Actionable Customer Verbatims: Creating Breakthroughs In High-Volume Comment Analysis

Posted on December 15, 2008. Filed under: Opinion Pieces | Tags: , , , |

Many of the market researchers and custom experience managers we have met during the course of 2008, view customer verbatims, the open-ended comments received by companies through surveys, contact centers and many other channels, as a potential goldmine of customer insight. But verbatims are also seen as a waste of time by many because of the manual, unscientific nature of manual coding, which often destroys their relevance when clear business decisions need to be made. 

 Here is a sampling of the absurd:

 “We take 100 comments every 6 months and have them manually coded.  That’s it.”

 “I spend 50% of my time just reading verbatims.”

 These come from well-placed managers at market-leading corporations. 

 Manual coding is slow, biased (one coder won’t do it the same as the next, I don’t care what you say), and certainly is expensive. Manual coding also relies on categories.  Some categorization methods don’t allow comments to be coded into more than one category. When’s the last time a customer said something in a sentence or two and didn’t cover a lot of ideas? Never. Also categorized comments don’t do anything in terms of identifying relationships between ideas and meaningful trends.

 Slow and expensive market research initiatives aren’t an answer that works for many companies. Plus, there are many more organic sources of vertabims arising, especially online and from Web 2.0 sites, meaning companies need to look at all the verbatims to gather the information needed to understand the behaviors and needs of their customers.   

 To be a customer insight driven organization, a business can’t ignore 80 percent of the information your customers provide you. By ignoring the resources at their fingertips, companies are missing a huge opportunity to identify emergent customer issues, and to test and measure new methods for making customers happy and loyal. 


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