Advertising over Time: Interactive Machine Learning for Image Data Analysis

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Advertising is omnipresent in all societies around the world and has a strong influence on human behavior. Today, companies such as L'Oréal, Pfizer, Procter & Gamble and Kraft Heinz together spend more than $2 billion a year on print ads in magazines. Past research has shown various effects of advertising (e.g. on sales, brand loyalty, market-share stability etc.). However, in addition to the level of advertising spending, the actual content and style of advertising is also crucial. This is something that the existing economics and management literature has widely neglected.With big data and todays increasing computing power at hand we have an enabler ready to fill this research gap. To be more precise, we possess a set of more than 1 Mio print ads from 1843 up to today. We propose to apply Machine Learning and Artificial Intelligence techniques to extract relevant features from the ads and use them to identify patterns in the content and style of the advertisements.Our research project consists of two main pillars: One of them is to derive design knowledge from the development of an "Interactive Machine Learning System". This system consists of two components: "Interactive Labeling" and "Interactive Analytics". The interaction is intended to create a system that directly involves the user in the learning and analysis process and is designed to meet the user's needs. The other pillar of our proposed research project consists of using the developed system to generate new insights in advertising research. Questions that we will answer are: How have print advertisements changed over time, especially with regard to ad text, ad image characteristics and ad complexity? How far are these changes related to external events that increase consumers' speed of life?