Research Lunch Club is heading beyond the small events space: RLC is planning in-person lunch events in 🇬🇧 London, 🇺🇸 New York, 🇺🇸 San Francisco, and 🇸🇬 Singapore, and the team is looking for people to help coordinate them.

These aren't membership events — they're open to any researcher, capped at 8–10 people, and designed to be the kind of lunch you actually look forward to. If you're interested in helping host or coordinate one — whether in those cities or somewhere closer to home — drop a note to [email protected]. or follow our luma page to be the first hear of our events!

📔 Incentive Structures for Diary Studies by Maria Rosala for Nielsen Norman Group | The article explains how incentive structures in diary studies directly shape participant behavior, affecting how often they respond, how consistently they participate, and the quality of their entries. Unlike one-off moderated sessions, diary studies typically compensate participants for their ongoing effort rather than just time, which means payments are often tied to the quantity and sometimes quality of submissions. Rosala outlines three common cash-based structures—paying after a minimum number of entries, paying per entry, and tiered pay-per-entry—showing how each influences reporting patterns and introduces tradeoffs such as delayed submissions, low-effort entries, or overproduction purely to earn more. She also discusses how bonuses for consistency or helpfulness can be layered onto these models to promote regular, high-quality reporting, while cautioning that there is no universally best structure. The core recommendation is to choose and fine-tune incentive structures based on study goals and data needs, so that they encourage natural behavior and reliable, useful longitudinal data.

✨ In the Age of AI, Experience Innovation is the Killer App by Brian Solis for A Quantum of Solis | Brian Solis argues that in an era dominated by AI, the real competitive advantage is not technology itself but experience innovation grounded in human empathy. He contrasts organizations that use AI merely to optimize existing processes with innovators who use it to augment human creativity, discover new possibilities, and design fundamentally better experiences. Drawing on his experience speaking to executives, he frames brand, customer, user, and service experience as concentric circles that must be intentionally designed as moments that become memorable, shareable experiences, rather than as disconnected functions or surface-level decoration. Solis urges leaders to deeply humanize customers by exposing executives to real moments of friction, struggle, and language, then translating that empathy into economic value via ignite moments, digital warmth, trust-building, and intuitive, personal experiences that people will feel, remember, and share. The article concludes that as AI accelerates change, organizations that treat experience as a designed system and use AI to elevate, not replace, human judgment and empathy will differentiate and thrive.

🧠 How I Use AI Without Letting It Do the Research by Shiza Ali for Shiza Ali | Shiza Ali describes a deliberate, researcher-led workflow for using AI as a support tool rather than a substitute for human judgment in user research. She starts by defining research questions, motivations, and protocols without AI, then uses models as a critique partner to surface assumptions, design gaps, and overclaiming risks. Throughout literature review, coding, and analysis, AI is positioned as a way to structure thinking, simulate skeptical reviewers, and improve clarity, not as a source of findings, quotes, or citations. Ali stresses that every claim must be traceable to real evidence—data, literature, or documented decisions—and rejects any AI-generated content that cannot be grounded in such sources. The article concludes that AI should make interpretation easier to question and inspect, reinforcing the researcher's accountability rather than automating meaning-making.

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