Applebee’s and IHOP Use AI Restaurant Technology to Plate Personalization

Dine Brands, the parent company of fast casual sitdown restaurants like Applebee’s, IHOP, and Fuzzy’s Taco Shop, is following in the footsteps of [[quick-service restaurant]] (QSR) giants like Taco Bell by adding AI into their restaurant technology stack. While QSRs roll out AI drive-thrus or incorporate the technology into self-service kiosks, Dine Brands is applying AI to revamp traditional table service.

Everyone who has ever dined at a traditional restaurant knows what to expect from the experience: You’re seated at a table and brought water. Before long (you hope), a server arrives to take your drink order. 

For most restaurant-goers, the experience begins with a clean slate with each visit, every time. Dine Brands’ new AI-powered personalization engine aims to change this model. The system uses customer loyalty data, like past orders and known dietary preferences, to generate real-time tailored menu recommendations. The recommendations are delivered directly to the customer through online and mobile order interfaces or by servers who access the engine tableside using a tablet.

However, questions remain. For the new technology to make sense, it must satisfy the expectations of consumers, franchisees, and investors:

• Consumers are (understandably) skeptical about new technology.
• Franchisors have to incorporate the tech, training employees on how to use it.
• Investors must see a return on the increased restaurant tech investment too. 

Can AI-powered dining personalization satisfy both bellies and the bottom line?

Where AI Meets the Menu

Here’s how the Dine Brands personalization engine works. 

1. An IHOP server approaches your table
2. Using a tablet, the server scans a QR code connected to the customer’s profile on a loyalty app to access existing customer data, and 
3. Using AI, recommendations are suggested that are tailored to the customer

For example, the engine might recommend an add-on like a limited time meal that aligns with the customer’s flavor preferences, or suggest a popular side dish to complement a particular breakfast combo.

Recommended add-ons are a common part of the experience while placing an online or self-service kiosk order. Before hitting submit you’re served a selection of sides, drinks, and sauces designed to complement your order. 

The level of in-person personalization Dine Brands is incorporating depends upon a complex technology ecosystem. Before a customer is offered that new smoothie or side dish at any of Dine Brands’ 3,500 restaurants, its [[point-of-sale system]], loyalty databases, mobile apps, and connected devices must exchange information.

Dine Brands’ small IT team is tasked with managing thousands of devices and systems across its restaurant portfolio, so it opts to buy proven solutions rather than build them from scratch. The personalization engine uses Google Cloud’s recommendations AI to blend individual customer data with anonymized buying patterns from similar diners to generate menu suggestions tableside. Other partnerships with the IT consulting firm, Cognizant, and Amazon’s Q generative AI assistant help Dine Brands explore additional AI capabilities, like a tool the IT team can use to query its collective knowledge base to service systems and tech devices.

All of this requires flawless execution. AI-generated recommendations require accurate data and operational, integrated systems. 

(For an interconnected system like this, [[remote monitoring and management]] (RMM) can help ensure devices are secure and supported at all times. RMM is the digital glue that holds together the front-of-house experience with the back-of-house tech infrastructure.)

According to Justin Skelton, CIO at Dine Brands, the personalization engine is designed to increase revenue and also repeat visits while improving both guest satisfaction and server efficiency. The AI-powered personalization tool is currently live in mobile apps and applied to online orders for Applebee’s and IHOP customers, with plans to expand to in-store tablets for servers and guests alike. The company is also planning a rollout of the technology for its Fuzzy’s Taco Shop chain.

Overcoming Cynicism About Personalization

McKinsey reports personalization can boost customer retention by 20–30% and increase average order values by 10–15%. Those numbers have many restaurants moving to develop and implement personalization solutions (as powered by AI). The catch is that an active contingent of consumers will be harder to convince.

In Reddit threads on r/futurology and r/technology, users expressed skepticism over the Dine Brands’ dining personalization. Commenters on a post in r/futurology said a personalization engine “sounds terrible” and worried about being stereotyped based on the data collected. Another comment on the post maligned AI as a whole, stating, “seems like ‘AI’ is the new way to say ‘ensh*ttification.’” The post on r/technology saw commenters discussing an AI-free way to earn repeat business: focus on improving the in-restaurant experience, including the food. 

The comments on r/technology reflect varying levels of discomfort among consumers with adding technology into the traditionally offline interaction. Dine Brands’ restaurants thrive on hospitality and face-to-face interaction. If AI recommendations feel intrusive or robotic, they risk clashing with the experience customers come for.

Can AI better the restaurant experience, as tech vendors would have you believe? Or are these tools likely to disrupt the experience in a way that is more aggravating to customers than beneficial?

AI’s Real Value: Making Staff More Effective

So far, customer-facing AI solutions are the ones earning headlines. While not as flashy, AI’s ability to reduce friction for staff and managers may be the real driver behind further technological developments. 

For example, Dine Brands is testing a number of AI-enhanced tools including the aforementioned natural language support system to help resolve tech issues faster. Also, AI-enabled cameras may soon detect when tables need service or to be cleared. And staffing tools to help managers make better scheduling decisions.

A chain like Dine Brands’ relies on making it easier for operators (franchisees) to manage lean, in-store teams. These operators work to lower the costs (time, labor) of day-to-day operations. When support is fast and restaurant technology works, managers can focus on their primary jobs: great service and food.

What It Takes to Make AI Work For Everyone

AI personalization at restaurants like IHOP and Applebee’s has potential: better recommendations for guests, more upsell opportunities for restaurants, and operational efficiencies that support lean teams. 

Realizing that potential requires a lot of restaurant technology to work together. A stable tech foundation, responsive support systems, and making a technologically-powered experience feel natural could be the future of dining in … if done right. And with the right infrastructure, companies like Dine Brands can lay the groundwork for scalable, sustainable personalization.