What’s the Big Deal with Big Data at The Gartner Customer Strategies and Technologies Summit

June 7, 2013
Daniel Hong, Senior Director Product Marketing Strategy

I attended the Gartner Customer 360 Summit in London, June 5-6, 2013 one of the premier knowledge forums where Gartner analysts present on the myriad of strategies and technologies employed by leading enterprises in customer engagement and experience management. At a high level, this year’s summit focused on the three areas needed for enterprises to effectively execute on a customer experience strategy, with the keynote titled “Understand, Engage and Deliver,” presented by Gene Alvarez, Jim Davies and Ed Thompson. According to the analysts the “understand” stage is the most important phase in this framework because the way an enterprise engages with a customer and the experience delivered are irrelevant if an enterprise doesn’t understand the customer. And this is where many enterprises run into issues. The presentation included highlights from a CRM Survey on the Top Five Challenges in Europe. Customer data and information were the biggest challenges facing customer initiatives/programs. It is in this phase that big data becomes the critical foundation on which companies need to build on in order to identify, capture, and analyze all the relevant information about the customer and uncover correlations to any external factors that impact the customer’s experience across the entire customer lifecycle. 

I certainly agree with Gartner on the importance of the “understand” phase and big data in customer experience; however, while “understand, engage and deliver framework” is highly relevant for enterprises I feel that the importance of  “learning” (the intelligence that powers insights by building on the past and continuously improving experiences) was under emphasized.  (“Learning” is implicit in the “understand” stage but it can also be broken out as a separate phase in this framework.) That’s because an enterprise that is successfully leveraging big data in customer experience has made that huge commitment to constantly refine and optimize customer engagement. In order to accomplish this enterprises have to continuously learn about customers in order to better understand their customers. 

To do this cost effectively and at scale requires elements of machine learning and data sciences to extrapolate structured, unstructured and real-time journey data into relevant information and actionable insight prior to and during the customer interaction. This can help enterprises anticipate customer intent and engage customers when and where customers want, how customers want and with the services and products that the customer needs..

Big data in customer experience is not new thinking relative to the implicit customer data-centric mindset that has permeated the enterprise market for years. Enterprises have and make use of copious amounts of data already but never before have enterprises been able to access as much data and new information sources as they do today and aggregate that into a unified view of the customer.  Towards this end enterprises should be thinking about:

  1. What can big data do for my business and my customers?
  2. What are the different approaches and benefits of each approach to big data in customer experience?
Daniel Hong, Senior Director Product Marketing Strategy
Daniel Hong, Senior Director Product Marketing Strategy

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