Restaurant data analytics: how to turn insights into action

Published: April 2023 | Updated: April 2025

Maintaining a restaurant’s success is a bit like walking a tightrope. Profit margins are so thin that balancing different business needs can feel precarious. Each time something changes—a rise in food costs, a sudden labor shortage, or an unexpected surge in orders—you have to respond quickly to regain balance.

It’s hard to track and manage these factors. But restaurant data analytics solutions are making things easier. In this article, we’ll explore the basics of restaurant data analytics, including:

• What is restaurant data analytics?
• Types of restaurant data
• How to collect restaurant data
• 6 ways to use restaurant data analytics in your business
• How data analytics from Uber Eats can add value to your business

Restaurant data analytics is the process of analyzing all the data you have on your restaurant’s performance and operations in order to gain meaningful insights. By leveraging restaurant data analytics, you can learn from past performance, identify meaningful trends, and approach decision-making with more precision. This process breaks down into 2 main components:

• Restaurant data refers to the metrics you track over the course of doing business. Today, this information is largely collected automatically with software tools.

• Restaurant analytics is the process of interpreting that data to identify meaningful trends and takeaways you can use to strengthen your business strategy.

Understanding different types of data and how they relate to your goals can guide where to focus your energy and resources. You can group data in many ways, but below are some of the most important categories for restaurant operators to monitor.

Sales data sheds light on the number of purchases customers have made in a given period. Important sales data to track includes:

• Number of orders placed through different sales channels (online, in-person, third-party apps)
• Best-selling and most profitable menu items
• Average value of each order
• Total amount of revenue generated from sales

Customer data reveals who your customers are, what they like about you, and how often they come back. For this type of data, you’ll want to monitor:

• Number of new versus returning customers
• Loyalty program growth and participation
• Online reservation volume
• Customer reviews and ratings

Operations data points to how well your business is run. It can help you identify ways to cut costs, reduce errors, and improve overall efficiency. Key areas you’ll want to pay attention to might include:

• Order data, such as order error instances and order preparation time
• Service data, such as how often your restaurant is available for online ordering relative to your restaurant’s hours of operation
• Inventory data, such as your stock record and budget breakdown
• Labor data, such as scheduling, payroll, and benefits information

Now that technology does much of the work collecting restaurant data analytics, your main job is using the insights you learn. Below are some of the main ways you can do that to improve your business.

Getting your menu right is one of the most important parts of running a successful restaurant. With data analytics, you can discover what works well on your menu and where there’s room for improvement. Some important menu insights you can gain from analytics include:

• Best-selling items. Paying attention to bestsellers can inform inventory needs, influence menu design, and even inspire new offerings based on customer preferences. AI is becoming a powerful tool in this area by analyzing vast amounts of data to suggest menu refinements and new offerings.

  
  

• Most profitable items. If your most popular items involve expensive ingredients, your net profits on those items could still be low. If you know that other items earn you higher profits, you can focus a greater portion of your marketing efforts on them and encourage staff to recommend them more often.

  
  

• Common substitutions and customizations. If customers almost always ask you to hold the mayo on a particular sandwich, you may want to update your menu so the common substitution becomes the default. If you notice that a frequent substitution increases your costs, you may want to start charging extra for it.

  
  

• Order issues: If you’re starting to see a rise in complaints regarding certain dishes or overall concerns about food quality or taste, your data can help you spot those trends, pinpoint problem areas, and address the issues.

  
  

• Conversion insights: Analytics can help you better understand how often your menu items are converting browsers into buyers. If you’re trying to entice more customers and drive sales, Uber Eats can help you improve your storefront with AI-generated menu descriptions that you can review, approve, and edit at any time.

Employees are one of the most expensive parts of running a business—and one of the most crucial ingredients to long-term success. With staffing insights, you can make sure you’re:

• Matching your scheduling to your needs. Tracking how customer traffic ebbs and flows can help you make strategic scheduling decisions. By scheduling only the staff you need, you can manage labor costs while balancing the customer experience.

  
  

• Making smarter hiring decisions. Staff analytics can shape strategic decisions around hiring and retention. If, for example, your data shows you’re investing a significant amount of resources on recruiting, only to lose staff soon after hiring them, you may want to shift some of that budget toward professional development and retention.

  
  

• Applying customer feedback: Sharing customer feedback with employees can help them tailor their service to better meet customer needs. Uber Eats lets you view AI-powered summaries of customer reviews, along with recommended actions you can take to improve customer satisfaction.

You can’t make an omelet without eggs—and running out of eggs during Sunday brunch could mean lost sales, unhappy customers, and stressed employees. Inventory data analytics confirms that you’re keeping the right amount of food by helping you spot:

• When it’s time to restock. Inventory data tracks which supplies are starting to dwindle while you still have time to order more. Some inventory tracking software includes forecasting features that use past trends to predict when you’ll need more of an item and how much to order.

  
  

• Overuse of key ingredients. If your kitchen staff tends to have a heavy hand when adding ingredients to dishes, you want to know about it. You can improve your training and give staff feedback on how to make important (and costly) ingredients go further.

  
  

• Food waste. Running out of important ingredients is inconvenient, but having to throw out unused food is even worse for your bottom line. Inventory analytics can identify food items that need to be used quickly to avoid going bad—and which you should buy less often.

For customers who place off-premises orders with your business, the delivery experience will play an important role in how they feel about your brand. Delivery analytics help you:

• Improve delivery time estimates. Providing customers with accurate delivery estimates sets realistic expectations, which can improve their overall experience. Monitoring your food prep times can provide you with information you can use to keep hungry customers in the loop.

  
  

• Refine your delivery menu. If data suggests that delivery customers are less satisfied with certain items than in-person visitors, you can use that information to improve your delivery menu. And if data reveals that deliveries are especially lucrative for your business, you may even consider starting a delivery-only virtual restaurant that operates from your current kitchen as a way to further boost profits.

  
  

• Expand your delivery options. If your POS system reveals that a rising number of customers are placing orders through your own sales channels, you can use that data to make strategic expansions to your delivery infrastructure. For example, with a white-label delivery solution, you can add on-demand delivery to your website or app without incurring the cost of building your own delivery fleet.

Your restaurant’s reputation hinges on the customer experience. Analytics can provide you with a better understanding of what your customers think and ways to increase their satisfaction. This is especially important in the current restaurant landscape, where up to 64% of customers say their dining experience is more important than the cost of the meal. With customer satisfaction data, you can:

• Reduce discounts and comped orders. When customers have a negative experience, comping items or providing discounts is a standard practice to smooth things over. But this can become costly. Tracking how often you reimburse customers can uncover key process issues—and possible solutions.

  
  

• Improve customer retention. With customer data, you can identify and nurture your loyal customers. Use information about ordering habits to craft personalized recommendations and offers that will keep regulars coming back.

The restaurant business is unpredictable. But we now have impressive AI-powered tools that can reduce uncertainty about the future. Software products with data forecasting features like predictive analytics use past data to make projections. With data forecasting, restaurants can:

• Improve staffing and inventory management. Data forecasting can predict how busy your restaurant is likely to be at certain times. It can also reveal ordering trends. Together, this information can help you shape schedules and determine inventory needs far before a seasonal rush hits.

  
  

• Make strategic spending decisions. Data forecasting also empowers you to make smarter decisions about spending. If you’re considering a substantial investment—say, in a new physical location or marketing initiative—it’s easier to make a decision if you have an idea of your expected profits. Data forecasting can’t promise exact numbers, but it can provide useful estimates.