The use case: how Epsilon deploys H2O.ai
Epsilon built its "Accelerate" machine learning system on H2O-3 to replace a legacy SAS system for audience targeting. The system builds interpretable models at scale on terabyte-sized datasets to select lists of consumers likely to respond to direct mail offers.
More reported results
Figures published in H2O.ai’s case study. They are not independently measured by usedby.
The Accelerate system improved direct mail response rates by 3 to 5%
adding roughly 15,000 highly relevant customers to each marketing campaign
The platform now supports 8,000 campaigns annually
Epsilon's Abacus data cooperative builds over 100,000 machine learning models a year
In the customer’s words
In the environment of increasing privacy regulations, the tools Epsilon employs need to provide transparent list selection. H2O.ai help us meet this challenging and critical need.Other AI tools used by Epsilon
Other public relationships recorded on usedby.
Explore Epsilon’s AI stack
H2O.ai users in Marketing Tech
Companies in the same sector, with public evidence.
See all H2O.ai customers
Go straight to the source
Based on H2O.ai’s published case study. We check the public evidence; the results are reported by the vendor.
h2o.ai- Last checked
- Oct 24, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: $9.0MChecked
Printed word for word on the page, near the name of Epsilon.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Epsilon.
- The numbers in our summaryChecked
Each one is printed on the page.
- Epsilon uses H2O.aiChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
The Accelerate system improved direct mail response rates by 3 to 5%, adding roughly 15,000 highly relevant customers to each marketing campaign. For one major gift and B2B retailer, a 1.10% response rate increase on a single campaign generated $9.0M in incremental revenue.