BI Experts: Close Encounters with Customers: 3 Steps to Success
Three recommendations for improving customer intelligence and engagement.
- 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.
Step #2: Deploy mobile BI and analytics to improve customer sales, service, and support
In my previous TDWI Best Practices Report on mobile BI and analytics, I found that about two-thirds of organizations surveyed regard using the technology to improve customer sales, service, and support as the most important potential business benefit. It's typical in many organizations that personnel out in the field working with customers lack timely and comprehensive information. Often, information is buried in paper-based reports that they lug around in briefcases.
Mobile BI on smartphones and tablets can be a game changer in making information more of a true competitive asset in customer relationships. Organizations should put a high priority on evaluation of BI, analytics, and technology for improving the flow of information to mobile users.
Step #3: Analyze social media data to gain visibility into marketing effectiveness across channels
Social media makes up a huge portion of the "big data" that people talk about today. Although some leading organizations are reaping major benefits from deep analysis of social media data, the more easily gained advantages come from listening to the channel for near real-time reactions and sentiments to marketing, service, and support activities in other channels. Organizations can then use analytics to correlate this information with data about marketing spending across channels, transactions, service records, and so on. This can be a good starting point en route to deeper analysis.
Even Closer Encounters Coming Soon
As avenues for data collection proliferate to include location data and sensor feeds from mobile devices, "close encounters" with customer behavior will continue to revolutionize analysis. In a recent interview with The Guardian, Tim Berners-Lee, the inventor of the World Wide Web, noted: "My computer has a great understanding of my state of fitness, of the things I'm eating, of the places I'm at. My phone understands from being in my pocket how much exercise I've been getting and how many stairs I've been walking up, and so on."
Quite rightly, in the interview Berners-Lee noted his privacy concerns about the personal data that this unfolding Brave New World will expose for marketing purposes as well as others.
However, there's no reason to wait for this rather interesting future to materialize to realize benefits from current customer behavior data. Organizations can do a great deal in the here and now to improve customer intelligence and engagement.