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Marketing Mix Modelling

Project goal: Create a data-driven cross channel media plan using both online and offline user acquisition and re-engagement mediums, allocating the marketing budget effectively for the best ROAS. 

Solution: Extensive data consolidation and cleansing, and analysis. Deep dive on business logic and requirements, producing a solid set of business rules to be applied to the model. On going stakeholder management and weekly alignments to ensure the project flow. 

Impact: Wiser execution of campaign, and budget allocation, as well as an enhanced understanding of own business data and dynamics.

Key takeaways from the Marketing Mix Modelling project

Before we start, ask the following questions:
  • Is the ROI Increase Worth the Cost?

Developing and maintaining an MMM model requires resources, including data infrastructure, analytics expertise, and ongoing model tuning. Will the expected efficiency gains in budget allocation justify these costs?

  • Why Do I Need MMM?

Are you looking to increase spend on existing channels, open new channels, or optimize your current budget?
If you’re increasing spend, is there enough demand in the market that can be reached?
More importantly, is your product ready to absorb a potential increase in demand?

  • Is My Data Ready for MMM?

Is your marketing and sales data consolidated into a single, structured format?
Have you collected enough historical data to allow for meaningful analysis?

  • Have I Experimented Enough?

Have you tested different messages, audiences, and spend levels to understand channel elasticity?
Do you have enough data points to create a robust model?

  • Are My Teams Ready to Act on MMM Insights?

Can your marketing teams implement model-driven budget decisions without internal disputes over budgets?
Are there any known operational constraints that would prevent budget flexibility across funnel stages?

 
MMM is a Big Project… How to Tackle it?

If you’re ready to move forward, a structured approach is key to success. Here’s what to do next:

  • Run a Feasibility Analysis

Ensure that the expected ROI increase will justify investment in the team and infrastructure required to maintain the model.

  • Monitor External Factors & Competition

MMM relies on historical data, but market conditions evolve. Keep a close watch on competitors and economic shifts.

  • Consolidate Your Data

Ensure clean, structured, and complete datasets for accurate modeling.

  • Run Small Incremental Tests

Assess how different spend levels and messaging affect each channel’s performance.

  • Define Business Constraints Clearly

Outline and verify limitations (e.g., budget caps, funnel restrictions) before applying them in the model.

  • Structure Your Operations

Ensure that marketing teams can act on model recommendations without internal roadblocks.

Other Key Considerations

The best MMM approach depends on various factors, such as:

  • Business size and stage of growth
  • Product type and market fit
  • Channel mix and historical marketing operations
  • Annual marketing budget and brand awareness levels
  • Market size and competition dynamics

Prefer channels with lower entry and exit barriers to allow for easier budget adjustments.

Review and refresh your model regularly to prevent inefficient spending—don’t wait a year to reassess tactics!

Implementing an MMM model is just the beginning. Execution is key.

Key Challenges to Watch Out For:

  • External conditions will change

Past data won’t repeat exactly the same way. Keep a close eye on market trends.

  • Your teams need to be proactive and adaptable

If model predictions aren’t aligning with real-world results, adjust strategies quickly.

  • Monitoring is key

Build automated dashboards and real-time reporting to track deviations from expectations.

  • Get product operations right

Ensure a seamless experience between increased demand and product availability—don’t scale too fast without operational readiness.

Image from Channel Diminishing Returns testing, used to identify what is the breaking point of returns, where marketing investments produce a negative ROI.

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