Building a Product Insights Team
Summary
Today data science, market research, and UX research are predominantly locked up in individual silos. This is a problem because companies are missing out on the full picture, research is repeated, and good insights are going to waste. In this session, Andrew shares how to build a product insights team that enables you to build bridges and tell more holistic narratives about your customers. The talk will cover how to set up the team, the different structures we see, and how you can get started today by getting the teams to work more efficiently together in the interim.
Key Insights
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Combining qualitative user research with quantitative analytics provides deeper, actionable product insights than either method alone.
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User behavior changes detected in data often lack explanatory context without qualitative research, as Andrew's Spotify example shows.
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Data analytics and UX research teams frequently operate in silos, missing opportunities for collaboration despite shared goals.
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A shared hypothesis, such as focusing on the ideal customer profile (ICP), can align cross-functional teams and reduce redundant research work.
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Relying solely on data for customer profiles can reinforce existing product biases and miss broader market opportunities.
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Starting a BI practice often means navigating shifts from qualitative to quantitative emphasis, then settling into a balanced hybrid that works for the organization.
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Three main organizational models for insights teams are embedded squads, centralized centers of excellence, and hybrid approaches, each with their own trade-offs.
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Owning the research backlog and aligning work to company OKRs enables the insights team to deliver maximum business impact and say no to less relevant requests.
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Cross-pollination of analysis between researchers and analysts during data collection and interpretation enhances the quality and buy-in of insights.
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Existing documentation tools like Confluence are insufficient for managing research knowledge, inspiring new solutions like Everywhere to prevent data silos.
Notable Quotes
"Without Jim, what we're going to see today would have been a lot worse."
"My playlist changed drastically when my son was born, but data alone wouldn’t explain why."
"Combining the what we see in data with the why we get from user research is where true insights live."
"Typically, data analytics teams are big and well-funded, while UX research teams are smaller and struggle for resources."
"Data analysts and user researchers rarely work together effectively, which is one of the biggest missed opportunities."
"At Hotcho, we started with a qualitative focus, swung too far into quantitative, and then found a balanced middle ground."
"You’ve got to take control of the backlog and position your team as value-driven, not just servicing individual teams."
"Embedded squads build domain expertise but risk losing knowledge if someone leaves, while centralized teams help reduce duplicated effort."
"Marketing is an essential collaborator because they help package and communicate insights organization-wide."
"Existing research repositories die at the bottom of slide decks; that’s why I started Everywhere to rethink how we manage insights."
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