Transform Open-Ended Feedback Into Actionable Intelligence

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Actionable intelligence might be a buzzword, but it's most definitely what you should look for in every interaction you have - especially interaction with your analytics software.

Customer analytics provider iPerception introduced four new reporting and analysis tools that help marketers mine open-ended customer feedback for business insights. Marketers will be able to drill into critical areas of verbatim customer feedback like term frequency, concept frequency, and concept concordance – and, for the first time ever, associate qualitative open-ended comments to quantitative web experience ratings.

  • Term Frequency – This tool is designed to find customer feedback associated with particular terms of interest. The tool aggregates unique terms over time and presents them back to the analyst sorted by frequency count or alphabetic order. By selecting the terms of interest, the tool then allows the analyst to pull the full source comment and sort the feedback by visitor group or time frame.
  • Concept Frequency – This tool is designed to find concepts of interest within the customer feedback, as well as to track the top 20 feedback concepts over time. This tool links related terms together for a wider look at particular issues of interest. In addition to having similar capabilities to the Term Frequency tool, this tool is based on concept libraries that can be accessed online.
  • Concept Concordance – This tool is designed to quantify and trend the issues related to the main concepts in the open-ended feedback, thereby helping you to uncover context and meaning over time. As an example, when the concept ‘Difficult’ is present, 55% of the time it is related to the concept ‘car configuration’ and 35% of the time it is related to the concept ‘find’.
  • Feedback mapped to iPSI Attribute ratings - This tool is a patent-pending innovation that ties qualitative open-ended feedback to quantitative ratings of the web experience. The end result allows you to select any Attribute rating for any user group segment for a particular timeframe and instantly pull the open-ended feedback from this sample that is most related to the rating in question. For example, if an e-commerce site sees a substantial drop in satisfaction for its internal site search tools, they can simply click on the Attribute score and drill right down into the open-ended comments that are most relevant.

 

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