AI plus customer data equals a powerful revenue boostAI plus customer data equals a powerful revenue boost

The days of customer data platforms (CDP) simply aggregating information about shoppers and their purchases are long gone, and a new generation of analytics and insights powered by artificial intelligence is unlocking new revenue.

That’s according to a panel of industry experts at the National Retail Federation’s Big Show in New York City in mid-January.

The combination of CDP (software that combines customer data from a variety of sources into a single database) and AI is driving innovations like personalized emails, dynamic website landing pages, and more, said panelists Art Sebastian, CEO of boutique consulting firm NexChapter; Sachin Shroff, vice president of CRM, loyalty and marketing technology at Michaels; and Mark Tack, chief marketing officer of data analytics firm Treasure Data.  

Sebastian, whose resume includes leading omnichannel growth at retail operations like c-store chain Casey’s and grocery chain Meijer, said leveraging CDP with predictive modeling enabled Casey’s to tighten the seven-day cycle for pizza purchases at the store.

“What we did was we took a segment of that overall audience (who purchase pizza once a week), and began to market their favorite pizza promotions to them at day six and a half, and at day six, and at day five and a half … and what were able to do is close the purchase cycle from every seven days and inch it towards every six days,” he said. “When you’re talking about millions of consumers spending a whole lot of money, you can really drive your business.”

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He said predictive customer behavior is part of the future of AI, and CDP will evolve beyond marketing. 

“It’s going to help operations run their stores better,” he said. “It’s going to help real estate decide where to build stores, so I look at CDP very much as an enterprise capability.”

Pairing CDP data with loyalty data, third-party data and retail media networks at the pump also helped drive customer purchases at Casey’s. 

When customers enter their loyalty number at the fuel pump, “I was able to move that data into the CDP, bang it up against existing offers and promotions in my store, and in real time, do an app push or a push notification to the customer within seconds to remind them of their favorite energy drink or coffee that’s on sale in the store,” he said. “So you need data, you need technology, and you need it all in real time to be able to do that.”

Leveraging customer data against the customer ID enabled Casey’s to observe what customers were doing outside the store. “In this example, our customer buying a cup of coffee at McDonald’s in real time, that triggered my database to remind the customer that we have great coffee in our stores,” he added. “So there are real examples of knowing your customer, triggering very relevant and contextual offers, all enabled by technology.”

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Shroff said Michael’s, an arts and crafts store, is working on new models using AI to create promotional web pages in real time featuring products relevant for the customer.

He used the example of a social media ad promoting decorative pumpkins sold at the store. Using the Michael’s product catalogue, AI can create a customizable page that includes products that go with the pumpkins. 

“The AI engine is actually reading images in the paid media ad and then creating a customized landing page,” he said. “Those who have been in the marketing world, you would realize a lot of times people click on that paid media ad and they lose interest because the page that landed you is not relevant anymore. 

“But with this technology, every time somebody comes from that big social ad, rather, the content will always be relevant. So this increases engagement, reduces bounce rate, just increases the convergence. So very high potential on what we can do with AI technology.”

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