Five Questions Every CMO Needs MMM to Answer

Most CMOs are flying blind on the questions that actually drive business decisions. Not the "nice to know" metrics. Not the platform dashboards that mark their own homework. The questions that determine whether finance approves next year's budget or demands 40% cuts across digital.

The problem: traditional attribution can't answer them. Last-click models miss upper-funnel effects. Platform data tells five different stories about the same spend. Spreadsheet analysis gets stale the moment market conditions shift. And you're left defending strategy with confidence intervals and caveats instead of clear numbers.

Marketing Mix Modelling (MMM) exists to solve exactly this. It's not a dashboard layer on top of your existing data. It's a completely different approach to measurement — one that works from economic fundamentals rather than platform cookies. Here are the five questions it actually answers.

1. How much of our sales is actually caused by marketing?

64% of CMOs cite proving marketing's impact on financial outcomes as their top measurement challenge. Meanwhile, 45% of CFOs decline marketing proposals because they can't see a clear line between spend and revenue.

This is the existential question. Without it, every budget conversation starts with the CFO assuming marketing is overhead. You're not debating efficiency — you're fighting for credibility.

Attribution systems try to solve this by assigning last-click credit, or spreading it across a journey. But they miss the baseline. What would revenue have been with zero marketing? How much does brand persistence drive sales weeks after a campaign ends? How much is pure seasonality versus marketing effect?

MMM answers through a decomposition chart: total sales broken into baseline sales (what you'd earn anyway) plus the incremental contribution from each channel. It's clean. It's defensible. A CFO can look at it and see exactly which marketing activities generated additional revenue versus which ones were just spending to stay even.

The chart answers the board directly: X% of our growth came from search, Y% from TV, Z% from retail media. That's the conversation you want to be having.

2. Where should we reallocate budget for maximum ROI?

This isn't "should we do more digital?" Nobody asks that anymore. The question is: should we shift the next £2 million from TV to performance? How much revenue do we lose? What's the net impact? Only 14% of CMOs actually make these allocation decisions using data.

But here's the catch: those who do are 2.6x more likely to exceed revenue targets. Data-driven allocation works. Most teams just can't do it because they lack the mechanism.

Spreadsheet modelling gets close. You calculate historical ROI and project forward. But channels interact. And market conditions change. You need something that understands real elasticity — how much additional return you actually get from incremental spend in a saturated channel versus a growing one.

MMM provides before/after allocation charts with quantified sales impact, plus what-if scenario tables. You change the budget split (say, reduce TV by £1 million, add it to digital video), and the model recalculates incremental revenue under that scenario. Not best-case estimates. Actual, cross-validated predictions based on your market data.

Then you test the scenarios against your financial goals. Does reallocating £3 million to search get you to your revenue target? What margin do you need on incremental sales? What's the risk if market demand shifts? You're making allocation decisions like a finance team should — with numbers, scenarios, and documented assumptions.

3. Which channels are saturated and which have room to grow?

Digital now accounts for 64% of FMCG spend, up from 53% three years ago. Every CMO is wondering the same thing: Is that right? Are we overweighting digital because it's easy to measure, or because it actually drives better returns? Where's the ceiling?

Most marketers understand diminishing returns conceptually. Spend a bit on search, you get high ROI. Spend a lot, you're bidding on every loose keyword and ROI collapses. But ask them to quantify where the inflection point sits for their channels, and they can't.

That's the blind spot MMM fixes. It models saturation and response curves for every channel — showing exactly where returns flatten. You can see that search works really well up to £5 million, then ROI drops 40%. Or that TV has room to grow and every additional £1 million adds 2% to baseline revenue.

These curves change with market conditions and campaign quality. An MMM model updates monthly or quarterly, so you always know if your channels are shifting. That's information your platform dashboards will never give you, because they optimize for engagement, not for your business questions.

4. How do our channels work together?

31% of senior marketers report struggling to connect data from different sources. But even if you could perfectly stitch your data, you'd still miss the biggest thing: channel synergies.

Last-click attribution actively works against you here. TV drives brand awareness and search intent, but gets no credit for the conversions it generates. So the easy move is to cut TV and pocket the savings. Meanwhile your search ROI collapses because you've cut off the top of the funnel. Now you need to increase search spend just to maintain baseline conversions. You've made a worse decision with incomplete information.

MMM models channel interaction effects and halo analysis — showing explicitly how TV lifts digital conversion, how brand campaigns increase email engagement, how awareness drives search volume. The output isn't just individual channel ROIs. It's a map of how your channels amplify each other.

This changes the entire conversation with finance. Instead of "Should we cut TV?" the question becomes "What's the cascade effect if we cut TV?" You can quantify it. And usually, the answer is that TV's true ROI is 3x higher when you account for its halo across the rest of the mix.

5. Why does every platform tell us a different ROI story?

60% of buyers cite lack of cross-network measurement standards as a barrier to better marketing efficiency. Each platform has massive financial incentive to prove it works. Google says Google works. Meta says Meta works. Amazon says Amazon works. They're all measuring with their own benchmarks against their own baselines.

You're left comparing apples to nectarines to kiwis. That's before you account for incrementality tests that run on platforms with vested interests, or attribution systems built to maximize platform credit.

The solution isn't to trust one platform more. It's to build an independent model that measures all channels on a level playing field. One system. One methodology. One baseline.

That's what MMM does. It sits outside your ad tech ecosystem. It doesn't have revenue from your spend. It measures all your channels using the same method — correlating spend changes with sales movements across a time series. Google gets the same treatment as LinkedIn. Paid social gets the same rigor as PR or email.

This independence matters hugely for credibility with finance teams. Your CFO knows that platforms have incentive conflicts. An independent model doesn't. Suddenly you have measurement they can trust.

Why this matters now

A decade ago, you could get away with defending marketing as a brand-building cost center. Margins were healthy. Growth was cheap. Finance didn't ask hard questions.

That world ended around 2022. Now every CMO budget gets stress-tested against concrete business outcomes. Your CFO wants to know ROI, payback period, and incrementality. They want to see what happens if spend is cut 20%. They want to understand trade-offs between channels.

If you can't answer these five questions with data, you're operating from a position of weakness in every budget conversation. You're defending rather than strategizing. You're hoping the committee believes in marketing rather than showing them why it works.

That's where MMM becomes essential. Not nice-to-have. Essential. It's the only measurement framework designed to answer the questions your business is actually asking.

Want to know if your data can answer these questions today? Let's talk about what MMM would look like for your business — and which of these five questions matters most right now.