MMM vs Attribution: What's the Difference?

The short answer

MMM measures long-term, aggregate impact of marketing across all channels. Attribution tracks individual user journeys in digital channels. Different tools for different questions.

Marketing Mix Modelling works with statistical regression. It looks at total marketing spend by channel and correlates it with business outcomes: sales, revenue, signups. It's asking "when we increased TV spend by 20%, what happened to sales?" Attribution works with user-level tracking. It follows a person from their first touchpoint through to conversion. It's asking "which touchpoint deserves credit for this sale?"

The tools answer different questions. That's why good marketing teams use both.

What MMM does well

Measures everything together. MMM works with online and offline channels in the same model. TV, radio, print, search, social, email, influencer, retail. You're seeing the full picture of how channels work together, not just the digital stuff.

Doesn't need user-level tracking. Attribution needs cookies or ID matching. It breaks when you can't track users. MMM works with aggregated data. You don't need to know who clicked what. You just need weekly spend data and sales data. This is table stakes for MMM.

Works with privacy restrictions. As first-party cookies disappear, attribution gets harder. Apple's ATT broke iOS tracking in 2021. Privacy regulations make third-party data riskier. MMM doesn't care about any of this. It works with whatever privacy environment you're in.

Shows diminishing returns. MMM models the curve of effectiveness. Doubling ad spend doesn't double sales. The curve flattens. That's crucial for budget allocation because it tells you where to shift money for maximum impact. Attribution can't show you this. It just distributes credit across channels.

Good for budget allocation across channels. You can use MMM to answer: "If I had £1 million to spend across TV, search, social, and email, how should I split it?" That's the core question of marketing strategy. MMM answers it empirically.

What attribution does well

Real-time. Attribution updates as conversions happen. You can see today which campaigns are converting. With MMM, you get results quarterly or annually. When you need to make immediate decisions about where to spend next month's budget, attribution is faster.

Granular. Attribution works at campaign, creative, and audience level. You can see which specific ad performed better, which audience segment converts best. MMM works at channel level. You get "search is worth £2.50 per £1 spent" but not "Adset A is better than Adset B".

Good for in-flight optimisation. If a campaign isn't converting, attribution tells you immediately. You can pause it, reallocate budget, test a new creative. This is daily work. MMM is too slow for this.

Shows the path to conversion. You can see the sequence of touchpoints that led to a sale. Did they see a display ad, then search? Or social, then email? This tells you about user journey and which channels work together.

Where each one falls short

MMM limitations: Slow refresh cycles (traditionally). The standard is quarterly reporting. Can't tell you which creative worked. MMM tells you "search was effective" but not "which search ad performed best". Works at channel level, not campaign level.

Attribution limitations: Can't measure TV, OOH, print, or any offline channel. Breaks with cookie deprecation. As third-party cookies disappear, attribution becomes less reliable. Last-click bias: all credit goes to the final touchpoint, ignoring everything that led to it. Not all channels have good attribution (brand awareness is notoriously hard to attribute).

Why cookie deprecation changes the equation

As third-party cookies disappear, attribution becomes increasingly unreliable. Google's Privacy Sandbox is trying to fix this with Topics and Fledge, but the tracking environment is fundamentally degraded compared to five years ago.

MMM doesn't depend on cookies. It works with or without them. This is why interest in MMM has surged since 2023. As attribution gets noisier, MMM becomes more valuable. It's not that attribution is going away. It's that its limitations are becoming clearer.

Smart marketing teams acknowledge this. They're building MMM capability not because attribution is useless, but because attribution alone isn't enough anymore.

The practical answer

Use both. Not as competing tools but as complementary ones.

Use MMM for strategic budget allocation across channels. Run it quarterly. Build a model once and maintain it. Feed the results into your annual planning. "If we want to grow revenue 15%, here's how to reweight the channel spend."

Use attribution for tactical optimisation within digital. Run it continuously. Every week, look at what converted. Pause underperformers. Scale winners. Test new creatives.

MMM answers the big questions. Attribution answers the small ones. You need both.