Urban Airship announced today that it is boosting its mobile marketing platform by introducing a new level of machine learning that predicts when a mobile user is most likely to engage, as well as two new onboard channels: triggered emails and SMS.
A new Send-Time Optimization machine learning model determines the best day/time a user is most likely to engage with notifications, based on previous app activity.
Previously, the platform could fire messages based on user segments or a trigger, like returning a product or a news alert. Or a marketer could set up an automation rule, such as triggering a message for any user who looked at these product pages.
Now, the company is adding the ability to predict the best time to send a message.
[Read the full article on MarTech Today.]
About The Author
Barry Levine covers marketing technology for Third Door Media. Previously, he covered this space as a Senior Writer for VentureBeat, and he has written about these and other tech subjects for such publications as CMSWire and NewsFactor. He founded and led the web site/unit at PBS station Thirteen/WNET; worked as an online Senior Producer/writer for Viacom; created a successful interactive game, PLAY IT BY EAR: The First CD Game; founded and led an independent film showcase, CENTER SCREEN, based at Harvard and M.I.T.; and served over five years as a consultant to the M.I.T. Media Lab. You can find him at LinkedIn, and on Twitter at xBarryLevine.
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