Menus are a critical part of every food service establishment.

In a QSR setting, menus are doubly important; they’re the primary way we communicate with the customer about our offers. In this article, we’ll look at the importance of your menus. Then we’ll delve into how you can make smarter menu decisions – not just with the physical menu board design, but with what items you sell – using data analytics.

Why good menu design is important

Your menu board is the main way you communicate with your guests; it’s your best sales rep. When your menu board is well-designed, people can quickly find the items they want. This results in shorter ordering times and a better order flow.

Where you place items on a physical menu can also affect your sales. Top sellers and items with a better cost-to-profit ratio are often given featured spots. Menu optimization has been called one of the most profitable QSR operations investments for good reason.

Most importantly, your menu and the foods you offer on it speak directly about your brand. It’s an integral part of the customer experience.

Even so, many restaurants face challenges in designing their menu. Without accurate data, it can be hard to determine which items to feature and which to drop. This can impact everything from budgeting to food waste. And in today’s highly personalized world, many customers expect a menu that’s tailored to their particular tastes. Let’s see how data analytics can help us cope with these challenges.

6 Ways data analytics can improve QSR menu design

We’ve already mentioned how a Customer Data Platform or other analytics-ready data collection system is a priority in the QSR tech stack. And that’s for a good reason; you can harness this data to make key decisions about your menu in several ways. These include:

Optimizing menu pricing. Sales and food cost data can be analyzed to determine the optimal price for menu items. This takes into account customer demand, ingredient costs, and the item’s overall profitability.
Understanding customer preferences and trends. We’ve already written about how customer data can transform your menu; in this case, you can aggregate data to learn which menu items are the most popular at various locations. This leads to smarter choices on what menu items to feature, bring back, or discontinue.
Customizing individual menus. You can also zoom in to individual customers’ order history, location, and preferences to customize an online or mobile app menu just for them. This not only improves their user experience, it fosters customer satisfaction and loyalty.
Reducing food waste. Inventory management data can combine with order and purchase data to identify which foods are creating unnecessary food waste (e.g. because the items have to be prepped ahead of time, but they aren’t big sellers). This can inform decisions on which items to keep on a menu, which trickles down to cost savings and greater sustainability.
Planning future menus. Data analytics and machine learning algorithms can find patterns in historical data and use these to predict future customer demand. This allows restaurants to create menus that feature the right items at the right time – thus delighting customers with the optimal selection of returning and season-appropriate favorites.
Fine-tuning menu board design. Data analytics tools make it easy to analyze the cost, sales, and demand for menu items, but they also help operators determine the best physical layout of menu boards. Adjusting the overall board design as well as the placement and price of individual products can improve how customers read the board. It can also influence the demand and profitability of items.

How to use data to optimize your menu

All of the outcomes mentioned in the previous section sound great. So, how do we go from idea to reality? In other words, how do we put them into operation?

It’s not as hard as you might think.

Optimizing menu pricing

Collect sales, customer demographic, and ingredient cost data.
Use a data analytics tool or platform to analyze this data and determine optimal prices for each menu item.
Periodically review and adjust menu pricing as new sales and customer data becomes available.

Understanding customer preferences and trends

Collect data on customer demographics, location, and orders.
Use a data analytics tool or platform to find trends in item popularity and demand.
Add, discontinue, keep, or reintroduce items based on these trends.

Customizing individual menus

Collect data on customer demographics, location, and orders.
Use a data analytics tool or platform to analyze each customer’s data and create individualized menu recommendations.
Add these personalized menus to your restaurant’s ordering system. This will build customer satisfaction and loyalty as you deliver the personalized experience so many guests expect.

Reducing food waste

Collect data on food waste, orders, and inventory management.
Use a data analytics tool or platform to uncover items that cause disproportionate waste.
Adjust menu offerings and purchasing practices to reduce food and budgetary waste.

Planning future menus

Collect data on sales, customer demographics, and inventory management.
Use a data analytics tool or platform to predict future demand for assorted menu items.
Adjust menu offerings and purchasing practices to prepare for increased or reduced demand, thus reducing waste while anticipating and fulfilling customer needs.

Fine-tuning menuboard design

Collect data on sales, menu item costs and popularity, and order trends.
Use a data analytics tool or platform to determine which menu items to feature and at what price points. You can also analyze how item placement on a menu impacts its sales and use that information to improve menu design and layout.
Periodically review and adjust menu offerings and design as new customer demand and profitability data is available.

As you can see, a good data analysis suite is a major ingredient to using data to effectively design and adjust your menu.

The benefits of a data-driven menu

Your menu is a key part of your business. Everything about it – from how items are organized to how often you update offerings and prices – can be fine-tuned by data analytics. And since you probably have most of this data anyway, why not put it to use? This can help you reduce wasted time, effort, and money while strengthening your sales and customer satisfaction.

If you think you’re leaving some of your data’s value on the table, then contact the Tillster team. We’ll help you analyze your tech environment and find ways to get the maximum benefit from the data you have.