Adobe used to associate CPM fees based on emails sent, until it switched to a fee on a per customer profile basis. And, LinkedIn recently reduced its volume of emails sent by 40% due to member pushback.
Marketers who measured efficacy based on open rates were also part of the problem.
“When I open email, it’s to get rid of it because of my Google Priority inbox,” Marchick said. “That’s an indicator I don’t like that email, whereas a marketer using a legacy system might call that a victory.”
Kahuna is different from other marketing automation providers because it hooks first into real-time data sources like publisher sites and apps, Marchick claimed. By contrast, major marketing automation providers integrate with big CRM databases.
“We built a technology where [if Overstock.com] understands you like shopping on their site at 9 a.m. or 2 p.m., a marketer can supply us with their messaging and our algorithm figures out which resonates most with you,” he said.
Because Kahuna was not built solely for email, a marketer may instead opt to send a push notification, in-app message or populate a Facebook ad.
Marchick claimed Kahuna goes one step beyond “predictive marketing.” Instead of identifying to the marketer 50,000 people at risk of churning, he said the platform will suggest a plausible outcome and next steps they can take in their message sequencing based on machine learning.