Making Omnichannel Continuous Discovery with AI | Interview with Jeff Erickson, Viable
In episode 11 of Brilliant’s AI for UX video series dedicated to emerging AI tools for UX research, we interviewed Jeff Erickson, Co-Founder and Chief Product Officer at Viable. We discuss the combination of analyzing many customer data sources with innovative data collection techniques including automating the interview process to gather rich, qualitative data more efficiently at scale.
“[Viable allows for] continuous customer discovery where every week you can open up Viable and in your sprint, you can just say what are our biggest problems? Let’s face those this week.”
Viable is an AI-powered tool that transforms customer feedback into actionable insights, enabling continuous discovery and reducing the need for manual data analysis. We consider how AI tools like Viable can benefit UX researchers and the product discovery process by facilitating continuous customer insights, reduced manual labor, and advanced automated analysis
Key topics and takeaways from this AI 4 UX conversation include Jeff’s take on:
Continuous Customer Discovery: How AI can transform the traditional periodic research approach and empower teams to stay constantly updated with user feedback and make agile, data-driven decisions.
Reducing Manual Work: Viable’s AI-supported data tagging and analysis features that allow UX researchers to reallocate time and resources to interpreting insights and shaping product strategies.
AI-Driven Interviews and Data Collection: Innovative data collection techniques including automating the interview process to gather rich, qualitative data more efficiently at scale.
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“AI 4 UX” is a space to consider the future of user experience (UX) research with artificial intelligence (AI), brought to you by Brilliant. Join us as we interview leaders and founders of some of the most popular AI tools for UX research. Learn more about Brilliant’s AI 4 UX series.
