The available application enables MediaMath to target ads based on the actions a consumer takes within an email.
For instance, a retailer might send an email to customers in its database about a fall sale, said MediaMath’s Shanti Grandhi, who works on strategic partnerships,. The recipients of that email would automatically turn into segments and be available for retargeting via MediaMath.
The closed beta solution, which is being tested with “a handful” of clients, has more robust segmentation and audience creation capabilities, Grandhi said. “We’re working with a few partners to continue to build the case.”
The more advanced functions include segmenting customers who don’t open an email in order to send them prospecting ads. And if a group of customers perform certain actions within an email message, MediaMath can enable lookalike modeling to allow marketers to identify a larger audience within their ecosystem.
Additionally, marketers will also be able to target based on email behaviors, like whether a customer opened an email or clicked through on an offer.
Finally, the solution will allow the coordination of MediaMath ads with email messages.
While the integration of marketing and ad tech has been a talking point for some time, it’s a difficult process because it entails mixing complex systems from different companies and getting mutual clients on board. (One reason this partnership happened is because the two companies had numerous clients in common, though Hooshmand wouldn’t say exactly how many.)
For MediaMath, a key enabler was its existing partnership with the Oracle DMP. Its integration with Oracle Marketing Cloud let MediaMath expedite certain processes, Grandhi said, including aligning pricing and transferring data.
That Oracle and MediaMath had both invested in APIs designed to pass data back and forth also helped, Hooshmand said: “A lot of times with ad tech companies, development resources are used for building up internal products.”
As clients take advantage of the integration, Oracle and MediaMath will evaluate client feedback and make gradual improvements.
“We’ve committed to experimenting fast, seeing what the results are and drawing conclusions from there,” Hooshmand said.