SAN FRANCISCO, Aug. 28, 2024 (GLOBE NEWSWIRE) — Outset, the first AI-moderated research platform providing the scale and speed of a survey with the depth of a one-to-one interview, announced today a new feature that enables researchers, designers and product managers to, for the first time, leverage AI moderators rather than people to conduct Usability Testing.
The research industry is projected to pull in $140B in revenue in 2024. Between 25 and 50% of that is qualitative research. But those numbers don’t represent the massive investment in human capital spent conducting qualitative interviews – not only do researchers spend a huge portion of their time moderating qualitative research, but so do product managers, designers, marketers and consultants.
Usability Testing represents a large segment of qualitative research. Traditional qualitative interviews have a lower sample size, are very expensive, and notoriously slow to conduct and get results. Teams often spend a month just conducting and analyzing interviews with only 15 people. It’s hard to make broad strategic decisions with so few inputs.
“Traditionally, usability testing involved researchers, designers and product managers observing customers interacting with a product one on one,” said Aaron Cannon, co-founder and CEO of Outset. “And that’s a time-consuming process. Outset allows teams to deploy AI-moderated research where AI can conduct hundreds of dynamic, in-depth usability sessions in a matter of hours and then synthesize the results afterwards. This approach helps teams go incredibly deep into the feedback from their users, but do so at a speed and scale that was never before possible.”
“Usability testing is often a challenge,” said Nii Codjoe, Senior Researcher at WeightWatchers. “Testing new products and features with our users is critical to growing our business. But running in-depth, 1-on-1 interviews can be slow and time-consuming—and automated testing tools don’t always give us the depth of insight we need. With Outset, my team and I have dramatically sped up how quickly we can produce generative, strategic insights. Now, we’ll get higher-quality insights faster with Outset’s new usability testing features. This new solution allows us to get better products and features to market faster.”
How it works:
- Researchers and their design and product partners prepare a usability testing guide.
- Outset trains itself on the guide and prepares a shareable link for research participants, who can come from Outset’s own panels or are provided by the client.
- Research participants (who are usually compensated for their time) enter the video survey experience using the link. An AI moderator provides an overview and sets up screen sharing with the participant, using voice and text prompts.
- As the participant navigates through the product experience on video, the AI moderator follows their movements and asks real-time contextual questions about their experience. It can listen to voice responses from the participant and ask dynamic follow up questions.
- The experience can last anywhere from 10 to 60 minutes, and Outset can conduct dozens or even hundreds of sessions at once.
- Once the sessions are completed, Outset synthesizes feedback and provides topline insights to the team for further review and action.
Outset’s Usability Testing feature is available now as part of its complete AI-moderated research platform.
About Outset
Outset is the first AI-moderated research platform providing the scale and speed of a survey with the depth of a one-to-one interview. Designed to help Fortune 500 enterprises obtain deep, qualitative research results quickly, Outset leverages AI to conduct and synthesize video interviews to inform strategic business decisions. Dozens of enterprises, including WeightWatchers, Away and Opendoor rely on Outset to deliver in-depth data results and insights faster than traditional survey methods. Learn more at http://outset.ai.
A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/29cd47b8-0134-4a9a-baf4-64930a01e6fc