Chain restaurants have access to thousands upon thousands of data points that can offer insight into customers’ purchase habits. Understanding this buying behavior can be invaluable for those tasked with menu strategy and pricing.
However, the data can be overwhelming because the sample size gets huge in a hurry. How do you make sense of all this information in order to divine intelligence that will inform your menu strategy, including promotion planning?
For help in sorting through the information, here are five questions to ask that will enable you to use data to drive decision-making:
1. How often are certain items purchased together or by themselves?
This is important information that can help you structure the menu so you can maximize your chain’s profitability. Items that are sold alone indicate items that may be strong traffic drivers.
Understanding which items are purchased together allows brands to influence purchase behavior. For example, let’s say you find out that mushrooms are a popular add-on for your steaks. You may want to structure the menu so mushrooms are highlighted closer to the listing of the steaks, encouraging customers to do the add-on.
2. Which items drive the bulk of your transactions?
Quite simply, if you want to make the maximum impact on your bottom line, think about changing prices on a few of your most popular items, instead of doing widespread pricing changes that might draw attention and tick customers off.
This knowledge also can help you make smart decisions as you plan promotions. Brands often do limited-time promotions, and you need to know whether they are working for you.
If you are selling an item for 99 cents, are people buying it alone or using it as an add-on? If the special isn’t getting customers to try other parts of your menu, they may never come back.
3. Which items are most commonly upgraded?
A common way to upsell salads these days is to have an optional protein add-on, like chicken or fish. Learn which items are being upgraded most often and how, and then you can think about inventive ways to encourage customers to do even more upgrades.
4. How big is the average check for transactions featuring a certain product line vs. other product lines or vs. the restaurant’s average check in general?
This is particularly important information to know when you are gauging the value of a promotion. When you run a promotion, the goal is that either people are spending more money overall, or more people are coming in, widening your customer base.
The worst thing is a promotion that results in no new customers coming in the door, and in having customers now spend less per check.
5. How do your transactions in certain categories break down by parts of the day, or day of the week? Are there changes in the mix of products sold on days when advertising runs vs. when it doesn’t?
Study the configuration of checks by price range. For example, at a fast-food restaurant, you may find out that 30 percent of the checks between $0 and $2 only have one value item, or that 30 percent of the checks between $2 and $4 have a dessert.
Having this information is the first step towards understanding the profitability of each transaction, which can help determine specials you offer – and how well your advertising is working.
Ultimately, to gain this level of understanding of your customer transaction data, you also need an internal focus at your company, tied to a commitment to spending the time and money required for the analysis.
Many progressive restaurant companies have IT leadership that understands the need for analyzing data as a first step toward innovation. This type of leadership is critical, along with an understanding by the marketing department that good menu decision-making should include consideration of actual sales data and not just on surveys that show what customers says they will do.
The time and effort will pay off. Done right, smarter menu pricing and promotions can have a huge impact on your bottom line, in a way where they won’t negatively impact your customer traffic.
How does your restaurant use data to drive menu decision-making? Join the conversation in the comments below.
