[Case study] Open-ends and NPS: the Sherlock Holmes to your Watson

In a marketplace where customers have thousands of choices, what sets your company apart? Drum roll please…it is the customer experience. Okay, you got me, this isn’t new or shocking information. Like many companies, you figured out a long time ago the importance of collecting and analyzing customer feedback.

The customer experience directly affects revenue and performance. According to the Temkin Group, customers are 5.2 times more likely to purchase from a company who provides a great customer experience. Conversely, not providing a good customer experience will harm you; a Harris Interactive/RightNow study revealed that 86% of customers have stopped doing business with a company because of a poor experience. If your customers are happy, they are likely to stay with your company’s service or continue to buy your products, not to mention recommend you to a friend.

You’ve laid the groundwork by incentivizing customers to take surveys about your products, services, and customer service. You have quantitative Net Promoter Scores, as well as open-ended answers from your customers explaining the reasoning behind their ratings.

You know how many of your customers gave you a positive rating, and how many…well, didn’t. The problem is, what do you do now? You don’t know why customers are satisfied or displeased, and manually going through each open-ended question is inefficient and wouldn’t give you an accurate representation as to how this data correlates with one another.

Our client, a global leader in web hosting services, encountered this same problem (let’s be honest, it is a prevalent issue). We were able to take both their quantified, and more importantly their unstructured, qualitative data, and analyze the “why” behind their customer feedback. Understanding why customers were happy or unhappy helped this company identify exactly how they could improve the situation, including customizing their customer support strategies for specific customer groups and revising how they collected feedback from their customers.

To learn more about how this web hosting services provider combined NPS scores and unstructured data to find insights, check out this case study.

Sure, quantitative data is a step in the right direction to better understanding your customer feedback. But how useful is the evidence if you don’t have Sherlock to interpret it?

IBM might have Watson, but Luminoso is Holmes.


Want to learn more about Luminoso? Ask us for a demo or get more information at www.luminoso.com!

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