Understanding the difference between Digital Attribution and Media Mix Modeling

Media Mix Modeling

With that said, MMM does have its limitations, namely:

Attribution Modeling

  • Identify the most influential conversion points in a consumer’s digital journey.
  • Utilize an advanced algorithmic approach to evaluate performance and automatically update results.
  • Understand with precision how media assets performed along the conversion path.
  • Enable intelligent optimization recommendations, such as how should marketers shift budget by tactic, ad group (SEM), publisher (display), placement (display), keyword (SEM), etc.
  • Allow for scenario planning and forecasting (e.g. what the expected KPI return will be if budget is shifted between channels).
  • Directionally assess the impact of digital efforts.
  • Allow marketers to integrate learnings and recommendations with DSPs (Demand Side Platforms) and DMPs (Data Management Platforms).

Attribution Modeling also has its potential limitations based on the solution/provider chosen, including:

  • Offline partnerships may offer limited match rates, where offline data is matched to an internal data pool, depending on the particular vertical.
  • Certain pathing approaches may add bias to results. Last touch and first touch models are considered inaccurate by many experts today as they are subjective and do not take into account the multiple interactions consumers have with a brand.
  • In many cases, results may not account for missing critical offline influences, such as in-person referrals.
  • Weighting assumptions (if the methodology is subjective and/or not holistic) may bias the results.

Summary

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I enjoy creating content, solving problems, sharing knowledge, learning about our world and celebrating others. Learn more at www.benhinson.com

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Ben Hinson

Ben Hinson

I enjoy creating content, solving problems, sharing knowledge, learning about our world and celebrating others. Learn more at www.benhinson.com