MMM vs Attribution vs MTA
How Marketing Measurement Methods Compare
There isn't one single way to measure marketing effectiveness - different methods answer different questions, at different levels of accuracy, with different blind spots. Here's how the main approaches compare.
Last-Click Attribution
Credits the single last touchpoint a customer clicked before converting. It's digital-only, simple to set up, but ignores offline media entirely and can't account for view-through or upper-funnel influence. Read more →
Multi-Touch Attribution (MTA)
Distributes credit across multiple digital touchpoints in the customer journey at the individual user level. It's an improvement over last-click for digital channels, but it's constrained by cookie deprecation and privacy regulation, and it still doesn't cover offline media. Read more →
Marketing Mix Modeling (MMM) - Causal
A statistical, causal model built on aggregate data rather than individual user tracking. Because it doesn't rely on cookies or clicks, causal MMM can measure every channel - including TV, OOH, radio and print - alongside digital, and it's designed to answer incrementality and saturation questions that attribution can't. Read more →
Platform-Native / Built-In MMM
An MMM model provided by a media platform itself, built into that platform's own reporting. Because the model is run by the same company selling the media, it's inherently vendor-dependent rather than neutral, and it tends to be structurally biased toward attributing more credit to that platform's own channels. Read more →
| Approach | Channel Coverage | Causal or Correlational | Cookie / Privacy Dependency | Measurement Level | Best For |
|---|---|---|---|---|---|
| Last-Click Attribution | Online only | Correlational | High (cookies/clicks) | User-level | Simple digital campaigns with short funnels |
| Multi-Touch Attribution | Online only | Correlational | High, restricted by privacy rules | User-level | Multi-channel digital journeys |
| Causal MMM | Online + Offline | Causal | None (aggregate, privacy-safe) | Aggregate | Full media mix incl. TV/OOH/radio/print, budget optimization |
| Platform-Native MMM | Usually limited to that platform's own channels | Causal (vendor-run) | Low (aggregate) but vendor-controlled methodology | Aggregate | Quick in-platform view of that platform's own channels |
Where Animo Fits
Animo builds causal, vendor-neutral Marketing Mix Modeling that measures every channel - offline and online - together in one model, at 15-minute resolution, without relying on cookies or user-level tracking. Because it isn't tied to any single media platform, Animo's MMM gives a neutral, cross-channel view built specifically to guide budget decisions across the entire media mix.
Frequently Asked Questions
Is MMM better than attribution?
They answer different questions. Attribution shows which touchpoints a converting user interacted with; MMM measures the incremental, causal contribution of each channel to overall results, including channels attribution can't track at all, like TV and OOH.
Can MMM measure offline media?
Yes - that's one of MMM's core strengths. Because it's based on aggregate campaign delivery and results data rather than individual clicks, causal MMM can measure TV, OOH, radio and print alongside digital channels in the same model.
MMM vs MTA - what's the difference?
MTA distributes attribution credit across digital touchpoints at the user level and is constrained by cookies and privacy rules. MMM uses aggregate, causal statistical modeling that works across both online and offline channels without relying on user-level tracking.
What is platform-native MMM?
It's an MMM model built and run by a media platform itself, inside that platform's own reporting tools. Because the same company both sells the media and measures its impact, platform-native MMM is inherently not vendor-neutral.