The Dark Side of Customer Analytics Essays

6268 Words Mar 13th, 2013 26 Pages
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HBR CASE STUDY AND COMMENTARY

How can these companies leverage the customer data responsibly? The Dark Side of
Customer Analytics

Four commentators offer expert advice.

by Thomas H. Davenport and Jeanne G. Harris


Reprint R0705A

An insurance company finds some intriguing patterns in the loyalty card data it bought from a grocery chain—the correlation between condom sales and HIV-related claims, for instance. How can both companies leverage the data responsibly?

HBR CASE STUDY

The Dark Side of
Customer Analytics

COPYRIGHT © 2007 HARVARD BUSINESS SCHOOL PUBLISHING CORPORATION. ALL RIGHTS RESERVED.

by Thomas H. Davenport and Jeanne G. Harris

Laura Brickman was glad she was
…show more content…
Several months after

receiving the tapes, analysts at IFA ended up finding some fairly strong correlations between purchases of unhealthy products (highsodium, high-cholesterol foods) and medical claims. In response, Laura and her actuarial and sales teams conceived an offering called
Smart Choice, a low-premium insurance plan aimed at IFA customers who didn’t indulge.
Laura was flying the next day to IFA’s headquarters in Cincinnati to meet with members of the senior team. She would be seeking their approval to buy more of the ShopSense data; she wanted to continue mining the information and refining IFA’s pricing and marketing efforts. Laura understood it might be a tough sell. After all, her industry wasn’t exactly known for embracing radical change—even with proof in hand that change could work.
The make-or-break issue, she thought, would be the reliability and richness of the data.
“Your CEO needs to hear only one thing,”
Steve had told her several days earlier, while they were comparing notes. “Exclusive rights to our data will give you information that your competitors won’t be able to match. No one else has the historical data we have or as many customers nationwide.” He was right, of course. Laura also knew that if IFA decided not to buy the grocer’s data, some other insurer would.
“Paper or plastic?” a young boy was asking.
Laura had finally made it to front of the line.

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