Comparing Marketing Mix Modelling Providers in the UK

Every advertiser we talk to is running some version of an MMM procurement conversation. The market has expanded so quickly that "compare three MMM vendors" is now a substantial project in itself. This is the framework we use when we help clients navigate it - and, occasionally, when we sit on the other side of the table.

The five dimensions that matter

Ignore logos, case studies and slide count. There are five things that actually predict whether an MMM engagement will produce decisions.

### 1. Methodology

Ask to see the model, not the dashboard. A serious provider should be able to walk you through:

• The functional form (linear, log-log, Bayesian hierarchical)
• Adstock and saturation assumptions per channel
• Priors and where they come from (industry, previous builds, experiments)
• Out-of-sample validation approach and current fit
• How multicollinearity is handled

"We use AI" is not a methodology. Neither is "our proprietary approach". If the team can't explain their maths, they can't defend the output.

### 2. Refresh cadence

The right cadence is monthly for most advertisers, weekly for a few, quarterly for none. A model that refreshes annually is a reporting deliverable, not a measurement tool. Ask how long a refresh takes end-to-end, including data updates, and ask to see the automation.

If the honest answer is "six to eight weeks", the model will not inform in-year decisions.

### 3. Calibration and validation

Any MMM is a set of statistical assumptions. Those assumptions need external validation:

• Geo lift tests to calibrate media channel elasticities
• Platform-run incrementality studies for digital
• Historical experiment results priced into priors
• Out-of-sample holdouts to test predictive accuracy

A vendor that treats their model as self-validating is asking for trust they haven't earned.

### 4. Ownership and handover

At the end of the engagement, who owns the model, the code, and the data pipelines? A partner that keeps everything inside their walled garden has sold you a subscription, not measurement.

The right shape is: the model lives in your cloud, in your code repository, on your data. The vendor brings the rigour and the review cycle; the knowledge accrues to your team. This is uncomfortable for vendors used to lock-in economics - and it's the single fastest way to tell serious partners from professional-services shops.

### 5. Independence

Ask directly: does the vendor benefit from the answer? Any provider that is also selling media, or that has a preferred platform partnership, has a conflict of interest that needs to be disclosed. It doesn't necessarily disqualify them, but it does change how you should read the output.

A short scoring framework

Score each vendor 1-5 on each dimension:

• Methodology - can they defend every assumption?
• Cadence - can they refresh in under a month?
• Calibration - do they use experiments and lift studies?
• Ownership - do you own the model at the end?
• Independence - are they conflict-free?

A total of 20+ is a serious partner. Anything below 15 is a dashboard vendor. Between 15 and 20, dig deeper on whichever dimension scored lowest.

The three questions we recommend asking every finalist

1. "Can you show me the last model you built, end-to-end?" - Real teams have permission to demo real work.
2. "How many of your MMM engagements led to a budget reallocation in the last twelve months?" - This is the only KPI that matters.
3. "What happens on day one after our contract ends?" - The honest answer tells you whether you are buying measurement or renting it.

That's the framework. If you want a facilitated conversation walking through your specific shortlist - vendor-neutral, no pitch at the end - our Clarity Score call is the fastest way to do it.