How InVision designs predictive models using Segment warehouses

To keep up with a growing customer base, InVision used Segment to unify their data across the diverse toolsets each team uses, giving the analytics team more time to run powerful new models and analyses.

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“If we did all the data engineering and integrations in-house we'd be spending a lot of time building and maintaining instead of analyzing.”

— Kai Rikhye, Analytics Lead, InVision

The Company

Over five million users around the world use the InVision platform for ideation, design, prototyping, and design management. Tens of thousands of companies, including 100% of the Fortune 100, and brands like Airbnb, Amazon, HBO, Netflix, Slack, Starbucks and Uber, use InVision to make products consumers love.

The Challenge

While InVision built an impressive customer base, its users were extremely sensitive to marketing tactics and expected a world-class user experience. InVision knew it needed to engage with customers in a personalized and highly-relevant way. This required them to With a lean analytics team, InVision had to be smart about where it invested resources in order to support the rapidly-growing business. This was compounded by the fact that InVision evolved the product rapidly to keep up with the need of its cutting-edge customer base. InVision needed to integrate customer data into a diverse set of tools across the fast-moving teams, all while making time for their own robust analysis projects.

  • Massive and highly engaged customers that are sensitive to marketing and the overall user experience.

  • Small analytics team must support a rapidly growing company.

  • Constantly evolving product results in increasing demand for event-level tracking.

  • Must integrate and support a diverse toolset used by many departments.

The Solution

InVision’s Segment-hosted data warehouse on Amazon Redshift stores millions of daily events, and because Segment seamlessly flows that same data to all the teams other destinations, the analytics team has more time for advanced analysis.

  • Improved onboarding experience with a Segment destination tool that messages users dynamically based on their feature usage.

  • Created sophisticated, side-by-side, analyses that allow teams to view data in ways that are most relevant to them.

  • Enabled modeling that identifies which content and promotions provide the most value to users.

Industry: B2B Tech
Location: New York, NY