The L’Oréal Professorship in Creativity Marketing stole a page from Google’s recipe book, organizing a Big Data Marketing Challenge for students from ESCP’s dedicated Master to see how marketers can use Big Data to develop new products.

The Big Data Marketing Challenge was run in June 2018 by L’Oréal Professor in Creativity Marketing Ben Voyer in conjunction with Wei Zhou, Professor in Information & Operations Management and Academic Director of the Master of science in Big Data and Business Analytics (MBD) at ESCP, and Stephan Glasser, International innovation director, Haircolor, at L'Oréal Group. The objective was for 40 students from the school’s MBD to use their expertise to work on defining what a “smart shampoo” could be like, and come up with recommendations.

The project was an introduction to contemporary marketing issues and how big data can help marketers. It proposed to students who have developed an expertise in data analysis and big data, to reflect on the innovation produced through the prism of data analysis. More specifically, students were asked to imagine the “shampoo of tomorrow” using existing data on the Internet that can be collected and analysed automatically, for example by an algorithm.

Inspired by Google’s “perfect” cookie recipe

The Big Data Marketing Challenge drew on Google, which used Bayesian Optimisation to create a smart cookie with ingredients as variables: type of chocolate; quantity of sugar, flour, vanilla, etc. Artificial intelligence came up with recipes, which Google employees tried and rated.

Google's smart cookie recipe © Google

 

This project was meant to dive into the future of new product development, by reflecting on a series of questions related to big data and artificial intelligence:

  • How can marketers leverage on big data and already available forms of data analytics (Google, Facebook, etc.) to better understand current and future product preferences and buying behaviours?
  • How can marketers use these inputs to develop new products?
  • Are data-driven, algorithm-created products a possibility?
  • How can we detect weak signals and anticipate trends before they emerge?

“This shows a different side of the use of big data analytics: the before - designing tools to harness data - and the after: feeding results in the product development stage, sums up Ben Voyer. It also creates awareness around L’Oréal and marketing as a potential industry for big data graduates”.

What the next steps could be:

  • Repeat the assignment/use another product category to generate new outputs.
  • Organise a joint-assignment/collaboration with ESCP’s MSc in Marketing & Creativity (MMK).
  • Work with existing datasets to increase inputs.
  • Organise a competition with other schools on this topic.