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Dan Lee explores how text analytics is allowing CEM to view and act on structured and unstructured feedback together.

Today’s successful hospitality companies are typically well versed in guest satisfaction and customer loyalty programs. Many frontline staff members are experts when it comes to closing the loop with customers, while managers know just how to tie quantitative performance metrics to ROI.
But consider this situation. A hotel manager notices that her branch has been receiving low quantitative scores for food quality on the standard guest satisfaction follow-up survey. Does a 2 on a scale of 1 to 10 actually tell her anything about the root cause of the issue?
The 2 out of 10 could signify:
  • Bad-tasting food
  • Unhealthy food
  • Cold food
  • Food that's inappropriate for kids
  • Not enough food
  • Limited menu choices
… and many other qualitative attributes of the food service.
Some businesses choose to address this issue by adding several follow-up questions or a “check all that apply” question, allowing customers to select from a list of possible causes of a negative rating. But what if the goal is to discover new sources of customer frustration? A “check all that apply” question does not serve this need.
If the original quantitative question on the survey were followed with an open-ended question asking customers to elaborate on the chosen score, the hotel manager would have a much richer data set for evaluating the problem and choosing how to address it - though she would still have to find a way to sift through all the responses. More on that later.
In short, only with verbatim comments can businesses find out what's really driving scores up or down.
Quantitative scores are undeniably useful. They provide a quick overview of a problem and are instrumental in tracking progress on particular metrics over time. The key is to view and act on structured and unstructured feedback together.
Text analytics: how it works
That’s much easier said than done. There are many reasons hospitality companies - and many businesses in other industries - started out using CEM to track only quantitative metrics. Open-ended feedback requires a much more concerted effort before it yields any value.


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