Insights Unlocked

Episode web page: https://bit.ly/4besnoH

Episode summary

AI can summarize customer feedback in seconds—but can it truly understand what customers mean? In this episode of Insights Unlocked, Jason Giles sits down with Chui Chui Tan, cultural strategist, founder of Beyō Global, and author of Research for Global Growth and International User Research, to explore why the biggest challenge in AI-powered customer research isn't analyzing data—it's interpreting it.

Drawing on nearly two decades of experience conducting research across more than 50 markets, Chui Chui explains why themes like "trust," "convenience," and "it's too expensive" can mean entirely different things depending on cultural context. She argues that while AI excels at identifying patterns, human researchers remain essential for uncovering the motivations behind those patterns and translating them into better business decisions.

The conversation explores how global teams can avoid costly misinterpretations, why translation alone isn't enough for international research, and how slowing down at the right moments can lead to more accurate insights—even in an AI-driven world.

You'll learn:

Why AI has shifted the research bottleneck from synthesis to interpretation

How cultural context changes the meaning behind common customer feedback

Why recurring themes aren't the same as actionable customer insights

How to uncover the real drivers behind comments like "it's too expensive" or "I don't trust it"

Why translation alone can't capture cultural meaning in global research

A practical framework for moving from AI-generated signals to better business decisions

How research teams can build simple checks into AI-assisted workflows to avoid costly mistakes

Resources & links:

Chui Chui Tan on LinkedIn: https://www.linkedin.com/in/chuichuitan/

Beyō Global: https://beyo.global/

Research for Global Growth: https://www.amazon.co.uk/Research-Global-Growth-Strategies-Cross-Cultural/dp/1068601701

Chui Chui Tan on YouTube: https://www.youtube.com/@chuichuitan

Jason Giles on LinkedIn: https://www.linkedin.com/in/jaygiles/

Learn more about Insights Unlocked: https://www.usertesting.com/podcast

Episode web page: https://bit.ly/4fsY5jb

Episode summary

What does it really mean for UX research to have "a seat at the table"? According to Paul Humphrey, head of UX Research Practice at Next, it has less to do with presenting to executives and more to do with helping the people making product decisions achieve measurable business outcomes.

In this episode of Insights Unlocked, host Amrit Bhachu sits down with Paul to discuss how he transformed UX research at Next from a reactive support function into a strategic driver of product and e-commerce decisions. Paul shares how empowering designers to conduct their own research, aligning studies with business metrics, and building relationships with stakeholders helped the team dramatically increase research adoption while demonstrating clear business impact.

The conversation explores what it takes to prove the value of UX research, including a case study that contributed to reducing call center training and handling times, resulting in an estimated £2.75 million in savings. Paul also explains why researchers need to speak the language of the business—not just the language of usability—and why understanding stakeholder goals is often more important than delivering another research report.

Finally, Paul and Amrit discuss the growing role of AI in UX research. Paul shares how Next is using AI to accelerate workflows while maintaining rigorous validation and quality standards, why researchers should embrace experimentation, and how curiosity remains the most valuable skill in an AI-powered future.

You'll learn:

What "having a seat at the table" actually means for UX researchers

How to align UX research with business goals and stakeholder metrics

Ways to demonstrate the business impact and ROI of UX research

Why empowering designers to conduct research helps research scale

How to build stronger partnerships with product and business leaders

Lessons from Next's transformation from reactive to strategic research

Practical approaches to measuring research success with business outcomes

How AI is accelerating UX research while preserving quality and trust

Why curiosity and adaptability are essential skills for the future of UX research

Resources & links

Paul Humphrey on LinkedIn (https://www.linkedin.com/in/paul-humphrey-7865a570/)

Next (https://www.next.co.uk/)

Amrit Bhachu on LinkedIn (https://www.linkedin.com/in/amritsbhachu/)

Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/)

Learn more about Insights Unlocked (https://www.usertesting.com/podcast)

Episode web page: https://bit.ly/4fjSOKR

Episode summary:

In this episode of Insights Unlocked, Mike Mace chats with Chase Keaten, senior research manager at Walmart, about the tension shaping how researchers, designers, and builders are learning to work with AI. Chase shares why he thinks the sharpest divide in tech right now isn't about tools—it's about two competing mindsets: an "always push forward" view of AI and a more cautious, human-centered one. He explains why holding both views at once, rather than picking a side, tends to lead to better decisions.

The conversation also digs into the much-hyped "builder model," where one person plus a stack of AI agents is expected to replace a whole product team. Chase makes the case for why healthy conflict between humans—not simulated conflict from AI—is often what actually makes products better. He and Mike also explore why trust, not usability, may be the real currency of agentic AI, and Chase closes with practical advice for researchers and designers under pressure to "do something with AI" right now.

You'll learn:

Why two opposing views of AI—full-speed-ahead and human-centered caution—can coexist productively

Why the "builder model" struggles to replicate the healthy conflict that makes products better

How AI is reshaping design work, and why speed often comes at the cost of context and novelty

Why trust, not usability, is becoming the key metric for agentic AI

How a "personalization butler" could change the relationship between retailers and customers

Practical advice for researchers and designers who feel pressure to use AI without a clear plan

Resources & links

Chase Keaton on LinkedIn (https://www.linkedin.com/in/chasekeaten/)

Mike Mace on LinkedIn (https://www.linkedin.com/in/mikemace/)

Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/)

Learn more about Insights Unlocked: https://www.usertesting.com/podcast

Episode web page: https://bit.ly/4fvszkT

Episode summary:

In this episode of Insights Unlocked, Nathan Isaacs sits down with three UserTesting voices—Lija Hogan, Amrit Bhachu, and Mike Mace—for a roundtable on the conversations they're hearing most often from enterprise leaders in the back half of 2026. Drawing on months of customer calls and industry events, the group unpacks where AI is actually changing how teams work, where the hype has gotten ahead of reality, and why human judgment keeps showing up as the differentiator no matter how capable the models get.

The conversation moves from the "next bottleneck" debate—is it code, is it customers?—to the growing skills gap facing junior researchers and designers, the fading subsidies behind "token maxing," and why AI in the loop, not human in the loop, might be the better way to think about accountability. They also dig into agentic AI and the emerging question of whether customers will engage brands directly or through their own AI "info butler," why testing the personality and relationship of an AI product matters as much as testing its accuracy, and what leaders should actually prioritize as they head into 2027.

You'll learn:

Why "what's the next bottleneck" is dividing opinion among AI's loudest voices

How shrinking model subsidies are forcing leaders to rethink where AI actually saves money

Why the panel prefers "AI in the loop" over "human in the loop"

How agentic AI and MCP could reshape whether customers deal with your brand or their own AI assistant

Why evaluating the personality and relationship of an AI product matters as much as evaluating its correctness

What UX research and design teams should prioritize in the second half of 2026

Resources & links

Lija Hogan on LinkedIn (
https://www.linkedin.com/in/lija-hogan-894769/)

Amrit Bhachu on LinkedIn (
https://www.linkedin.com/in/amritsbhachu/)

Mike Mace on LinkedIn (https://www.linkedin.com/in/mikemace/)

Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/)

Learn more about Insights Unlocked: https://www.usertesting.com/podcast

Episode web page: https://bit.ly/4vcJe2e

Episode summary:

In this episode of Insights Unlocked, Nathan Isaacs sits down with Matt Howland, president and chief product/engineering officer at Cordial and chair of the working group behind the Shopper Context Protocol (SCP), to unpack what's really at stake as AI agents start shopping on our behalf.

Drawing on his years on both the vendor and retailer sides of martech, Matt explains why SCP was created to keep brands from being cut out of the customer relationship as agent commerce protocols like ACP and UCP take hold.

Matt walks through why "context-less transactions" are a problem for both shoppers and brands, why he believes standards like SCP need to preserve loyalty and intent rather than flatten every purchase into a generic transaction, and why he's optimistic that customer behavior—not platform incentives—will ultimately steer where these protocols land. The conversation also covers what Cordial is building as a customer context engine for brands like Levi's and Abercrombie, and closes with practical advice for leaders who want to start experimenting with AI internally before standards like SCP fully take shape.

You'll learn:


What the Shopper Context Protocol is and why Matt's working group built it


Why "context-less transactions" break the shopping experience for both brands and customers


How SCP relates to competing agent commerce protocols like ACP and UCP


What's at risk for retailers and loyalty programs if they don't engage with emerging standards


How Cordial uses AI to turn unstructured customer data into a "fiber uplink" of intent


One practical step leaders can take today to prepare their organizations for agentic commerce

Resources & links


Matt Howland on LinkedIn (https://www.linkedin.com/in/mhowland/)


Cordial (https://cordial.com/)


Shopper Context Protocol website (https://shoppercontextprotocol.io/)


Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/)


Learn more about Insights Unlocked: https://www.usertesting.com/podcast