allocation for your objective (profit, revenue, or new customers) and refreshes as new data arrives.
Flexible objectives
Optimize for profit, revenue, new customers, or long-term value. Set different goals per market: growth markets chase new customers, mature markets protect margin.
Marginal ROAS
Not average ROAS. The return on the next euro. The optimizer reads the slope of each response curve to find where spend still has room to grow.
Guardrails & constraints
Protect brand spend, freeze channels under test, cap max swings. The optimizer respects your rules.
Multi-metric steering
Sales, margin, new-customer profit, LTV. Switch the objective and watch the optimal mix shift.
Scenario comparison
Save a profit plan and a growth plan side by side. Compare budget shifts, then pick the path that fits.
Profit-focused
Models run on contribution margin, not just revenue.
Calibrated by experiments
Incrementality tests keep your MMM grounded in reality.
Agent-powered
Ask the agent to compare channels, run scenarios, or shift budget.
Ad platforms overstate performance by up to 40% on average. Marketing Mix Modeling reveals where your budget actually drives results.
Calibration
Feed the model with real experiments
A model is only as honest as the evidence behind it. Geo-based incrementality tests give Dema's MMM causal ground truth, so response curves reflect what actually happened rather than what the platforms reported.
Tests produce ground truth
Geo-based experiments measure what spend actually caused — no cookies, no platform claims.
Results feed the model automatically
Every finished test recalibrates the response curves it touched. No consultant re-fit, no quarterly refresh.
The optimizer spends against calibrated curves
Budget recommendations come from curves anchored in your own experiments, not industry priors.
Incrementality test · Meta · Sweden
Geo holdout · 3 of 12 regions · 4 weeks
Measured lift 1.68× · curve recalibrated
Marginal ROAS revised
Trusted by category leaders
Real teams, real numbers — from cutting acquisition costs to doubling profit to automating whole planning cycles.
They tested scaling Google spend — and incremental profit went up with it.
Axel Arigato is a contemporary fashion and sneaker brand born at the intersection of streetwear, music, and culture. As growth accelerated, the team wanted to ensure that scaling their digital investments would translate into sustainable, profitable growth, not just higher ad spend. That's when they turned to Dema.
>100% Incremental epROAS on Google scalingEnterprise-ready
Built for production.
Where your data is processed, how it is protected, and what an agent is allowed to change are controls you set — not defaults you inherit.
EU & US inference
Choose where your data is processed. Model inference and data pipelines run on European or US infrastructure with full residency control.
Never used to train models
Your data is never used to train models. Processing stays in your chosen region and runs in isolated, encrypted sessions.
Always the latest models
New reasoning models roll out as they ship, so your agents keep improving automatically without migration work.
Permissions and approvals
Each agent has its own scope and integrations. Actions can require a named approval before anything changes.
What you can create
Real setups, linked to how they run.
Every example below is a real prompt from the library. Open the use case behind it to see the full run — what it checks, what comes back, and where it lands.
Questions
Frequently asked questions
Marketing Mix Modeling (MMM) is a statistical method that measures how each marketing channel contributes to business outcomes, using aggregate spend and results data rather than user-level tracking. Because it doesn't depend on cookies or click attribution, it stays accurate as privacy restrictions tighten. Dema's MMM runs on contribution margin, so it measures profit impact rather than just revenue.
Dema MMM runs continuously. It ingests new spend and revenue data as it arrives, so your model is always current. No waiting for quarterly consulting deliverables.
Platform ROAS tells you what the ad platform claims. It's biased because platforms optimize for their own attribution. MMM measures each channel's contribution from aggregate data, and geo-based incrementality tests provide causal proof. The agent helps you compare all three methods side by side.
Multi-touch attribution follows tracked user journeys and divides credit between the touchpoints it can see — precise, but blind to anything untracked and getting blinder as privacy rules tighten. MMM works from aggregate spend and outcome data, so it covers every channel including the untrackable ones, at the cost of user-level granularity. Dema runs MMM as the budgeting backbone and uses causal attribution to keep the channel-level view honest.
They're stronger together. Incrementality tests answer specific causal questions ('Does Meta in Germany work?') but can't cover every channel every month. MMM gives continuous, full-mix measurement, and incrementality results calibrate the model so it stays accurate.
Marginal ROAS is the return on the next euro of spend, rather than the average return across all spend. It matters because channels saturate: a channel with high average ROAS may have no room left to grow, while a lower-average channel might still be underfunded. The optimizer reads the slope of each response curve to find where spend still has headroom.
Connect your ad platforms (Google, Meta, TikTok), your e-commerce platform (Shopify), POS or store systems, and your cost data. Dema builds the unified data model automatically. Most teams are set up within a day.
Bring one commercial job