Unified Marketing Measurement (UMM): One Framework for MTA, MMM, and Experiments
Stop choosing between your measurement methods. Roivenue’s UMM combines multi-touch attribution, marketing mix modeling, and incrementality experiments into a single connected model, so every channel gets measured the way it deserves.








One unified model. One agentic layer. From measurement to the next budget move.
Every number Roivenue UMM produces, an MTA credit, an incrementality test result, a unified view that folds in your MMM inputs, agentic AI can act on directly: ask a question, build the report, analyze what moved, and reallocate budget across channels, all in one agentic workflow.
You stay in control, and your data stays yours. No made-up numbers: every answer is grounded in your own attribution data. No surprises: you decide what happens next, every time.
Roivenue MCP
Your unified model, acting through any AI agent.
Generate a cross-channel report spanning attribution, incrementality tests, and your MMM inputs, or reallocate budget across channels, straight from Claude, ChatGPT, or whatever AI agent your team already runs, on the open Model Context Protocol standard.
R-AI
Your in-app AI Data Consultant
R-AI reads your unified model and builds the answer: why TV’s incremental lift shifted this quarter, how that lines up against your attribution data once your MMM inputs are folded in, and what the Budget Optimizer recommends moving between channels, grounded in your own account’s data.
Works with the AI your team already runs
Roivenue MCP is built on the open Model Context Protocol, the same standard behind Claude, ChatGPT, and the AI agents your team is already using. Point the assistant you already have at Roivenue and start asking.
Claude
ChatGPT
Gemini
Cursor
Copilot
Perplexity + any MCP-compatible agent
Add offline channels to your attribution data
Evaluate offline channels and external factors alongside digital performance. UMM enriches attribution results with insights from your marketing mix model, so you can connect online and offline and make smarter investment decisions across the full customer journey.

Attribution granularity in your MMM
Traditional MMM often works at a high level, leaving you blind to campaign details. With UMM, you can add the granularity of attribution data directly into your mix model. This lets you move from broad budget splits to precise insights on campaigns, channels, and even tactics, without losing the long-term view that MMM provides.


Use Incrementality Tests to calibrate your model
Experiments give you the ground truth that other methods can’t. With UMM, you can feed results from lift tests and controlled experiments directly into the model. This ensures your measurement is not only comprehensive but also validated by real-world outcomes, making every recommendation more reliable.
How it works
Unified Marketing Measurement brings together the best of MTA, MMM, and experiments. Here’s how we combine your data sources into one model that delivers both detail and strategic insight.
Import your marketing mix model from any source and connect it with attribution results inside UMM. This allows you to bring in:
- Digital channels – align MTA and MMM by mapping mix model variables to specific attribution data
- Offline media – add the missing view of traditional channels that attribution alone cannot capture
- External factors – include seasonality, weather, or other variables to complete the picture
On top of this, you can also feed in experiment results to calibrate and validate the model with real-world evidence.
Define how your data sources should work together inside one unified model. Each channel can be configured independently, while our optimization algorithm processes your rules to create a UMM that combines the strengths of MTA, MMM, and experiments.
With Roivenue, you can build and compare multiple UMM models side by side, making it easy to identify the version that best matches your business goals.
UMM results are available across all Roivenue reports and exports, so you can work in the environment that suits you best, whether that is directly in Roivenue or inside your existing BI tools like Power BI, Tableau, or Looker Studio.
Every budget change you make can be measured and analyzed, giving you instant feedback on its impact. This means you can experiment freely, optimize with confidence, and always know if you are moving in the right direction.
The project was carried out under the Country for the Future program of the Ministry of Industry and Trade and co financed from European Union funds under NEXT GENERATION EU.


MTA, MMM, and UMM: What Each Method Measures
Roivenue UMM
Channel coverage
Digital trackable only
Online + Offline
Full digital (MTA scope) + offline channels
Campaign-level within a mix model
Time to insight
Near real-time
Weekly to monthly
Near real-time with strategic context
Low
High, with experiment calibration
Tactical and strategic, unified
Roivenue (native, imports MMM)
Digital trackable only
Roivenue UMM
Full digital (MTA scope) + offline channels
Roivenue UMM
Campaign-level within a mix model
Time to insight
MTA
Near real-time
MMM
Weekly to monthly
Roivenue UMM
Near real-time with strategic context
Roivenue UMM
High, with experiment calibration
Roivenue UMM
Tactical and strategic, unified
Roivenue UMM
Roivenue (native, imports MMM)
Frequently Asked Questions about Unified Marketing Measurement
Marketing mix modeling (MMM) is a standalone statistical methodology that uses historical spend and outcome data to estimate channel contribution. Unified Marketing Measurement (UMM) is a framework that combines MMM with multi-touch attribution (MTA) and incrementality experiments in a single model. UMM uses MMM as one of its inputs, it does not replace MMM; it orchestrates it alongside other measurement signals. Roivenue provides UMM and MTA natively; MMM is imported from any external provider.
Roivenue is an MTA and Unified Marketing Measurement platform. It does not build or deliver Marketing Mix Models. For MMM, ScanmarQED (Roivenue's parent company) provides dedicated econometric modeling (both software and consulting services). Together, ScanmarQED MMM and Roivenue MTA cover the full measurement spectrum from strategic portfolio modeling to granular campaign-level attribution.
Multi-touch attribution (MTA) assigns credit to individual touchpoints along the customer journey, giving marketing teams granular, near-real-time campaign performance data. UMM encompasses MTA but goes further: it adds marketing mix modeling for offline and long-term effects, and incrementality experiments for causal validation. Where MTA answers “which campaign drove this conversion?”, UMM answers “what is the true contribution of every channel, online, offline, and walled garden, to revenue growth?”
The entire process typically takes just a couple of days from the time you share the data access with us. The time needed depends on the scope of the implementation. If an existing MMM model is ready to import, the integration step is faster. Roivenue connects natively to Google Ads, Meta Ads, and other major platforms, which reduces data preparation time significantly. Your dedicated onboarding team guides the configuration from day one.
The Budget Optimizer turns your UMM data into forward-looking spend decisions. It uses historical performance data to forecast future marketing outcomes, surfacing trends and patterns across your channels so you can allocate budget based on what's likely to drive results, not just what worked in the past. Instead of manual budget models, you get a data-driven planning tool built directly on your unified measurement framework.
What is Unified Marketing Measurement (UMM)?
Unified Marketing Measurement (UMM) is a marketing analytics framework that combines multi-touch attribution (MTA), marketing mix modeling (MMM), and incrementality experiments into one reconciled model. Instead of running three separate methodologies that each tell a different story, UMM integrates their signals, using each method’s strengths to compensate for the others’ limitations.
MTA delivers granular, touchpoint-level attribution across the full online customer journey. MMM provides the holistic view of long-term and offline channel effects. Incrementality experiments supply the causal ground truth that validates both. UMM is the structured layer that orchestrates all three.
For enterprise and growth marketing teams, UMM closes the gap between operational attribution and strategic budget planning, delivering both the granular, creative-level detail needed to optimize day-to-day spend and the full-funnel view required to make annual investment decisions with confidence.