Getting Quality User Insights with Deanna Sim

Inside Getting Quality User Insights

1. —

   Meet Deanna Sim

   The episode opens with Deanna's path into the field: a user researcher at Polarsteps in the Netherlands who came to research through sociology, then a master's in Digital Experience Innovation. She sets up a conversation about what separates good insights from merely easy ones, why she embeds with product teams, and how she treats AI as a sparring partner rather than a shortcut.

2. 01

   From Sociology to User Research

   • How a professor and a curiosity about the digital space pulled her from sociology into research.
   • Why she rates a social science degree highly: understanding people, patterns, and ethics.
   • The transferable core skill of turning loose curiosities into well-structured questions.
3. 02

   Research That Serves the Business

   • Her shift over ten years from research driven by curiosity to research driven by business impact.
   • Why she now protects her time for projects that move the roadmap.
   • What “human-friendly experiences” means, using clunky government websites as the anti-example.
4. 03

   Inside an Embedded Research Workflow

   • How researchers at Polarsteps sit inside product teams and plan around company and team goals.
   • Building a research roadmap each “third” with PMs, head of product, and design.
   • The day-to-day mixed bag: interviews, analysis, recruitment admin, and product analytics.
5. 04

   Turning Insights Into Decisions

   • The question she always asks a team: what decision are you actually trying to make?
   • Why “I just want to know this” usually isn't a research project worth running.
   • Matching the approach to the timeline, from quick sprint learnings to year-end decisions.
6. 05

   The Research Tool Stack

   • Notion as the hub, because research should live where the team's attention already is.
   • Dovetail for qualitative analysis, Refiner for surveys, Ballpark for unmoderated studies.
   • The supporting cast: Slack, Figma, Granola, Claude, Calendly, DeepL, and Zoom.
7. 06

   AI as a Sparring Partner

   • Where it helps: fast, low-risk tasks like surfacing top themes from survey responses.
   • Why she double-checks the numbers and rarely uses AI output directly.
   • Using it to pressure-test screeners, find holes in survey logic, and rephrase recruitment emails.
8. 07

   Easy Insights vs Quality Insights

   • The hardest part of the job: knowing the difference between okay insights and good ones.
   • What quality comes down to: right questions, right people, right relevance to your goals.
   • How that judgment sharpens as you grow as a researcher.
9. 08

   Passive and Active Data, Together

   • Passive signals like NPS, CSAT, and product behavior at a mass, quantitative scale.
   • Pairing them with qualitative work to get the “why” behind the “what.”
   • Using each to fill the gaps the other leaves, rather than picking a side.
10. 09

    The Case for Embedded Researchers

    • Her magic-wand fix: embed researchers in product teams wherever possible.
    • Why embedding builds product context, working relationships, and motivation.
    • How to start when you're a team of one: pilot with a single high-impact team and support the rest lightly.
11. 10

    Advice for Newer Researchers

    • What she'd do differently: learn the language of business far earlier.
    • How to stay current, through conferences like UX 360 and UX Insight Festival, and researchers on LinkedIn.
    • Why communication skills and leaning into your strengths matter as much as method.