The Biggest Barrier to Accurate MMM? Your Messy Data

Marketers are leaning into MMM as a way to measure the incremental impact of all channels, even those hard to track through clicks.

The good news? MMM is more accessible than ever, thanks to open-source tools like PyMC, Meta’s Robyn, and Google’s Meridian.

The bad news? Most brands aren’t ready, and the problem isn’t the modeling itself. It’s the messy, incomplete, inconsistent data they’re feeding into it.

We’ve seen it time and time again, the biggest blocker is almost always data quality and readiness. Let’s dive into a few tips and tricks to get your data where it needs to be.

MMM is not about fancy math; it’s about clean inputs. To run even a basic MMM, you’ll need:

Yes, you can add more variables over time, but these are table stakes. The models themselves are open-source and well-documented. The real challenge is gathering and structuring your data properly.

It’s shockingly common for critical pieces of data to be lost:

Even one missing quarter can hurt your ability to generate reliable insights.

Even when data exists, inconsistent structure can make it unusable:

MMM requires spend and results to be broken out consistently by channel, tactic, and funnel stage.

Sometimes everyone thinks the data exists but no one actually has it:

These access gaps can take weeks (or months) to untangle.

Brands often obsess over which MMM package to use or which Bayesian priors to tune.
But here’s the reality: Even the most sophisticated model can’t fix garbage input data.

Start with clean, consistent, well-structured data, and even a basic model can produce actionable insights.

Centralize your data
Even if you don’t have a full data warehouse, build a shared sheet or dashboard that lists platforms, KPIs, and access owners.

Standardize definitions
Document what counts as a conversion, how revenue is calculated, and how funnel stages are defined and apply them consistently.

Track external factors
Log promotions, product launches, and other one-off events so your model can account for them.

Automate where possible
If you have the tech, set up automated daily exports to your warehouse or cloud storage.

Make data ownership a priority
Assign clear owners to each platform and hold them accountable for maintaining access and hygiene.

For one client, simply cleaning up inconsistent campaign names, recovering missing spend data, and separating branded/non-branded search improved model fit by 30%, unlocking actionable budget reallocations within weeks.

MMM is a powerful way to understand the true impact of your media mix but it starts with clean, complete, accessible data.

Need help untangling your data? Reach out to us. At fusepoint, we’ve seen (and fixed) it all.