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Viva la Revolution: How MailChimp is using Big Data to Help Users Help Themselves

John Foreman (MailChimp)
Data Science Beekman Parlor - Sutton North
Average rating: ****.
(4.50, 10 ratings)

MailChimp is the largest email service provider (ESP) worldwide, enabling over 3 million users to send email marketing material to billions of subscribers. Each month, MailChimp sends more than 4 billion emails and tracks opens, clicks, purchases, and other engagement from the recipients of those newsletters. This dataset is unique in its size and richness, capturing everything from an individual’s interest in the local softball league to daily deals on zipties at Woot.

Like most ESPs, MailChimp silos each user’s account data; the tracking and performance information related to their marketing material is theirs alone to analyze and leverage to improve their marketing performance.

But MailChimp is more than 5 times larger than any other ESP. So the question naturally arose, how can MailChimp use the company’s combined data to create products valuable to each user without giving away one user’s performance data to another?

This talk will explore the tension between user privacy and using data to enrich each user’s experience, creating a more “sticky” service. We will explore examples of the Big Data products MailChimp has released using both siloed and pooled user data, to include:

  • MailChimp’s ChimpQuery segmentation tool on top of Google BigQuery
  • MailChimp’s Not-a-bot product
  • Send-time optimization
  • Likelihood to disengage calculations
  • MailChimp’s Wavelength product, facilitating subscriber interest discovery
  • Credit score calculations for discounts
  • Probabilistic A/B content testing
Photo of John Foreman

John Foreman

MailChimp

John Foreman is the Chief Data Scientist for MailChimp.com where he leads MailChimp’s data product development effort called the Email Genome Project. He also runs the Data Science for Managers course at Analytics Made Skeezy.

John holds a graduate degree in Operations Research from MIT and has worked as an analytics consultant for the Department of Defense, Coca-Cola, Royal Caribbean International, and Intercontinental Hotels Group. His expertise is in optimization modeling, revenue management, and predictive modeling.

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