Marketing Mix Modeling: how data helps brands grow

In a world where marketing budgets are counted down to the last cent, businesses are looking for smarter ways to invest. One such approach is Marketing Mix Modeling (MMM).

Yana Fareniuk, PhD in Economics, Head of MADLAB and Chief Data Science & R&D Officer at Razom Group, shared in a column for Vector how MMM supports marketing planning, along with case studies from pharma, FMCG, finance, retail, and e-commerce.

How MMM helps businesses

The marketing environment is constantly changing—new channels, trends, and consumer behaviors. Legacy planning methods often fall short. MMM reveals what truly works and what simply burns money.

The method analyzes how factors—advertising, price, distribution, seasonality, on-shelf availability, competitor activity, even weather—affect key business metrics. Based on these data, you can forecast, optimize budgets, and build effective media strategies.

MMM lets you not only track how results shift under different factors but also simulate scenarios. For example: what happens if you reduce TV spend and reallocate to digital? How much do you need to invest in communications to grow sales by 10%?

It answers questions such as: “What if we increase or decrease budget?” and “How should we split spend across channels?” Instead of focusing on TRPs, reach, or SOV alone, MMM centers on business outcomes: traffic, calls, sales, market share. As a result, strategies become more effective, precise, and agile. Businesses see what truly drives success and can react quickly to change.

What MMM enables

  • Clarity on what drives the business. Identify which factors influence sales and how much each contributes.
  • Channel ROMI assessment. See which media work best—and which waste money.
  • Stronger media strategy. Recommendations on where and how much to invest for maximum effect both strategically and short term.
  • Scenario forecasting. What if you increase advertising by 20%? What sales will you get by changing your campaign plan? MMM answers with data.
  • Creative wear-out assessment. How long does your message remain effective, and when should you refresh it?
  • Factor interactions. If the product isn’t on shelf, ads may underperform. MMM accounts for this to maximize results.
  • Competition & SOV. Understand how competitor activity affects your ads and whether you need to “speak” more often than others.
  • Halo effects. If you advertise one product, does it lift others in your portfolio?
  • Seasonal budget planning. See how effectiveness shifts by month to optimize allocation.
  • Campaign architecture optimization. How long to stay on air, when to pause, and how many flight weeks to run.
  • Price elasticity. How price changes impact sales, and what distribution recommendations to apply.
  • Portfolio & regional strategy. Manage not just one product, but an entire portfolio and regions.

MMM in real cases

  • Retail: We built models showing how online and offline traffic drive sales. The client reallocated budget across channels and formats, boosting ROMI by 40%.
  • Pharma: Portfolio-level models helped optimize total company sales by 5%. We uncovered seasonal ROI patterns, the best campaign architectures, and how price affects media efficiency—balancing the mix for a more strategic approach.
  • FMCG: We found a strong link between distribution and ad ROI. Narrowing campaigns to regions with >60% distribution increased ROMI by ~70%.
  • Finance: MMM identified the best days and hours for advertising. Reallocating activity improved media returns by 58%. This case won a WARC Media Awards accolade in 2019 for Best Use of Data.

Overall, with a robust MMM model you can use budget far more efficiently—either achieving better results with the same spend or calculating and allocating an optimal budget to hit your KPIs. The finished model is integrated into marketing plans to continuously adjust budgets, channels, and tactics, and to build scenarios that forecast business outcomes. Our team, for instance, has integrated MMM into the Brand Control Panel—an interactive reporting system that helps manage marketing and respond quickly to change.

Important nuances

  • Data quality is critical. You need detailed information on budgets, channels, launch dates, promotions, prices—everything that might affect results. Poor or insufficient data will produce an unreliable picture.
  • Hypotheses matter. MMM isn’t a black box; its effectiveness depends heavily on the team’s experience. Choose a partner who can build models and understands the business context objectively.
  • Be ready to challenge assumptions. Modeling may recommend shortening campaigns or radically changing the mix. Often, these non-obvious shifts drive the best outcomes. Embrace change and break stereotypes.

The experience of Ukrainian and international clients confirms it: used correctly, MMM increases the effectiveness of marketing investments.