Monday, November 14, 2016

Using Big Data Text Analysis to Determine Profitability Drivers – How to Measure and Manage the Customer Experience in the 21st Century


Professor Phil Klaus
International University of Monaco
INSEEC Research Center

Managers around the globe recognize the importance of customer experience (CX) measurement and management as the ultimate success driver for their business.

Yet, a major problem is that despite an understanding of the importance of customer relationships to a company’s success and an enthusiastic embrace of customer experience management, many managers do not have a good understanding of what customer experience management entails, nor do they know precisely what they must do to achieve success. As a matter of fact, 9 out of 10 CX programs are not profitable.

That is why the introduction of a new text-analytic-based measurement is both important and timely. Businesses that recognize how complex the process of designing, managing and measuring customer experience can be are provided with a clear step-by-step approach based upon the latest research and many years of previous work dedicated to this task.

The CX meta-mining approach, incorporating the successful application of the EXQ scale, can enable executives to move faster and outperform their competitors. CX meta-mining provides a useful guide, and addresses the three most pressing questions managers face today:

  • Where are we currently in terms of managing and measuring customer experience? 
  • Where do we want to be?
  • And most important, how do we get there?

The measurement delivers the answer to these questions 

The development of CX meta-mining was driven by client needs to enrich the knowledge gained through EXQ with existing data and leverage what their customers really thought about them. By this we mean what drives their purchasing behavior, their Share-of-Category (SoC), and ultimately, businesses profitability.  EXQ, the comprehensive measurement for CX, highlights these individual drivers in terms of importance. It lists which parts of your customers‘ experience drives how much money they spent with you versus your competitors, as illustrated in the example in table 1. 
   

Table 1 EXQ Example SoC Drivers with Competitor Comparison

EXQ allows managers to dissect the reasons for all purchasing decisions, including your competitors. It allows you to clearly identify actionable trends, as, in the example above, the importance of the ‘human’ and ‘emotional’ factor in a perceived long-term, not just sale-based relationship. 

Managers, however, often have often difficulty determining the exact meaning of, for example, ‘Your company demonstrates flexibility in dealing with me.’ CX meta-mining delivers a coherent platform allowing all team members to easily understand what a specific EXQ item means and which actions to engage in to increase SoC, and which actions to avoid to decrease SoC. 

CX meta-mining is particularly useful for analyzing already existing market research, Most existing customer experience measurements are based on static, survey tools. CX, however is dynamic in nature, requiring dynamic tools to match. The use of mobile apps to capture customer experience by using a “diary” approach is still in its infancy, but shows huge promise. This can be taken one step further by developing CX meta-mining, based upon EXQ-profitability-driver knowledge as a dynamic, multimodal measurement approach, capturing traditional ratings, text, pictures, voice and videos.   The combination of EXQ and CX meta-mining gives managers the tools for their business not only to survive, but  to thrive in a customer-dominated world. How does it work? 

CX meta-mining collects data – and makes sense of it – in real-time. Using techniques developed in health research a collection of ‘live’ CX data from consumers, is embedded while they are participating in their customer experience. Stated simply, CX meta-mining involves isolating relevant strings from documents, computing co-occurrence between strings at different levels, and examining the topology of the resulting network. Visual data is analyzed using basic feature extraction and labeling techniques. Survey ratings are also collected to capture CX. Importantly, this collection format allows one to cross-link all three data types for richer and finer-grained analysis of CX. For example, prominent themes extracted from the text and visual data can be linked to more focused rating questions.

Rather than looking for ‘hotspots’ or ‘word counts,’ CX meta-mining makes sense of what is being said and relates it to the important question ‘will this make my (existing and potential) customers buy more (and more often) from me rather than from my competitor? EXQ and meta-mining give therefore every single person in the company clear – and easy to follow – rules on what drives profitability, what it means in terms of how  the customer perceives their experience, and what to do and not to do (see screenshot below). In summary, the combination of EXQ and CX meta-mining delivers the most advanced, scientifically-based tool to measure and manage a more profitable customer experience program.



Professor Phil Klaus is considered one of the leading Customer Experience and Marketing Strategy experts worldwide. He is Professor of Customer Experience at the International University of Monaco INSEEC Research Center, founder of Dr. Phil Klaus & Associates Consulting, Professor of Customer Experience and Marketing Strategy, bestselling author of “Measuring Customer Experience – How to Develop and Execute the Most Profitable Customer Experience Strategies,” and holds multiple visiting professorships around the globe. 

His award-winning research has appeared in numerous books, and a wide range of top-tier academic and managerial journals. Phil is a frequent keynote speaker at public and in-company seminars and conferences around the world. He is an experienced manager and management consultant with an active, international portfolio of Blue-Chip clients for whom he advises on customer experience strategy, profit enhancement, 'next practice,' and business development. Phil may be reached at: pklaus@monaco.edu

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