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Optimization is an important aspect of building a successful, profitable business in the restaurant industry. When your operations and staff are working efficiently, it’s easier to reduce waste and maximize productivity.

Restaurant analytics play a critical role in this process — by collecting data about each aspect of the business, you can establish a baseline understanding of current operations. From there, you can identify areas for improvement, measure results of optimization activities, and monitor ongoing performance.

Sound like something that could benefit your business? Let’s look at how you can use restaurant data analytics to boost your bottom line and improve the customer experience.

What are restaurant analytics, and how do you use them?

Restaurant analytics are data points created by gathering and analyzing information about your business. Each metric assigns a numerical value to a specific process so you can assess the restaurant operation objectively and track performance over time.

Data analytics create an in-depth picture of your restaurant’s financial metrics. They also provide valuable insights into factors such as prep time, delivery efficiency, and customer satisfaction.

Restaurant analytics can help you evaluate various aspects of your operation:

  • Menu design and menu item pricing
  • Inventory management 
  • Food waste
  • Guest behavior and preferences
  • Staff performance
  • Kitchen operations
  • Website traffic
  • Payment methods
  • Performance of targeted marketing campaigns
  • Online ordering vs. in-person ordering
  • Delivery volume

Many restaurants use data analytics to measure performance and find ways to improve. If you notice that it’s taking longer on average to prepare each meal, for example, you might decide to improve staff training, develop a more efficient kitchen workflow, or replace older equipment. Then, you can monitor the average prep time to see if your changes had the desired impact. Used effectively over time, restaurant analytics can help you make informed decisions that cut costs, increase profits, and improve the dining experience for delivery and in-house customers.

Thanks to the proliferation of digital restaurant systems, including POS software and payment processors, it’s easier than ever to gather data using streamlined technology. Restaurant operators and restaurant managers don’t need experience in big data or data science to make sense of the information — readily available data analysis tools take existing figures and output a variety of relevant metrics.

One popular program is Google Analytics, which tracks website traffic and conversions. Your restaurant management software or business intelligence platform may also have built-in data analytics, predictive analytics, or artificial intelligence tools that produce actionable insights.

What are the four types of restaurant customer data?

When you start digging into restaurant analytics, the sheer volume of information can feel overwhelming. It’s helpful to break the data you collect down into categories:

  1. Identity data covers basic information about your diners, enabling you to find your key demographics and spot opportunities for audience expansion. It includes things such as a customer’s name, age, birthday, location, ethnicity, gender, phone number and email address. Depending on your restaurant’s goals, your database might also include information about the customer’s family. You can take identity data a step further to add socioeconomic information such as job title, industry and approximate income.
  2. Engagement data includes details about how, when and how often customers interact with your restaurant. You can collect this information from your POS system or the analytics that are connected to your website, social media platforms or email marketing program. Useful metrics include website traffic, marketing email open rate, behavioral flow, click-through rate and conversions.
  3. Behavioral data covers the different ways diners engage with your restaurant. It could include order history, average order value, participation in loyalty programs and use of delivery promotions. On a broader scale, this data can also incorporate things such as email newsletter sign-ups and unsubscribes, creating an account on your delivery system and engagement on different types of devices.
  4. Attitudinal data involves customers’ attitudes toward your restaurant. It helps you track the opinion of your brand across your diners, the public and specific segments of your audience. For restaurants, it might cover the performance of a menu item, customer reactions to a pricing or feedback about a seasonal dish. This information typically comes from customer surveys, comment cards, online reviews and complaints.

Key performance indicators (KPIs) for the restaurant industry

Before you can use restaurant analytics to boost your business, you’ll need to decide which information to track. To start, select the key performance indicators (KPIs) that are most relevant to your operation. Every business is different, of course, but most restaurants can benefit from business analytics regarding sales data, profit margins, and customer behavior.

Some popular restaurant industry KPIs include:

  1. Delivery speed. This key piece of restaurant data shows how quickly your delivery drivers get food from the restaurant to customers’ locations. Ideally, it should be as fast as safely possible — that way, the food stays hot and guests stay happy. If your restaurant’s average speed is low, you can choose different routes, optimize the kitchen for delivery, or partner with a third-party delivery service.
  2. Average order size. Larger orders create more revenue. Boost this number by offering add-on items, such as appetizers, desserts, or drinks; it can do wonders for your bottom line. To overcome price hesitation and encourage customers to treat themselves, consider offering lower-priced add-ons and free or discounted delivery fees.
  3. Customer review scores. Track your average review score to get a sense of how customers perceive your restaurant business. If the score drops, examine negative feedback to find opportunities for improvement. Make sure to track the scores going forward to see if your adjustments result in better reviews.
  4. Order accuracy. A high order accuracy rate means customers usually get exactly what they ordered. This is critical — even small errors, such as forgetting to remove mayo or add onions, can negatively impact your brand. To improve this KPI, consider implementing new quality checks, adding more comprehensive staff training, or hiring more employees per shift.
  5. Average orders per shift and day. When you identify trends in order volume, it’s easier to adjust staffing and inventory to meet the demand. If the restaurant data indicates you’re the busiest on Wednesday and Friday evenings, for example, consider scheduling more servers; on slow Tuesday mornings, you might cut costs by going with a skeleton crew. This KPI also helps you determine the best times to add incentives to shore up slow periods — you could add promotions during off-peak orders, offer in-house specials, or reduce delivery minimums.
  6. Food cost percentage. This data analytics metric expresses your ingredient costs as a percentage of the revenue those ingredients produce. A high percentage usually means your food costs are eating into your profit margins. When that happens, you might look into adjusting inventory, negotiating better deals with suppliers, or revisiting your menu pricing.
  7. Customer support requests. If a restaurant guest contacts customer support, it almost always indicates a problem. Tracking the number of online support tickets, phone calls, or in-person requests can help you gauge the overall performance of your restaurant. When the number increases, it’s a sign that something is going wrong in the business; at that point, you can dig into the customer feedback to identify and address the cause.
  8. Social media engagement. About 37% of customers use social media platforms to get information about restaurants. Measure the effectiveness of your social media presence by tracking metrics such as likes, comments, follows, unfollows, and profile link clicks. To improve these KPIs, you can post more frequently, experiment with different content types, and ensure your profiles are complete.
  9. Ad conversion rate. By calculating how many ad viewers convert into paying customers, you can determine the ROI of each digital restaurant marketing campaign. If conversions are low, it can be helpful to target a different audience segment or invest in a different platform.

No matter which restaurant analytics you choose, continuous monitoring is key. Tracking performance over time enables you to spot dips and take corrective action quickly.

Get more restaurant insights with Grubhub

As a restaurant owner, you have a great deal of data at your disposal. Restaurant analytics help you put that information to use to improve the business, serve customers efficiently, and boost profitability.

Need more restaurant data from your delivery operations? Switch to Grubhub — the Customer Insights dashboard collects and analyzes delivery, order, and customer data automatically, so you can check KPIs, including sales, average daily orders, and more at a glance. You can even segment that information to monitor restaurant analytics performance by date and customer type. To try it out, partner with Grubhub today.