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The Scoop Behind IHOP’s AI-Powered Recommendation Engine

  • Automatic
  • 28 October 2024
  • 2 minute read
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This article was written by Hospitality Technology. Click here to read the original article

image

Tech Moves

Since 2019, Dine Brands has tripled its spending on technology, rolled out a new POS to 1,500+ IHOP locations, launched a new website and mobile app with a guest loyalty program, and more.

In a one-on-one fire chat with Hospitality Technology’s Vice President & Brand Director and Restaurant Technology Network Co-Founder, Abigail Lorden,  CIO Justin Skelton explained how IHOP built upon Google Cloud Recommendations AI to enhance IHOP’s online ordering experience nationwide.

Skelton shared that the AI recommendation engine was one of Dine’s first foray’s into leveraging AI at scale. 

The idea was born during the pandemic when the full-service restaurant had 40% of revenue coming from off-premises sales and needed to generate revenue. “We needed something. We needed something that wouldn’t cost a lot.  … We wanted to make sure it was something that we could do, and we could it quickly. It wouldn’t take 2,3,4 or 5 years to implement. We felt the ROI (on a recommendation engine) would be immediate.”

After analyzing different products, Dine settled on the Google Retail API platform. “We settled on the Google platform, but the amount of work we had to do to get it configured and get it deployed in production was significant,” explained Skelton.   Data cleansing, importing customer information from its 11 million loyalty members, and adding other information such as intersession transactions for non-loyalty customers, menu uploads and more.

𝐘𝐨𝐮 𝐜𝐚𝐧'𝐭 𝐬𝐡𝐨𝐰 𝐮𝐩 𝐭𝐨 𝐚 𝐫𝐚𝐜𝐞 𝐰𝐢𝐭𝐡 𝐣𝐮𝐬𝐭 𝐨𝐧𝐞 𝐬𝐡𝐨𝐞. Boutique hotels keep asking about AIO, GEO optimization, and preparing for AI search. But here's what I see when I… | Eduard Ruppel 爱德华 | 21 comments
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𝐘𝐨𝐮 𝐜𝐚𝐧'𝐭 𝐬𝐡𝐨𝐰 𝐮𝐩 𝐭𝐨 𝐚 𝐫𝐚𝐜𝐞 𝐰𝐢𝐭𝐡 𝐣𝐮𝐬𝐭 𝐨𝐧𝐞 𝐬𝐡𝐨𝐞. Boutique hotels keep asking about AIO, GEO optimization, and preparing for AI search. But here's what I see when I… | Eduard Ruppel 爱德华 | 21 comments

“I want to underscore that although we went with the underlying platform, the engine, that all the work we had to do to pull everything together to make it work,” Skelton emphasized, adding that it took Dine’s IT team about 9 months to ready for deployment.

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