Aberdeen Group:
Uncovering Customer Insight in Big Data

November 1, 2012 - ... The presentation, entitled "Uncovering Customer Insight in Big Data," (freely available after registration) featured Aberdeen enterprise data management Research Analyst Nathaniel Rowe, with a few examples from Tom Starek, marketing intelligence services director at security systems vendor Diebold Inc., and Phani Nagarjuna, founder and CEO of customer analytics provider Nuevora.

Aberdeen indicates that companies that have taken on big data initiatives have a 4 percent greater rate of customer growth year-over-year than their counterparts who have not taken on these advanced analytic capabilities. Rowe was quick to follow up that big data programs can't be directly linked to profitability, only that these successfully companies were the ones investing in and expanding big data plans. However, this "hand-in-hand" business growth and big data adoption does reveal insight into what enterprises are going after with big data programs and what separates successful and struggling initiatives.

According to Aberdeen research where enterprises provided multiple answers, the top sources for their big data initiatives were transactional, structured data (95 percent), social and customer data (85 percent), clickstream (83 percent) and internal, unstructured data (82 percent). Rowe says these adoption percentages reflect a maturity scale of sorts, and he expects enterprises with a solid grasp on their transactional structured data to be able to branch out into other data streams more quickly and aptly.

Surveying enterprises engaged in big data intiatives, Aberdeen split a group of 99 respondents into "leaders" and "followers" on ROI. Of those leaders, 63 percent had a data analyst or data scientist on staff to search out value in data, compared with 42 percent of followers. Rowe says that "this role really wasn't a thing five years ago" but this job title is becoming mainstream along with big data initiatives.

However, such initiatives will only truly succeed as data scientists are able to tie information streams into business needs and decision-maker plans. In addition, 54 percent of leaders had assessed enterprise department needs with big data ahead of time, compared with 27 percent of followers who had done the same. Twenty-eight percent of big data leaders had an understanding of their data sources, compared with only 9 percent of followers, according to the Aberdeen survey.

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