Millions of users visit Intuit product portals every day. With web analytics, we know what user behavior looks like, but not why. By tapping into in-product search and social data, we began to understand the types of questions, pain points, and suggestions users have. This was made possible with text analytics, via unguided machine learning at scale.
Topic discovery was just the beginning though. Trending, segmentation, integration with clickstream data and association with business goals made voice of customer insights actionable. In this presentation, learn about:
Text analytics at Intuit (case study)
Building decision support around text analytics
Technical approach & scaling
Protecting data privacy
Open source & commercial solutions
Heather Wasserlein is a Senior Product Manager at Intuit, where she partners with Data Science to create data-driven New Business Initiatives. Prior to Intuit, Heather worked on advertising marketplaces and web content classification at Yahoo! Heather holds a Master’s degree in Mechanical Engineering from MIT.
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