๐Ÿง  Psychological Targeting & AI + ๐Ÿ’ธ Translating Business Needs Into Research

This week, Creating Quantitative Personas, Translating Business Needs Into Research and What Makes AI Agents Different from Other Types of AI Tools? Plus, Psychological Targeting & AI, our People of Research member interview from ๐Ÿ‡ฌ๐Ÿ‡ง, and the latest podcasts, videos, and job opportunities for the week!

๐Ÿ“ข Announcements

๐ŸŒ This year, we want to host more in-person events - and we need your help to make it happen!

We have members in cities like ๐Ÿ‡บ๐Ÿ‡ธ NYC, ๐Ÿ‡ง๐Ÿ‡ท Sรฃo Paulo, ๐Ÿ‡ฌ๐Ÿ‡ง London, ๐Ÿ‡ซ๐Ÿ‡ท Paris, ๐Ÿ‡ฉ๐Ÿ‡ช Berlin, ๐Ÿ‡ฎ๐Ÿ‡น Rome, ๐Ÿ‡ฎ๐Ÿ‡ณ Bengaluru, ๐Ÿ‡ฎ๐Ÿ‡ฉ Jakarta, ๐Ÿ‡ฆ๐Ÿ‡บ Sydney, and beyond.

So far, weโ€™ve hosted events in ๐Ÿ‡ฌ๐Ÿ‡ง London and ๐Ÿ‡ต๐Ÿ‡น Lisbon, with ๐Ÿ‡ง๐Ÿ‡ท Sรฃo Paulo. If youโ€™d like to help co-host an event in your city, reply to this newsletter to get involved. Letโ€™s make 2025 a year of meaningful connections across the globe! ๐Ÿ‘‰๏ธ Email us!

๐Ÿ”ฌ People of Research Member Interview

People of Research Interview with Karen

๐Ÿ“ฐ Article Picks

This weekโ€™s article picks:

๐Ÿ”— Creating Quantitative Personas Using Latent Class Analysis: In โ€œCreating Quantitative Personas Using Latent Class Analysis,โ€ Talieh Kazemi highlights the potential of latent class analysis (LCA) to create data-driven personas. By clustering user data into meaningful segments, Kazemi demonstrates how this approach can uncover hidden user needs and preferences. The article includes a case study on optimizing e-commerce strategies through LCA, illustrating its effectiveness in shaping product decisions. The takeaway: LCA can bridge the gap between quantitative data and actionable user insights.

๐Ÿ”— Translating Business Needs Into Research: Silja Mustaparta-Dolve shares insights from her experience at Oda & Mathem. She discusses the importance of UX researchers proactively engaging with business challenges to guide impactful research. A case study involving grocery shopping habits highlights how translating a business needโ€”larger order sizesโ€”into user-centered research uncovered previously unknown barriers. Mustaparta-Dolve emphasizes the value of asking the right questions early to align research with business goals and drive strategic innovation.

๐Ÿ”— What Makes AI Agents Different from Other Types of AI Tools?: Alexey Evdokimov explains the distinctions between AI agents, copilots, and assistants. Evdokimov explores how AI agents are characterized by autonomy, goal-oriented behavior, and environmental interaction, setting them apart from simpler AI tools. Using examples like ChatGPT and specialized copilots, the article delves into the practical and conceptual gaps in the current AI landscape. The key takeaway: understanding the capabilities of AI agents is crucial as they become more integral to enterprise solutions.

๐ŸŽ™๏ธ Podcast Pick

๐ŸŽ™๏ธ Event Pick

๐Ÿ’ผ Job Picks

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