Outreach demos the power of machine learning to Seattle

Posted April 23, 2019

By Sunny Bjerk

Product Marketing Manager at Outreach

Last week, three of our stellar Data Scientists and Machine Learning Engineers, Andrew Brooks, Jiwei Cao, and Li Dong, spoke at the Seattle Unified Analytics Workshop to offer a glimpse into how Outreach is using machine learning to help our reps sell better.

Selling Smarter with Data

With more than 100 data scientists and engineers in attendance and hosted by Databricks, the team highlighted our Amplify Out of Office information extraction capabilities to help our reps maintain momentum when a prospect is OOO. From our available data, the team discovered that the likelihood of booking a meeting from a sequence dropped 46% if our reps reached a prospect while OOO. The team developed a Natural Language Processing (NLP) algorithm to understand the content of the OOO reply, and delivered an intelligent solution to gracefully pause communication during the OOO period and automatically resume it based on the return date.

The whole process is done in the blink of an eye. As soon as an OOO reply is received, it is passed into our machine learning architecture where our NLP component that extracts the return date and then shares it with Outreach. A notice is then displayed to Outreach users about which prospect is out of office and help you pause the sequence and resume it based on the extracted return date.

The Crowd Goes Wild

Our Data Scientists received active engagement from the audience. Many had follow-up questions about our machine learning findings, a hot topic as companies migrate to modern real time workflows like the one used by the OOO intelligent automation feature.

Stayed tuned to our blog for more updates on our Data Science team’s adventures. Next stop: the Spark+AI Summit on April 23-25 in San Francisco, CA!

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Interested in our OOO intelligent automation capabilities? We are too! Today, these features are only available for Outreach Gmail users who sign up for early access.


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