Abstract
Twentieth century retail innovator John Wanamaker lamented that ‘‘Half the money I spend on advertising is wasted; the trouble is I don’t know which half.’’ This all changed radically in the opening years of the twenty first century when search giant Google applied Garfield’s [1] bibliometric tools to advertising. Google takes cues from keywords input to its core search engine, and translates these to deliver relevant ads to consumers. Facebook has extended this model, taking cues from friendship and posting networks, political views, interests, and numerous other measures of a consumer’s social life, translating these into relevant ad placements. Together these two internet giants control 40 % of the $150 billion internet advertising market, with additional share controlled by internet retailers Alibaba and Amazon. Internet retailers waste very little money, and when they do, they know about it quickly. Massive dollar flows in e-commerce have ushered in a golden age of consumer research, making available nearly limitless volumes of data on consumer interests, personalities, demographics, intentions and purchase actions all funneled through our favorite internet browsers. Machine learning, statistical analysis and graph theory have reached an unprecedented level of integration in R, Mathematica and other tools, and can reliably compute demand curves, elasticities, surpluses and other mathematical depictions of consumer behavior. Google, Facebook, Amazon and other internet firms make it a priority to share marketing data with users and researchers, offering APIs, code bases, and state-of-the-art analysis tools. The wealth of new data and tools being freely distributed to researchers should have encouraged an explosion of innovation in consumer research. So far, academe
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