Using AI tools internally can help you conduct simpler, quicker and better user research. Here are simple suggestions to step into this new phase of UXR.
In Part I and Part II of our AI series, we’ve looked into how to respect UX principles when using AI and to use it for developing customer happiness.
In this article, we will look into AI tools that help improve user feedback processes. From automating transcripts to generating interview scripts and supercharging data analysis, this could be the future of user research.
If you're interested in using AI-powered user research techniques to improve your CX and UX strategies, connect with us at Rethink Labs!
UXR (user research) platforms already leverage AI to assist in a variety of ways: generating interview questions that align with research goals, importing brand assets and language, optimizing question language for better responses, and the list goes on. Researchers can then fine-tune the scripts while benefiting from the AI's ability to quickly produce interview scripts.
Platforms like Qualtrics and Typeform have already started to integrate AI-driven logic within their products.
AI-powered transcription tool seamlessly converts audio files into accurate and readable text. Utilizing AI-powered transcription services like Otter or Dovetail, you can effortlessly transform spoken conversations and Zoom calls into written text.
During your user interviews, the accuracy and speed of these tools allow you to focus on the substance of the interviews, and be present with your user, rather than trying to capture everything in your notes.
This automation also saves countless hours post-interview, enabling you to focus on interpreting and extracting insights from the transcribed content.
If you’re looking for more support on executing your UXR send us a note here and we’ll share our step by step guide.
Imagine a vast dataset of user responses waiting to be analyzed. Natural language processing algorithms identify common themes and sentiments, streamlining the analysis process. Through sentiment analysis, topic modeling, and keyword extraction, AI-powered tools enable researchers to glean deeper insights with remarkable efficiency.
Dovetail is currently testing an AI clustering tool to help process the interviews quicker than ever. AI algorithms are good at classifying feedback into categories like "Feature Requests," "Bugs," and "Positive Feedback." This allows you to prioritize improvements and address pain points effectively.
Using AI in user research can not only save you time, but also allow you to uncover some major insights that you might have missed by doing the work manually. As AI-products are getting more common, automation is now baked into our favorite products and seamlessly integrates in your existing user research process.
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