New York, NY and London, UK – May 4, 2023 – Dr Peter Cain’s latest research piece was published in the 4th Issue of I-COM’s Frontiers of Marketing – Data Science Journal. In the editorial, Dr Cain first provides a point-of-view around the application of AI in the MMM context and suggests caution in using it as a tool for causal analysis and parameter identification. The core paper, titled “Attribution and the Marketing Mix Model”, which Dr Cain wrote in collaboration with Nitesh Sahay, then dives into the resurgence of MMM as a marketing attribution tool following the recent setbacks suffered by MTA due to stricter data privacy regulations and the imminent abolition of third-party cookies. However, to be useful in a post-MTA world any ‘next generation’ MMM framework needs to deliver on three fundamental business issues.
Firstly, to serve as a true attribution solution, MMM needs to focus on causal estimation methods. Too often we see reliance on consumer journey solutions to address the problems of last-touch attribution. However, these ignore the critical issues of selection bias endemic in much online media – leading to endogeneity bias and misallocation of the marketing mix. The growing popularity of automated machine learning approaches to the mix model only serve to exacerbate this problem, where the focus is on prediction not causation.
Secondly, MMM needs to quantify the long-term (base building) effects of marketing and so inform brand-building strategy. Standard approaches are simply not set up to measure these effects, with fixed baselines and a focus on short to medium-term lag structures or Adstocks. Alternative time series structures are required that can quantify both short and long-term (base) variation – coupled with dynamic network models that can explain the causes of base variation and the economics of brand-building.
Finally, next-generation MMM needs to fill the gap left in a cookie-less world to deliver granular and swift insights on marketing ROI and optimal budget allocation. Suitably identified high dimension mix models – across consumer cohorts by day or hour – can fit the bill. This can provide many of the claimed benefits of MTA such as granular online media effectiveness ranking by publisher and placement with the added benefit of quantifying the contribution of pricing and offline media, controlling for the wider economic environment and the ability to analyze brand building.
Read the full paper here.
About Peter Cain
Peter Cain is executive partner and co-founder of Marketscience, an award-winning marketing effectiveness agency. He is widely known for championing the use of dynamic modeling techniques to capture both short- and long-term marketing effects and measure the long term effect of marketing strategy on brand sales. Peter was the original founder of Marketscience, which he established in 2012 with the goal of blending academic, commercially relevant analytics and strategic advice for business. He has more than 20 years of commercial and academic experience in economics and marketing science designing econometric business solutions for blue-chip companies and organizations. Dr. Cain has experience consulting across a wide range of industries and writes extensively on economics and econometrics in marketing. He regularly publishes in top peer-reviewed journals. Before marketing research, Dr. Cain was in academia, specializing in monetary economics and econometrics. He holds BSc and MSc degrees in Economics from the University of Warwick, and a PhD in Monetary Economics from the University of Nottingham.
About Nitesh Sahay
Nitesh Sahay brings almost 20 years of experience in advanced analytics, consulting and research to Marketscience. He has long been engaged with cutting-edge innovations in analytics and their implementation. With an advanced programming background, Mr. Sahay has developed analytical software and built highly customized tools that are efficient, user-friendly and robust. Several of these continue to serve as platforms for building marketing analytics models globally. Mr. Sahay’s sector expertise includes FMCG, ecommerce, automotive, pharmaceutical, telecoms and banking, and he has worked across several other domains. In addition to seven years at Ninah Consulting, Mr. Sahay’s background includes senior management positions at Symphony Marketing Solutions, Datamonitor PLC and GE Capital. He is a published expert in advanced marketing analytics and won a Bronze “Emvie” award for analytics from The AdClub. Mr. Sahay earned an MPhil in Economics from Jawaharlal Nehru University, Delhi, where he also received a Master’s in Economics. His academic papers have been published worldwide.