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What Will Big Data Mean for Marketers?

It was no surprise that “big data” emerged as a priority topic for scholarly research in a recent survey of Marketing Science Institute company members. Marketers have always been at the forefront of using the big data of their day, beginning with the mailing lists and targeted catalogs of Montgomery Ward and Sears and the early IRI/Nielsen scanner data.

History suggests that marketers should be, once more, the drivers of their firms’ efforts to exploit data for customer insights and offerings. But will they meet the expectation? Today’s big data poses a new challenge, one that does not build on the skills that have been refined in past decades of training in the marketing discipline.

Historically, marketing research handled stocks, not flows, notes MSI Executive Director John Deighton. Researchers analyzed relatively small samples of data in batches. They modeled the batches, estimated model parameters, tested them on hold-out samples, and then applied the parameters to new batches to make new resource allocations. “It was a relatively leisurely process, and not entirely trustworthy in turbulent environments. Now, with massive streams of information flowing continuously, firms want methods that can cope with the turbulence. They can’t tolerate pilots who close their eyes periodically to process information. They want pilots that have their eyes open all the time.”

With massive streams of information flowing continuously, firms want methods that can cope with the turbulence.

Some firms are turning to entirely new approaches like machine learning and data visualization to harness the potential of the unstructured data generated by websites, social platforms, and mobile devices. But their efforts can be hampered by legacy systems and IT infrastructures ill-suited to real-time integration and processing of information from disparate sources. For many firms, big data compounds an ongoing problem. As one member put it, “The difficulty of integrating datasets is huge: we’re not handling our ‘little data’ all that well.”

Marketers also need new decision support systems, and must incorporate these systems into existing customer relationship management systems. “Managing and analyzing data quickly become more important than that last 1% of accuracy,” one executive notes. “We need fast, heuristic approaches that work moderately well, but in real time.”

The danger is that software engineers, rather than marketers, will increasingly shape the customer experience.

Finally, big data raises an anxiety-provoking question: Will it challenge the traditional role of marketing as an independent business function? Many new-generation marketing and media enterprises were founded and are led by software engineers, who embed marketing strategies directly into code, rely on machines to discern consumer tastes, and infer brand sentiment from the digital traffic on social media.

The danger is that software engineers, rather than marketers, will increasingly shape the customer experience. Says Deighton: “By the time that marketing gets to comment on the service offering at Amazon, Twitter, or Spotify, engineers may have already made most of the key marketing decisions.”

Known for their abilities as data gatherers and interpreters, marketers are now challenged to act as leaders as well. Will they lead firms to the holy grail of big data: richer, faster customer insights generating more-targeted offerings more quickly? That remains to be seen. To equip marketing to deal with these new realities, MSI will support research that draws on disciplines once seen as “adjacent” to marketing: organizational behavior, systems engineering and user interface design, information technology, machine learning, data mining, artificial intelligence, and operations research.

In addition to deepening their analytical skills, marketers will need “wisdom, charisma, and political adroitness” to be consumer insight leaders within their organizations. Says Deighton, “It takes the broad vision found in the leadership of people like Jeff Bezos at Amazon, or the imagination that led Facebook’s Zuckerberg to hire Cheryl Sandberg, to get the customer into the process upfront, before engineering has frozen the design.”

2012-2014 Research Priorities

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