UserTesting bolsters ML-based UX testing with $1.3 billion acquisition by Sunstone, Thoma Bravo

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Getting insights into how users experience and use software was previously only possible by having all user testing performed by humans. With the advent of modern sentiment analysis and machine learning (ML) techniques, testing is yielding more insights than ever before.

UserTesting is among the pioneers in using ML techniques to discover and analyze user behavior. The past two years have been a whirlwind of activity for the company. In 2020, UserTesting raised $100 million in funding, and a year later, in 2021, the company went public on the New York Stock Exchange (NYSE) under the ticker symbol USER.

Today, UserTesting announced that it has reached an agreement to acquire Thoma Bravo and Sunstone Partners for $1.3 billion. When the deal closes, the plan is to merge UserZoom - which Thoma Bravo acquired in April 2022 - with UserTesting, to create an even broader set of features for user experience testing.

"We're in a space where we've built a set of technologies to capture a kind of feedback that we call a customer experience narrative," Andy MacMillan, CEO of UserTesting, told VentureBeat. "UserZoom has a set of additional different research techniques and methodologies that could complement some of our customer experience stories."

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Over the past two years, UserTesting has made significant investments in technology that help it learn from its testing.

Testing involves recording users to see how they interact with apps, including what they click on, and asking users to tell us about their experience. MacMillan said his company has invested in using ML to help extract insights from recorded user experience content.

"We really take unstructured content, but turn it into something structured," MacMillan said. "We trained a set of machine learning models to help us uncover what we call moments of insight."

Moments of insight are those nuggets of information that can help identify trends that will improve the user experience. UserTesting uses several ML technologies, including natural language processing (NLP), computer vision, and intent and behavior analysis.

Among the things that ML allows for UserTesting is the ability to perform click path analysis, which can track where a user is going and what they are actually trying to do when they click on something thing. User sentiment analysis is another key attribute that ML helps with, along with the ability to see if the user is happy with an experience.

To take it a step further, UserTesting uses ML to power a visualization that overlays intent and path behavior to gain insight into how people navigate a site or app.

"There are a lot of things we can determine about being...