This technique based on Natural Language Processing (NLP) can analyze thousands of survey responses and automatically categorize them within seconds to help you: After all, how can we measure words? Well, one effective and easy way to do it is with text analysis. However, it’s hard to grasp the insights that lie behind heaps of text. That’s why more than 40% of SurveyMonkey’s surveys include open-ended responses. There’s no escaping the fact that we need to understand the Voice of Customer (VoC), and we try our best to do so. Time to go through this emotional rollercoaster all over again! Well, not necessarily. Then, a new batch of survey responses arrive. You finish going through the responses and send the report just on time. You brace yourself for hours of reading and manually categorizing the written responses, to find insights that will help answer your questions. What is the customer saying about UI? Has the overall user experience improved? These questions need to be answered so you can create reports and analyses (asap). Then, your team receives the survey responses and can easily analyze most of them… until they reach the open-ended responses. You sign up to SurveyMonkey and create professional surveys in a matter of minutes. Your team spends hours on end trying to come up with the best survey to gain a deeper understanding of customer experience and the areas it needs to improve.
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