With AI, marketers are able to predict dozens of metrics like CLV, likelihood to purchase, and overall revenue. It gives us the ability to unlock new dimensions of our database, to go from being reactive to being proactive, and to predict the future.

Marketers can use AI to get in front of customers and automate the execution of next-best offers, 1-to-1 content, individualized incentives, and more. But the most exciting part of AI for e-commerce and retail marketers is its ability to calculate the likelihood of an action happening or not happening.

You can also define opportunities within repeat segments, lapsing segments, churning segments, and more to fill revenue gaps. In this episode, we take a look at what the “marketing matrix” is, how AI helps escape it, and numerous use cases and examples that demonstrate how it’s driving real world value.

“We have a solution as close to a silver bullet as possible to help us break out of the #marketing matrix – #AI is it,” says @mjbecker_   CLICK TO TWEET

Show details and highlights

► (0:30) Introduction: AI is legitimate

► (3:21) Why the marketing matrix will continue if we don’t invest in AI

► (5:57) AI is automation on steroids — predicting/calculating likelihood of an event

► (7:34) Is AI for you?

► (9:34) Two requirements for AI to work best

► (11:00) AI in action: 5 examples of use cases

► (15:00) BrandAlley and City Beach use AI

“AI is for any marketer who understands that database segments represent more than lines of names, email addresses, facts, figures, purchases, and preferences. They represent real HUMANS! That data is changing, growing, evolving, and very much ALIVE! AI works to expand our knowledge about WHO our customers actually are… about where they’ve been and where they’re going. Using AI, you can better understand the health, activity, and engagement of the various segments of your database on a new level previously unknown.”

Michael Becker
Digital Content Manager, Emarsys

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