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Text Analytics at Scale: Listening to 45 Million Customers

Data Science Beekman Parlor - Sutton North
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(2.80, 10 ratings)
Slides:   1-ZIP    external link

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 VOC insights actionable. We invite you to join us in our text analytics journey.

  • Text analytics at Intuit (case study)
  • Building decision support around text analytics
  • Technical approach & scaling
  • Protecting data privacy
  • Open source & commercial solutions

Heather Wasserlein


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.

Comments on this page are now closed.


Heather Wasserlein
10/30/2013 6:57pm EDT

Hi Marek, I don’t see an option to post my slides on this particular page, but I have posted them to my LinkedIn profile, accessible here:

If you have any questions about the slides, please feel free to ask. Cheers, Heather

Marek K Kolodziej
10/30/2013 4:30pm EDT

Would it be possible to post the slides here, like the other speakers have?


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