How Restaurants Can Use Data to Improve Customer Relationships and Sales – Part II

Previously on the blog, I wrote about why restaurants should be thinking about their customers’ data.  But perhaps the more pressing question is how.

It’s a typical Friday evening at your restaurant. Reservations are fully booked, customers are lined up outside hoping to get a table, your best waiters are on the floor, there hasn’t been one verbal complaint all night and a waiter just closed a bill 50% higher than your average check on a Friday night. It’s a great night, or so you think. What you don’t know is that behind the scenes, the most popular dish on the menu costs you $1.50 more to make than your selling price because the cost of tomatoes skyrocketed this week, your top server just got a 10% tip from one of your best customers who has never left less than 25%, someone just posted a horrible review on Yelp about your hairy clam chowder and 60% of your liquor sales are wine by the glass. Don’t worry, you’ll know most of this eventually, but it may be too late.

In a data-savvy restaurant, all of the above situations would be monitored and detected using information stored at various customer service points. These restaurants are able to gather information quickly and in real time to identify the above issues even before the end of the night. For example, menu pricing can be monitored through the ingredient and recipe functionality in most ordering systems. All tip information, if stored by customer, can be compared to previous visits to identify potential anomalies in service. Reviews can be monitored in real time so quickly that the manager may be able to resolve the problem before the customer even leaves the restaurant. Liquor sales versus bottle sales can be scrutinized down to the time of day, specific server, area of the restaurant and type of customer.

Even for restaurants without sophisticated data integration, data gathering is actually quite straightforward. Most restaurant owners may argue that their reservation system does not talk to the point-of-service (POS), but it isn’t so much about having tools that talk to each other as it is about having tools with relating data. Let’s say you’re a manager and you want to know what the typical order is for your best customer, Bob Foodie. Mr. Foodie makes a reservation through your reservation system for lunch as he always does. When he walks into your restaurant, you already have his phone number, name and number of previous visits. All you have to do is figure out how to link that information with the POS order for future analysis. If the hostess simply had a label to give to the server with this information on it, the server could use this phone number as the title of the POS order. Once the order is entered and the phone number is referenced, it is just a matter of analyzing the information to identify certain patterns. If you can slightly change some of your staff’s processes, you may be able to vastly change the amount of information you have on your customers in order to make better business decisions.

Collecting data like the above example can be extremely helpful in answering questions like:

♦ How can I make more money during my slowest hours?
♦ Why does waiter X get tips of 25% while waiter Y never breaks 15%?
♦ What is the ROI on my newest salad and how does the fluctuating price of the ingredients affect my pricing?
♦ How many customers return to my restaurant in a month and why?
♦ When and where are my best reviews occurring?

Analytics give businesses the power to turn servers into sales people, managers into relationship builders, and staff into much more efficient and well-informed employees.  It is simply a matter of using the data you are already collecting in a more efficient and useful manner.

Keep an eye out for the final installment of this series where I’ll share a real-life example of how data integration improved a restaurant’s bottom line.

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