• Kevin Chang

How to Leverage Your Company's User Feedback to Focus Product Development (Case Study of TechSmith)

Read how TechSmith stays on top of the needs of their user base through text analysis.


Snagit screen capture software is a long-standing success. After a large-scale collection of feedback from their international user base, Kai Analytics was able to analyse and interpret the results to give the company information they could act on to improve the product and use to develop the next version.

Overall, we found that while the vast majority of Snagit users were highly satisfied, there were a number of suggestions on how Snagit could be even more useful


With over 30 million users, Snagit, a screen-capture tool that allows users to grab and edit screen content, has become the world’s number one application for visual communication software. So why would such a successful product require market research?

Because TechSmith is an insight-driven company. They wanted to know why people liked Snagit and how to make it better. A survey of users produced a total of 5,500 comments, each with an average of ten words. But how could the company make sense of them all?

This is where Kai Analytics came in. We know that internalising 55,000 words is a lot of work but using software to sort and classify the data would be like using Google Translate to do important business communication

What we do at Kai Analytics does comes between these two extremes. We leverage natural language processing and machine learning techniques to quickly clean, parse and summarise customer feedback into major themes. In the case of TechSmith, we took a hands-on approach. Undertaking a mini-analysis with a sample 300 comments, we first identified major themes and worked iteratively with the company to repeatedly test their hypothesis and understanding. As a result, when analysing the remaining 5,200 comments, we were able to identify over 40 major categories across six open-ended survey questions.

We were able to find aspects of the user experience that were easy to address in a way that increased the satisfaction of one-third of the users. For example, if the user failed to save a video capture, some users mistakenly believed that the video file was lost. In the subsequent update, Snagit team was able to show users how to recover files from a temporary folder, thus saving them time and frustration.

These insights helped the development team prioritize updates and new features; and the marketing team enhance the language around the positioning of the product.


The insights that Kai Analytics provided to both our research team and overall business strategy were invaluable. With a short timeline, and no additional bandwidth to complete this project, we turned to Kai Analytics to help us gain the knowledge from a large pile of unstructured data. The speed and thoroughness Kai Analytics provided helped us understand the themes of our user’s thoughts and opinions about our product. We used those themes to prioritize future marketing, engineering, and research work to better serve our user base

- Stephanie W


About Us:

Kai Analytics provides text analysis services to help businesses understand their customers' insight. We leverage natural language processing and machine learning techniques to quickly clean, summarize and categorize thousands upon thousands of customer feedback and reviews into major themes. No software subscription or coding ability is required. You have the information, we make it useful.

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