Rolling Out a Repository: How Zapier Centralizes Insights from Across their Organization
Summary
By consolidating insights into a repository that all stakeholders could access and contribute to, Michelle is looking to compound Zapier's research efforts and drive insight-led decision-making across the organization.
Come along and hear firsthand the challenges and triumphs of rolling out a research repository in a growing, fully remote organization.
Key Insights
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Zapier’s existing culture of transparency and documentation was a strong foundation for the research repository implementation.
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Fragmented insight sharing systems led to perceived lack of existing research and unnecessary duplicate studies.
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Dovetail evolved from a qualitative analysis tool to a flexible centralized repository for multiple research teams.
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Stakeholder buy-in was built effectively using ‘show don’t tell’ through demo videos simulating contributor and viewer experiences.
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Populating the repository before launch with curated, relevant insights created a meaningful 'wow' moment for users on day one.
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Over a third of Zapier’s company logged into the repository shortly after launch, indicating strong adoption.
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Templates and structured workflows helped maintain insight quality and established informal peer reviews.
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Automations, like Zapier integrations and follow-up reminders to authors, are key to improving contribution and insight impact tracking.
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AI is seen as a valuable tool to speed up insight summarization and curation but cannot replace human contextual interpretation.
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Creating research indexes with dynamic search blocks facilitates discovery of recent and relevant insights and aids sense-making.
Notable Quotes
"Rolling out a research repository is complex but crucial to avoid duplicate research and make insights discoverable."
"Show don’t tell is really critical for getting stakeholder buy-in on a new tool like this."
"We wanted people to get value from day one so they could see how much more they would get from all insights centralized."
"Having one centralized repository aligned with our culture and values made the most sense for us."
"Over a third of the company signed in shortly after launch, which felt like a great success."
"Templates outline workflow models that encourage peer feedback before insights get published to the main hub."
"AI can help us cut through noise and speed up the so-what part of insights but can’t replace human knowledge of strategy and customers."
"We created research indexes with search blocks that update over time to help people focus on the most recent insights."
"The feedback culture in our company means there’s transparent discussion if conclusions aren’t clear or agreed upon."
"Automation reminders to authors help close the loop on what actions come from their published insights."
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