You need to look at the comments to understand context and identify the problem. But ratings in isolation can't provide a fix. If you have 100 one-star reviews of a product, you know something's going wrong. So what counts as qualitative data? Simply put, it's information collected from text, audio and images that can't be easily expressed using numbers. Qualitative data and themesĪs soon as you start looking at feedback or text analysis, you'll see the term qualitative data. We’ll also give some examples of how leading companies use thematic analysis to better understand their feedback data. We'll briefly cover some manual approaches, and take a deeper look at thematic analysis software. In this overview, we’ll break down the jargon, and explain how thematic analysis works. To get valuable insights, companies need to structure their feedback data and filter out the noise and filler data. It’s a conversation, rather than a list of points. Qualitative data is inherently unstructured, with people contributing ideas and feedback in the way that is natural to them. It enables you to find rich, useful insights quickly, and organizes your data so that you can easily see context. Thematic analysis is a systematic method of analyzing qualitative data. When you have a lot of text feedback, like open-end survey responses, app review comments or twitter threads, how do you begin to make sense of it all? One of the best approaches is to uncover themes in the data using thematic analysis. Thematic analysis: an overview AI & NLP Thematic Feedback Analysis
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