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How marketing mix modeling should guide your budget allocation decisions
Most marketing leaders have more data than they know what to do with, and still can't say where the next dollar should go. A six-step framework for turning MMM output into a budget decision your CFO will back.
Pranav Piyush
Co-founder, CEO
How marketing mix modeling should guide your budget allocation decisions
Marketing leaders rarely struggle because they don't have enough data.
Between platform dashboards and attribution reports, most marketers have more data than they know what to do with. Yet somehow, after reviewing it all, they still struggle to answer one of the most important questions in the job:
Where should the next marketing dollar go?
Understanding what happened is only the first step. Deciding what to do next is much harder.
Marketing Mix Modeling (MMM) helps inform that decision by estimating the incremental contribution of different marketing channels and forecasting how changes in investment are likely to affect business outcomes.
But statistical models don’t allocate budgets. People do. And when they do, having a repeatable decision-making process increases the likelihood of getting it right. Here’s the framework we recommend.
Step 1: Understand contribution, efficiency, and saturation by channel
Before defining a new budget, look at the data to understand how the current one is performing.
Start by looking at each channel’s contribution to the business outcome you care about, whether that is pipeline, revenue, qualified traffic, or any other metric marketing is responsible for influencing.
But contribution only tells part of the story. A channel might be responsible for a large share of results simply because it receives a large share of the budget. To understand whether it deserves more investment, you also need to look at efficiency: the incremental impact generated relative to the amount spent. Now you can identify where increasing investment may create more value and where it may make sense to invest less.
The final piece is understanding saturation. A channel may perform well today but have limited room left to grow. Take search: if available keyword demand is already being captured, increasing spend further won’t necessarily result in proportional growth. The easiest way to waste budget is to keep investing in a channel that's already done most of the work it can do.
Together, contribution, efficiency, and saturation give you the foundation for deciding how your budget should change.
Step 2: Use a scenario planner to recommend ideal allocation per channel
Once you understand how each channel is performing, the next question is: how should the new budget be allocated differently?
Paramark, like most MMM platforms, comes with a scenario planning (aka budget optimization) tool. These scenario planners use the data from the previous step to recommend how your budget should be allocated across channels to improve business outcomes.
It allows you to visualize your saturation curves per channel, exclude any outliers, set manual guardrails around max/min budget allocation to optimize media spend under realistic operational bounds.
Step 3: Get a human in the loop
Don’t take the optimizer's recommendation as the final answer. An optimizer doesn't know your team just launched a direct mail campaign, or that legal hasn't cleared next month's creative. You do.
So adjust its recommendations in two ways:
Firstly, set or tweak guardrails for channels that have no more room left to grow. Imagine the model suggests sending direct mail more often. If your team knows it’s already at the highest frequency, that should be adjusted in the model.
Secondly, incorporate testing recommendations that are already planned or underway. These should influence budget decisions instead of being treated as a separate activity.
These adjustments ensure the final recommendation reflects both the data and the reality of running a marketing organization.
Step 4: Finalize the budget
Once you've incorporated business constraints and ongoing experiments, you have a budget recommendation ready to present to your CFO. But avoid walking into the conversation with only one number. Build it out the way you'd build any budget case for finance:
Start with historical data (what you spent, on what, and what it drove). This helps them understand the reasoning behind your recommendation.
Present multiple scenarios, not one. A best case, a worst case, and a base case give finance something to negotiate around instead of something to simply reject.
Where you have it, back your recommendation with testing data. A model's estimate is stronger when there's an experiment behind it confirming the direction.
Step 5: Compare actual performance vs. forecast
A budget recommendation is a prediction: based on the available data, this is where we expect the next dollar to have the biggest impact. But we still need to check how those predictions hold up once the budget is deployed.
Did results align with expectations, or were there gaps? Did any channel perform differently than the model expected? The answers to these questions provide important feedback about your marketing performance as well as the quality of your underlying assumptions. Over time, this feedback helps improve future decisions.
Step 6: Rinse and repeat
Historically, companies treated MMM as a one-off exercise: build a model, deliver a report, adjust the budget. Revisit it in months (or next year).
Modern marketing moves too quickly for that approach.
Refresh the model as new data comes in. Feed new experiments into the next planning cycle. Let incrementality testing results flow back into the model so your assumptions keep getting checked, and your forecasts keep getting better.
Do that consistently, and every budgeting cycle builds on what you learned in the last one.
That's ultimately where Marketing Mix Modeling delivers its greatest value — as a system for helping marketers make better decisions every time they need to answer one of the most important questions in marketing:
Where should the next marketing dollar go?
At Paramark, we help marketing teams turn MMM insights into budget decisions, combining measurement, optimization, and experimentation into a continuous planning process. If you're curious what that would look like for your organization, let's talk.
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