Marketing Mix Modelling, with Jim Gianoglio

Episode 170

Whenever your marketing is being assessed by an analyst, they will use one of two approaches. 

The first is called Multi-touch attribution, which takes a customer who’s made a purchase decision, then puts weights on the touchpoints they had on various channels (Google calls their model ‘Data-driven attribution”) on the way to that point, to say which touchpoints were most influential. 

The other approach they may use is Media Mix Modeling. From what previous podcast guest Kevin Hartman told me about MMM, it’s a ‘tremendous undertaking.’  It involves collecting and analyzing historical data in different geographies at different times of the year: sales figures, both legacy and digital marketing channels, and external factors like economic indicators and even weather. It has its own jargon: Incrementality, ratios, betas, impact on objectives. Then there’s the math. It uses regression methods, both linear and non-linear, Frequentist vs Bayesian statistics. 

I get so overwhelmed with these modeling solutions, it’s like the old Who’s On First skit. I needed someone who would sort this out for me. 

Our guest has been a consultant in the marketing and digital analytics space for 15 years. I’m currently focusing on helping clients quantify the impact of their marketing efforts using Marketing Mix Models, experimentation, and various attribution methodologies.

He is so passionate, he started a newsletter called MMM Hub

He graduated from Carnegie Mellon with a Masters degree in Information Technology, focused on Business Intelligence & Data Analytics.

Jim is great at showcasing other people in the analytics community -He truly believes that all of us are smarter than any one of us. He, along with Simon Poulton, co-host the MeasureUp podcast

He talked with me from his home in Pittsburgh. Let’s meet Jim Gianoglio.

People/Products/Concepts Mentioned in Show

Jim’s Cauzle Analytics consultancy

The MeasureUp podcast.

John Wallace

Randomized Control Trials (RCTs)

Bayesian Statistics

Media mix modeling ratio:

  1. The Marketing Channels Being Used
  2. The Money Being Spent on Each Marketing Channel
  3. Campaign Results & Insights
I tell you, Multi-Touch Attribution isn’t real!

Episode Reboot – articles & videos shared by Jim:

What is Marketing Mix Modeling? 3 Benefits and Limitations – this is a very high-level article, explains some of the basics (but none of the ‘how-to-do-it’ pieces)

Market Mix Modeling (MMM) 101 – This is a good intro-level article highlighting the important high-level concepts of MMM

A Complete Guide to Marketing Mix Modeling – although this article/site is littered with a bunch of ads, the content is actually pretty good. It touches on the concepts as well as providing some code snippets for R, Python and SAS.

Videos / Courses to help get started with modeling:

MASS Analytics – Marketing Mix Modeling Master Classes – (free) 14 courses (YouTube videos) – very well done, starts at a beginner introduction to MMM and goes all the way through advanced modeling techniques. It’s about 3 hours in total.

Marketing Mix Modeling 101 – (free) online course (YouTube videos). This is 2.5 hours over 5 courses that focuses on MMM using Robyn, so is good if you’re comfortable using R.

Vexpower – What’s the impact of TV ads? – (free) this is a good intro into the concepts of modeling and MMM, and should only take 1-2 hours to complete 

Vexpower – Can we try Facebok Robyn? – (free) this one walks you through a complete example of using Robyn to do MMM

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