The Data Science Dilemma: Should Marketers Build, Buy, or Both? [VentureBeat]


This article originally appeared on VentureBeat.

Data science, artificial intelligence, machine learning and algorithms have become the business buzzwords du jour. And with good reason. Organizations adopting data science-driven automation see up to 10x improvement in business process speed, 72 percent reduction in customer churn, and 40 percent reduction in new customer acquisition costs.

It’s the so-called sexiest field of the 21st century as both enabling technologies and brands are fighting for the top talent that will allow them to modernize and scale their marketing efforts. But much like the big data that fuels the practice, data science for marketing is challenging to get a grip on.

Having a data science team doesn’t mean that marketing gets to take advantage of the expertise. Macro level insights and micro level optimization can’t always both be a focus.

What should be built? What should be bought and managed? When do you combine building and buying?

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