Bill Shander

Here's a pro tip for those massive gift guides or summer/winter fun guides that are actually large research projects: The best way to create such a list is by keeping notes in a spreadsheet with wraparound text enabled. Each row and column serves a purpose in keeping you organized and in keeping track of assets like photos, videos, backgrounding links, transcripts, factchecking documentation and social snippets. Each team can then view this master document and drop in assets or copy and paste what they need for their own branch of the work. (Or make those folks read only if they have butter fingers.) This is easy for me because I do it all the time. So... if your brand marketing team needs a summer or fall or winter book reading list, I got you! Plus, I've already read the galleys and can guarantee you a well-done list of actual and real books, plus (my own) interviews with most of the authors. There really are no short cuts when it comes to covering books or crafting a seasonal guide. It truly is an art to be able to produce well-done brand content in this area.

12

Unsexy (but very valuable) AI use case in research operations #1. (Even if you've never run a research survey, you've probably been affected by bad ones) There are MANY factors that impact research quality...one of which is survey design. One poorly written question can contaminate an entire study with bad data—and those studies inform product launches, policy decisions, and strategies that affect all of us. A real example that believe it or not, has burned plenty of researchers: Survey qualifying (screening) question: Do you eat Wonka chocolate bars? ☑️ Yes 🔲 No Survey fraudsters know "Yes" gets them paid with a small survey incentive...and those can add up in certain parts of the world. The fraudster's data fuels your "insights" based on responses from people who've never actually touched a Wonka bar. Where AI actually helps: Scalafai's platform, Safia, automatically flags problematic screening questions and suggests alternatives that are more likely to capture real data: ▪️ "Which chocolate brands have you consumed in the past month?" ▪️ Specific frequency questions requiring real knowledge ▪️ Follow-ups verifying genuine experience Stay tuned for super exciting news for market research teams: Beyond catching individual question issues, Safia will soon help researchers implement a holistic, prevention-focused framework that integrates ALL quality factors across the research ecosystem—from survey design to data collection to stakeholder collaboration. Prevention beats correction. Every time. Researchers, the yes/no questions stories are epic. What questions have you seen?!? I'll go first... Are you a funeral home director that offers direct cremation with an online arrangement app? ☑️ Yes 🔲 No 😬

111

21 Comments

The recordings from the Accessible and Inclusive Design Conference (AIDC) are now available, including my session on Minimizing Bias in AI-Generated Images. Watch the recording, download the slides, and get additional resources here: https://lnkd.in/euCR6Pra

51

9 Comments

Simplifying data… I've seen the most brilliant people present data that overwhelms their audience. Or confuses them… Or misses the mark on helping stakeholders understand the story the data is telling. Here's a quick clip from my recent conversation with Nathan Teuscher of Aplos Analytics, Inc. We discussed the importance of making sure you present data in a way that specific audiences can actually understand. I hope you'll give the entire episode a listen (link in comments). Nathan shared many tips, and learnings from his own experiences, that I think you'll find helpful — whether or not the data you're presenting or communicating is scientific. #Podcast #LeadershipCommunication

29

1 Comment

Who else wants to know more about those "AI use vs capability vs exposure" charts? What's behind them? What do they mean? Interesting overview from Martha Gimbel, Jed Kolko and others: https://lnkd.in/g5up5Qip

13

1 Comment

You don’t need a $3,000 Vegas badge to move your career forward. Brian Fowler and I just published a new piece with Greenbook on why local and regional conferences often deliver better ROI, especially for insights and analytics professionals who are job searching, hiring, or trying to grow their network without blowing the budget. A lot of this thinking grew out of conversations inside Insights Career Network (ICN), which is an awesome community that’s been helping thousands of researchers navigate career shifts, job searches, and industry change together, not alone. We see every day how smaller, local events can spark real opportunities: new roles, mentors, collaborators, and clients. In the article, we dig into: - Why smaller shows = deeper conversations (not just collecting lanyards) - How locally sourced speakers and sponsors get you closer to real opportunities in your own backyard - Simple ways to turn a one-day event into new connections, leads, or job conversations within 14 days - A mini-list of lower-cost conferences to keep on your radar If you’re thinking about how to level up in 2026, without getting on a plane, this might help you choose your next move more intentionally. Read it here: Why Attend Local Conferences IRL? For the ROI https://lnkd.in/e3S7RdBY And if you’re in the insights world and not yet plugged into Insights Career Network, it’s a great place to compare notes, swap leads, and find your “conference crew.”

21

9 Comments

An interesting attempt to separate user role and expertise level in evaluating research on user-centered AI systems was made in the UMAP 2025 paper "Disentangling Stakeholder Role and Expertise in User-Centered Explainable AI," presented today by Maxwell Szymanski. Placing existing work in this two-dimensional space will help us understand what we are assessing and compare different works. https://lnkd.in/exrN9g7n

24

When software doesn’t do what you want, what if you could tweak it yourself? My research group at Ink & Switch just published an essay outlining our vision for “malleable software” — software that users can tailor to meet their unique needs.  It summarizes some big ideas from decades of prior art, as well as lessons from years of our own prototyping. We explain why AI is a big deal, but not enough on its own to enable a new era of personal software. We also explain why “apps are avocado slicers” — read the piece to see what that means :) It’s a deep dive not a quick read, but we’ve tried our best to keep it accessible to anyone who’s curious about this work. Check it out and let me know what you think!  https://lnkd.in/egdgHmz4

26

3 Comments

If the orienting focus of all your product research, user research, design research, whatever you're all calling it these days -- is simply "The Product" and never shifts to thinking about capturing a holistic enough picture of actual real-world behaviors of people (yes, REAL PEOPLE, not whatever "personas" are dreamed up in rushed socially acceptable planning fever dreams and only allowed to be expressed in the language of pre-existing roadmaps and quarters of groupthink), what you'll be analyzing is the composite bundle of hopes, fears, wishes, dreams, stereotypes, unpacked assumptions and mental models of your organization. Which you know, has value. Some organizations even shift that mental model closer to the real world than others, they're not all bad. You need a collective dream of A Product I think. But how do you update your beliefs with new information? How do you think outside of the box of "a bunch of people deeply commercially motivated to support this product"? What ensures that you're not operating from entrenched groupthink? Personally I've always chosen to try to evaluate whether the products I've built or worked on are fitting into a big enough part of real human behaviors in the world and helping those people achieve their goals. And doing that requires structure. You need to do it in ways that take in human judgment and motivated perceptions, but also are capable of challenging those. Most of us wouldn't take a medicine that was only tested with interviews with five friends of the doctor. But for some reason a lot of product decisions are fine with this. There's a lot of money to waste this way.

17

1 Comment