Magazine Fall 2012 Big Idea: Competing With Data & Analytics Research Feature

Innovating With Analytics

Data-savvy organizations are using analytics to innovate — and, increasingly, to gain competitive advantage.

David Kiron, Pamela Kirk Prentice and Renee Boucher Ferguson Reading Time: 11 min 

Topics

Competing With Data & Analytics

How does data inform business processes, offerings, and engagement with customers? This research looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.
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Love is a funny thing.

It’s intangible. It’s elusive. It’s illogical, completely beyond quantification.

But that doesn’t stop online dating site Match.com from weaving data science into many aspects of its business. Data analytics influences decisions about everything from the company’s marketing and customer care to its mergers and acquisitions, with one end goal: to help people connect and fall in love.

And many do. According to surveys conducted in 2009-2010 by Match.com, one in five new committed relationships in the United States started online, as had one in six U.S. marriages during the prior three years.1 Match.com is doing its share to increase the ratio. Over the past two years, Match.com has seen more than a 50% increase in revenue, with more than 1.8 million paid subscribers in its core business.

The biggest contributor to Match.com’s recent growth spurt, according to President Mandy Ginsberg, is innovation.2 Several years ago the company began investing in a crack team of data scientists. At the same time, it built out an underlying technology platform that enabled innovation, much of it spurred by data analytics.

Because a dating site is only as good as its ability to connect people, Match.com has a group of data scientists who are continuously improving a series of more than 15 matching algorithms. Their activities underlie the company’s innovative approach to connecting people and support its business advantage in an increasingly competitive market.

Match.com President Mandy Ginsberg said the company has billions of data points it can analyze.

Image courtesy of Match.com.

“Our competition uses a psychological-based methodology and they work closely with psychologists,” said Ginsberg. “Match.com believes that every psychological theory is different, so it becomes difficult to have something that is concrete as opposed to a mathematical equation. We haven’t seen much in the market quite like it. Plus the unique thing about Match.com is that we have billions of data points from the last 17 years to analyze.”

Match.com is among a small but growing cadre of companies — both online and off — that are mastering the use of data and analytics to drive innovation and build competitive advantage.

In a recent data and analytics survey conducted by MIT Sloan Management Review in partnership with SAS Institute Inc.,

Topics

Competing With Data & Analytics

How does data inform business processes, offerings, and engagement with customers? This research looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.
More in this series

About the Authors

David Kiron is executive editor of MIT Sloan Management Review’s Innovation Hubs. Pamela Kirk Prentice is the chief research officer of SAS Institute Inc. Renee Boucher Ferguson is the contributing editor for MIT Sloan Management Review’s Data and Analytics Innovation Hub.

References

1. Match.com and Chadwick Martin Bailey 2009-2010 surveys, http://cp.match.com/cppp/media/CMB_Study.pdf.

2. “Match.com’s Ginsberg on Subscribers, Strategy,” Bloomberg video, May 20, 2012, www.bloomberg.com/video/70015972-match-com-s-ginsberg-on-subscribers-strategy.html.

3. D. Kiron and R. Shockley, “Creating Business Value With Analytics,” MIT Sloan Management Review 53, no 1 (fall 2011): 57-63.

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Comments (2)
Avoid the Big Data Trap: Four Steps for CEOs | ChiefExecutive.net | Chief Executive Magazine
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Dean Malmgren
I think its interesting the way you have defined the "information transformation cycle" as "capturing data, analyzing information, aggregating and integrating data, using insights to guide future strategy and disseminating information and insights." 

I completely agree that those steps are all necessary, but I frankly think they are ordered the exact opposite of what I have found to be the most effective way to innovate with data. In our projects at Datascope Analytics, we take inspiration from the design community and start projects by first trying to understand what insights our clients need, then designing dashboards that clearly articulate what they need to make decisions, and then think about how to aggregate data and develop analytic algorithms. 

As data becomes ever cheaper to store and analyze, I'm pretty confident that "problem first" strategies will be much more effective at innovating on faster time scales.