Category: Data Science
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Prejudice Against The Machine: Impact Of Chatbot Identity Disclosure
Whenever technology progresses a major question arises: What can technology do as well, or better, than humans? Since the luddites, and probably before, people reacted to technology with hostility. This raises the question whether machine learning algorithms can replicate (or outperform human behavior) but still be unpopular due to human reaction. A group of authors…
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Programmatic Media Buying And Algorithmic Purchasing
This post looks at art and science — communications and analysis — in the use of data. I also discuss programmatic Media Buying And Algorithmic Purchasing. Art And Science in Marketing Analytics Kevin Hartman, the Director of Analytics for Google, has a pleasant readable book on digital marketing analytics. (Which quite frankly you’d expect him…
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Artificial Intelligence, AI, And Marketing’s Future
Thomas Davenport and his colleagues have a recent piece in the Journal of the Academy of Marketing Science on Artificial Intelligence, AI, and Marketing’s Future. This is an eminently readable piece, which I appreciate. It lays out some issues with AI and where the marketing discipline may go. AI And Human Beings I am fascinated…
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Machine Learning And Retailing
Joseph Ryoo, Xin/Shane Wang, Praveen Kopalle and I have an article available now in the Journal of Retailing. This focuses on machine learning and retailing. It is a major question how new technology will change retail. Our work therefore tries to get a grip on this. Reviewing Machine Learning And Retailing In The Literature We…
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Advice On Data Science, It Isn’t Too Hard to Understand
Marketers should understand the data science models that are increasingly being used in the discipline. We really need good advice on data science. As such it is helpful to find simple explanations of data science models. Numsence by Annalyn Ng and Kenneth Soo is an admirable attempt to clarify basic models used in data science.…
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Finding The Right Marketing Metrics
It is extremely challenging to get marketing metrics pieces published at top marketing journals. Indeed, a piece on finding the right marketing metrics isn’t a typical article. One challenge is that often journals want something “new”. Investigating what managers do doesn’t seem new enough. This is a real shame. I worry editorial decisions encourage the…
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Creating Stories With Data Visualizations
Cole Nussbaumer Knaflic has a useful book — Storytelling with Data. This contains lots of good advice on Creating Stories With Data Visualizations and generally improving data visualization. She tries to ensure the reader does not lazily follow the first thing a software (e.g., Excel) recommends. This is important, she gives many examples in the…
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Marketing Metrics Must Add Up
Marketing metrics can get a bad reputation. This sometimes for good reason. A key, unsurprising, idea is that marketing metrics must add up. To Build Trust Marketing Metrics Must Add Up Kevin Lindsay discussed why this is: why do marketers (and people working with marketers) sometimes lack trust in the numbers they are being given?…
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Personalization In A World Of Artificial Intelligence
V. Kumar and his colleagues examine what Artificial Intelligence (AI) is doing to the world of marketing in their recent piece in the California Management Review. What is the future of artificial intelligence and personalization? Artificial Intelligence And Personalization Versus Customization Central to their analysis is the idea of personalization. They distinguish this from customization.…
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Bias And Algorithms
As algorithms play greater and greater roles in our lives a reasonable question is: “are they fair?” The answer is often; “no, not really”. To be clear that doesn’t necessarily mean algorithms are making the world worse. If things were unfair before (and they were) then just knowing that things are unfair now can’t tell…
