Data Solutions: Media Mix Modeling & Multi-Touch Attribution Models

Are you using the best measurement solution for your brand? Probably not. It's likely that your data reporting has some gaps due to attribution model inefficiencies.

MMM (marketing mix model) and MTA (multi-touch attribution) are two measurement modeling types. Both can offer unique insights into your data and will help you find the best approaches for your marketing plans. Having a fully integrated MMM/MTA model is the ideal solution for most brands.

So why is a fully integrated MMM/MTA model the right approach? Here's why it works, and how we can help.

MTA vs MMM: Maximize Results With Multiple Attribution Models

First, let's understand the differences between MMM and MTA.

A multi-touch attribution (MTA) focuses on the short-term or more immediate impact of media, primarily digital touchpoints, to drive online conversions, such as action booking or purchases. Based on the various touchpoints a consumer encounters within their journey, each touchpoint is assigned a value towards the final conversion, showing the probable consumer journey.

A marketing mix model (MMM) quantifies the sales impact of your marketing activities, based on your past marketing spend and sales. A marketing mix model can help you optimize your future spend and maximize your ROI (return on investment) by channel.

MMM and MTA work together. Consider a brand that is running multiple campaigns across several online and offline channels and markets globally. Using marketing mix modeling, the brand can assess how to best allocate its budget between all these channels globally.

With MTA, the brand can also tactically optimize each ad group, publisher, placement, keyword, or another dimension to maximize performance within each individual market, adjusting its strategies and campaigns on the fly. A single MMM/MTA approach provides a strategic top-down and tactical bottom-up single measurement solution. 

Single Solution MMM/MTA Enhances Current Work

There are several ways a single solution MTA/MMM could enhance your current work: 

• Reporting and Insights: Customizable dashboards give broader and deeper insights into performance and profitability at the weekly, monthly, and quarterly levels.
• Incrementality testing and budgets: Tests give you lots of tactical information, but usually not about the bigger strategic questions – how much to spend, on which channels, and on what brand strategy. MMM & MTA fill in these gaps and can be calibrated to incrementality testing results.
• Google Ads for budgets: Improve budgets based on custom weights through the funnel.
• Forecasts: Incorporate macroeconomics and other media channels' influence by market.

A single MMM/MTA solution is ideal for providing the most comprehensive and effective reporting. 

Strategic Top-Down Measurement

MMM is an analytics-based approach for understanding and quantifying incremental impacts. It's best for breaking down marketing efforts into pieces to see what works in highly specific ways. Key outputs include:

• Standardized dashboards for insights generation.
• Scenario planning and optimization tools for planning.
• Effectiveness of media spend and optimal marketing mix.
• Finding marketing breakdowns. 
• Identifying diminishing ROI.
• Determining lag effects.
• Measurement of upper-funnel on lower funnel media.

If you're working on developing your reporting capabilities, you're likely looking to have some specifics about your marketing and data needs. After all, good data should be able to answer your questions and enable you to solve problems. MMM can help answer the following: 

• What budget size will maximize profit or other KPIs?
• You need to increase sales by x%, what mix should you use to accomplish this goal the most efficiently?
• How do you allocate fixed marketing resources across multiple products, banners, geographies, customer segments, etc. to maximize return?
• What return will you get for different allocation scenarios of marketing spend?
• How should advertising activity be distributed over time and across geographies to maximize return?
• Does the responsiveness of one marketing vehicle change when the intensity of another vehicle changes? 
  • If so, by how much? 
  • What does it depend on?
  • What are the relationships (halo or cannibalistic) between different banners or products?
  • When you advertise Product A, does Product B benefit from it, and if yes, how much?
  • What impact does competitive advertising have on us?  
    • How can we best defend?

Tactical Bottom-Up Measurement 

Bottom-up attribution model solutions, such as MTA are focused on granular measurement of marketing. This method is used to inform tactical planning. MTA uses identity events to provide additional insight into journeys and actions. Key outputs include:

• Integration with MMM.
• Standardized dashboards for insights generation.
• Scenario planning and optimization tools for planning.
• Effectiveness and ROI of granular media tactics.
• Optimal frequencies.
• Insight into optimal customer journeys.
• Recommended next best actions.

Like MMM, MTA can help you answer questions about your data and marketing efficiency. Take the following as examples:

• What are your consumer journeys?
• What is the probability of a consumer starting their journey on a particular media channel?
• What is the probability of a consumer moving from one media channel to another?
• How do the MTA results compare to standard last-click reporting results?
• How much of organic search results and direct conversions are driven by paid media?
• If I remove a media channel, how many conversions would be lost?
• Even if ads are not being clicked on, are they still having any impact?
• If so, what is that impact?
• Should you be spending more or less in a particular channel?

Keep in mind that the loss of 3^rd-party cookies is causing disruption in bottom-up measurement. As a result, MTA will evolve to leverage new data sources, and more specific, mathematical approaches that highlight probability will become even more important for marketers. 

Takeaways

It's clear that using more than one attribution model provides the best results. Using MMM and MTA together provides a single measurement solution. MMM results show how to best allocate budget between channels and MTA results show how to tactically optimize your spend. This single solution can enhance current work by giving deeper insights into reporting, improving budget recommendations, and incorporating results into forecasting. A single solution MMM/MTA will give you all the data you need, and answer important questions you need to know to make you more efficient and maximize your efforts. 

Our performance and analytics (P&A) team can help you through onboarding, modeling approach, factors that go into modeling, forecasting, ongoing maintenance, and more. Learn more about our attribution modeling offers, Insights Dashboards, and how we can help you transition to GA4. 

Contact us to find out more.