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  • Writer's pictureKuba Tymula

Restaurant groups must use their data better to deliver better customer experience

The ability to collect, synthesize and act on customer-level data is transforming customer experience across all service industries. We see retailers, travel companies and hotels moving toward omnichannel and data-driven approaches to customer experience. Yet the restaurant industry, an industry completely reliant on delivering high-quality customer experience, strangely lags behind in capturing and using data to improve the experience of diners.

This may be due to the decentralized, mom-and-pop nature of the industry. However, as the pressure of rising wages across the globe and increasing competition from well-funded competitors increases, it is inevitable that our restaurateurs turn their eyes to the numbers. There they will find the answer to differentiating their customer experience.

Understand your customers

For restaurant service, having customer-level data lets you deploy your best, most experienced servers to cover your most important tables, and lets you get the best out of every customer interaction across the not only your restaurant but your entire group. From the knowledge of your best servers, who know every regular customer and can recall every first drinks order, dietary requirement and seating preference, you can help your whole service team deliver an exceptional experience to your clients.

Beyond shaping direct customer interactions, you can find data-driven answers to many of the traditionally more-art-than-science elements of the restaurant business. You can learn what effect shortening seating times has on overall customer satisfaction, what is the ideal table mix to ensure maximum bookings, and even which menu layout maximizes spend per head. With these answers you can incrementally improve the customer experience while strengthening the bottom line of your restaurant.

To achieve the level of familiarity and knowledge that creates great service, you need to collect, synthesize and analyze customer-level data.


Restaurant data comes from three key sources: reservations, point of sale systems and feedback systems. In isolation these sources do provide some value. Reservation data provides a picture of frequency of repeat visits, average group size and booking times. POS data gives an anonymized picture of what the restaurant is selling, and feedback provides a qualitative picture of customers' opinions. However the true value to service becomes available when you combine the data to create a 360-degree view of the diner's experience. Linking a reservation name to dining preferences creates personal profiles for all diners, so you can personalize the message that gets them in the door and the service that keeps them happy.

Combine this data with data received through marketing channels adds another layer of customer understanding. Email and social-media data offers insights into customer demographics as well as engagement and reviews.

The common barrier to efficient data collection is technology, which used to be expensive and take a long time to implement. Andrew El-Bayeh, the Director of Marketing of Merivale (the Sydney-based iconic house of brands that includes, among others, the likes of night-life venues like Ivy and Establishment as well as restaurants like Mr Wong or Est) has experienced these pain points in his work: “We have experienced exponential growth, in which we prioritized great concepts and great venues, which meant that our systems couldn’t be updated as fast as we would have wanted them to be. Thankfully, our competitors are even further behind”.

Cloud, and the advent of Platform-As-A-Service and Software-As-A-Service is making things easier for even the smallest of the restaurants, so we can expect a lot of progress in this area soon.


The next step is to ensure this data is actionable by driving insight through analytics. The creation of a 360-degree view of the diner allows segmentation to be performed based on value, frequency, menu choices and party size. This information then lets restaurant management make data-driven decisions about everything from menu makeup to seating plans and section sizes. Segmentation also becomes the driving force behind marketing efforts, with marketing teams now able to deliver targeted messaging to loyal and high-value customers based on their past behavior.


The final stage of the process is to get the data into the hands of front line staff and restaurant marketers to empower them to deliver the levels of service now possible through comprehensive profiling of customers.

Ensuring that historical data is available in the restaurant gives servers the information required to deliver high-quality personal service. This involves real-time linking of reservations and point of sales systems to ensure profiles are updated and the knowledge is displayed in a format that easily actionable on the floor, for the reservations team, and in the kitchen.

Getting data into the hands of those marketing your restaurant is perhaps the biggest opportunity for change. Communicating with customers based on their preferences and previous dining experiences lets restaurants build a far more personal relationship with regular diners. You can ensure that customers who are regular whiskey drinkers get a message when you are having a whiskey night, or VIP diners receive relevant access to exclusive events.

What's next?

There is large value to restaurant groups in taking a more data-driven approach to their operations and service, yet it is a significant shift for most operators. Digital transformation is a challenge that is ahead of all industries, especially consumer facing, and even more so one like hospitality, where relationships play such a crucial role. However, relying on gut instinct and tradition is the norm, and whichever of the major players is able to step up and implement processes to collect, synthesize and act on data stands to profit from a considerable improvement in customer experience, service standards, and the restaurant's bottom line.



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