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Visit challenges are a great way to boost restaurant sales and increase customer engagement while motivating guests to dine more frequently. With the help of machine learning, this marketing technique has evolved from using the same challenge for all guests or even segments of guests to fine-tuning both the number of visits required and the timeline for completion.
The approach has been shown to engage more customers without increasing discounts or cannibalizing sales. HuHot Mongolian Grill, a 65-unit all-you-can-eat stir fry concept, had run simpler versions of visit challenges in the past.
The members of its loyalty program were assigned different visit requirements based on the bands they belonged to, and the promotion would last for two weeks. But the results left considerable room for improvement.
One-to-one visit challenges enabled HuHot to vary two different parameters. Driven by computer algorithms, the company determined the proper time frame and number of visits to use for each guest.
Some were given less time to complete the challenge, such as visiting twice within a week, while others needed to make six visits in a month. Having a reliable way to calculate visit history and program it into loyalty offerings is key in motivating different types of guests to make that one additional visit.
The results of HuHot's redesigned one-to-one visit challenge exceeded expectations. Compared to their simplified version, HuHot saw a 69% increase in overall engagement. This is noteworthy because it's difficult to motivate more visits from those who are already frequent guests, but HuHot realized a 22% sales lift and a 21% visit lift for guests in the platinum band alone. Since sales were flat for this group in previous visit challenges, the one-to-one approach could move the needle for high-frequency guests.
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