Social data intelligence in the enterprise

An interview with Susan Etlinger, an Industry Analyst at Altimeter Group

Strata co-chair, Alistair Croll recently introduced me to Susan Etlinger and indicated that “Susan is the smartest person I know on the collision of enterprise and social data.” Susan is an Industry Analyst at Altimeter Group and an upcoming speaker at Strata New York 2013. She is also the lead analyst on the new report, Social Data Intelligence: Integrating Social and Enterprise Data for Competitive Advantage. She put aside some time to answer a few questions about the study and provide insights into social data intelligence.

Why did Altimeter Group decide to conduct this study?

Susan Etlinger

Susan Etlinger

Susan Etlinger: During the past year, we’ve seen growing evidence of social media proliferation throughout the enterprise. My colleague Jeremiah Owyang did a study earlier this year that found that the average enterprise-class company has 178 social media accounts, while a total of thirteen different departments—from marketing to customer service to HR, Sales and Legal—all engage in social media. That’s a substantial investment of time and resources.

I’ve been researching how the enterprise measures the business impact of social media for several years, and the sheer scope of social media proliferation made me curious as to how broadly organizations were using the data generated by social media platforms. After all, social data carries signals related to business opportunities, risk and threats, customer experience, top and bottom-line financial performance, and brand reputation.

Given the proliferation of this data throughout the organization, I wanted to look at whether companies were viewing it in the context of other enterprise data. And, if they weren’t, why not?

What was the process? Were there any tools that were particularly helpful with the data analysis?

Susan Etlinger: The majority of Altimeter Group clients are Fortune 1000 or global organizations, so we have a lot of regular interaction with the folks who address these types of issues every day. We started by interviewing about a dozen large companies about their social media use, and then fielded a survey to see whether what we were hearing anecdotally was supported by data.

The results were intriguing, but not in the way we’d envisioned. Because we focus on enterprise, a lot of responses were screened out early. Still more said they were not looking at social data in relation to other data sets. So we ended up with a very small sample size, one that should be taken anecdotally.

But here’s the interesting thing: the companies that were using social data in context of other data sets are very committed, and are using social data to inform strategic decisions at the highest level. So there was a bifurcation in the research process. Our interpretation of our findings was that social data integration is still a very nascent area, but that there is significant untapped need to bring it into the enterprise fold in a meaningful way.

How does social data intelligence differ from social data?

Susan Etlinger: I would frame the question a bit differently: how does social data differ from social data intelligence? It’s really the difference between justifying an investment in social media (did it do what we promised it would?) and using social signals from the outside world to inform business strategy (if and how should we act on this). The trick is that you can’t just look at social data in a silo. For it to be meaningful, it needs to be viewed in context of other signals about the business. That’s the difference between counting data points and developing real intelligence.

Who does social data intelligence impact within an enterprise organization? What are the challenges?

Susan Etlinger: Social data intelligence can be used by anyone within the organization. Our research counted thirteen departments actively engaging in social media, but new use cases come to light all the time. In addition to marketing, we’ve heard of social data being used for product roadmaps, fraud detection, risk mitigation, improving customer experience, performance management, recruiting; the list goes on and on. But it has to be collected and interpreted with rigor, consistency, and in context of other critical business signals. The days when companies could afford to handle social data as an afterthought—or simply to inform marketing campaigns—are rapidly drawing to a close.

How can teams make social data intelligence actionable?

Susan Etlinger: In the research report, I laid out a maturity model for social data intelligence that looks at six dimensions of maturity.

The first is scope. You need to define your universe. Then there’s strategy: what business goal does your social media initiative support? How? Then there’s context: do you have any benchmarks or data to help you evaluate what is normal? What is success? What is failure? And why? Next you look at governance. Great data is useless if it doesn’t get to the right people.

Clearly you have to develop a set of core metrics. What do you measure from a business point of view that is applicable to the social world? One example of that is the relationship between online sentiment and a measure like a Net Promoter score. Is there a correlation? Finally, you have to know the ins and outs of your data: their sources, their accuracy levels, and how to square social data—which are heterogeneous—with enterprise data.

It is my understanding that you will be speaking at Strata NY in October. Are you planning to speak about social data intelligence at your session?

Susan Etlinger: Yes, I will be presenting these models and some case studies from large organizations such as Caesar’s and Symantec that are using social data—and gleaning real intelligence from it. In the meantime, readers are welcome to download the report on Slideshare at http://www.slideshare.net/Altimeter/report-social-data-intelligence-by-susan-etlinger/

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