@BigDataExpo Authors: Pat Romanski, Hollis Tibbetts, William Schmarzo, Elizabeth White, Kevin Jackson

Related Topics: @CloudExpo, Java IoT, Linux Containers, @BigDataExpo, SDN Journal

@CloudExpo: Article

How the Data Science of Email is Solving Today’s Business Problems

At Cloud Expo, SendGrid’s Aaron Beach to discuss how to improve sender deliverability at minimal cost per email

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There are 182 billion emails sent every day, generating a lot of data about how recipients and ISPs respond. Many marketers take a more-is-better approach to stats, preferring to have the ability to slice and dice their email lists based numerous arbitrary stats. However, fundamentally what really matters is whether or not sending an email to a particular recipient will generate value. Data Scientists can design high-level insights such as engagement prediction models and content clusters that allow marketers to cut through the noise and design their campaigns around strong, predictive signals, rather than arbitrary statistics.

SendGrid sends up to half a billion emails a day for customers such as Pinterest and GitHub. All this email adds up to more text than produced in the entire twitterverse. We track events like clicks, opens and deliveries to help improve deliverability for our customers - adding up to over 50 Billion useful events every month. While SendGrid data covers only about 2% of all non-spam email activity in the world, it gives SendGrid a unique snapshot of email activity spanning from the senders to the recipients and inbox providers like gmail and yahoo. To cope with data of this scale SendGrid has designed and implemented custom data structures to store 10s of billions of items in memory on a single commodity machine.

In his session at 15th Cloud Expo, Aaron Beach, Senior Data Scientist at SendGrid, will discuss how SendGrid has used technologies like this to predict recipient behavior and improve sender deliverability at minimal cost per email.

He will share his research based on analysis of billions of email interactions:

  • The data we collect: Email activity and SMTP events
  • The problems we solve: Predicting recipient engagement
  • The data structure we use: Combinatorial Bloom Filters

Through a deep dive into back-end email systems, data scientists can profile inbox behaviors to learn how to reduce spam complaints, increase delivery and improve recipient engagement.

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Speaker Bio:
Aaron Beach is a data scientist with experience in email services, energy systems, privacy, social networks, mobile apps, natural language processing, recommendation systems and Big Data. He has a PhD in Computer Science and has published over 25 research papers.

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