Close Encounters with Customers: 3 Steps to Success
By David Stodder

Social media, big data analytics, mobile devices, and real-time data are among the technologies revolutionizing many business functions, but probably none more so than those engaged in customer marketing, sales, and service. Companies that can take advantage these technology advances for improving customer insight and engagement will have a leg up on competitors. Those that block progress due to an internal tug-of-war between business units and IT, however, will lose ground.

Two projects have me intensely focused these days on customer intelligence and the impact of new technologies on the marketing function.

The first is development of the program for the TDWI BI Executive Summit to be held July 30 to August 1 in San Diego; the theme is "big data analytics for better customer intelligence." I'm very excited about the program, which will bring together users and experts in a range of practices and technology implementations that are important to customer intelligence and analytics.

The second is the TDWI Best Practices Report that I am writing, Customer Analytics in the Age of Social Media. I will save discussion of the report and TDWI's research survey findings for a later column, when the project is finished. In this article I would like to spotlight three key trends that I have encountered in my research and offer brief recommendations for steps that organizations seeking to improve customer intelligence and engagement should take.

Step #1: Recognize and address tensions between IT and marketing over analytics

The increasing self-service functionality in business intelligence (BI) and data discovery tools is forcing IT to adapt to "democratizing data" movements among users who want to determine on their own how they will access, analyze, and share data. In my research, I found that the growth in implementation of predictive analytics by marketing functions is even further exacerbating tensions with IT.

The discovery-oriented, iterative quality of predictive model and variable development doesn't fit well with IT's standard approach to gathering all user requirements at once and owning the development of a solution. "IT would ask us to identify the fields we wanted," a marketing data analyst told me, "but we had to say, 'Gee, we won't know until we can look at what's available and start playing with it.'"

Organizations need to resolve the tensions between business functions and IT over analytics before internal problems become obstacles to meeting strategic objectives.

-- To read the entire article (originally published in TDWI.org), click here. Dave Stodder is the director of TDWI Research for Business Intelligence.