Marketing Mix Modeling, Media Mix Modeling, Marketing Effectiveness, Experimentation, Causal Inference, Adstock, Marketing ROI, Statistics, Machine Learning, Marketing Attribution, Media Planning, Marketing Budget Optimization, Robyn, Multi touch Attribution, First Party Data, Privacy Proof Marketing Solutions.
Why MMM Needs Innovation

Why MMM Needs Innovation

MMM is not new. CPG/FMCG domain has been adopting MMM for nearly 30 years.

The statistical methodology behind it, is proven and time tested.

Why then should one innovate ?

Through this post, I would like explain why.

🎯 Reason 1: MMM is being adopted by new domains.

There has been increasing adoption of MMM by new domains like digital first brands. The problems faced by established brands vs newer brands are different and so are the data collection processes.

Most modern brands collect data at a much faster cadence and advertise at a faster cadence. Some of the old MMM methods do not work in capturing the right ROI at the campaign level.

So, we have innovatively utilized concepts like SHAP value to answer which creatives/campaigns most effectively drive sales through a particular marketing medium.

🎯 Reason 2: New media channels

With digital advertisement on the rise, specially in the form of podcasts, reels etc., the old methods like print, OOH are no longer staple for many brands.
These newer ad formats need more modern approaches to solve the ROI problem.

🎯 Reason 3: The increased focus on accountability on marketing.

Most brands/organizations nowadays, are required to internally prove that their marketing efforts have worked. So, we have leveraged causal methods like Difference-in-difference to causally prove that the marketing efforts work.

🎯 Reason 4: Availability of better and efficient methods

MMM can’t be fully automated. But we can leverage techniques from other fields. We can utilize Machine learning algorithms to hasten hyper-parameter tuning which in turn can lead to faster parameter estimation.

In summary: Innovation overall makes the Marketing Measurement more robust and trustworthy.

Link to our innovative MMM methods in the resources section.

Resources:

Link to posts on our innovative MMM methods:

https://www.linkedin.com/posts/ridhima-kumar7_cracking-the-granularity-problem-in-mmm-activity-7135613763096870912-MAne?utm_source=share&utm_medium=member_desktop

https://www.linkedin.com/posts/ridhima-kumar7_marketingmixmodeling-marketingattribution-activity-7119672601920114688-h-Fb?utm_source=share&utm_medium=member_desktop

https://www.linkedin.com/posts/ridhima-kumar7_granger-causality-a-possible-feature-selection-activity-7117840404351250433-TrhB?utm_source=share&utm_medium=member_desktop

https://www.linkedin.com/posts/ridhima-kumar7_proving-efficacy-of-mmm-through-difference-activity-7116043248753659904-jdkw?utm_source=share&utm_medium=member_desktop

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