Big data for restaurants opens insight into customer attitudes, operational efficiency, order fulfillment, and every other restaurant KPI. That's restaurant data intelligence in the industry.

Through surveys, cell phones, and POS systems—restaurateurs collect data in every touchpoint they can (while following privacy and security standards). 

As a result, an enormous mountain of restaurant data gains momentum with each customer order, response, and interaction with restaurants. Sheer volume poses a veritable challenge. How do you ensure quality, structure, organization, and—most importantly—profitable value through restaurant data analytics? 

Well, we’re here to expose the beating heart of your restaurant’s customer information. Wield knowledge in the battle over customer loyalty, and learn these 3 collection, analysis, and optimization strategies for big data in restaurants. Increase customer satisfaction, sales metrics, and control of your supply chain.

Key Takeaway: Using big data for restaurants for insight improves satisfaction, labor costs, stock control, menu management, and more operations in F&B.

3 Collection Methods for Big Restaurant Data

How does McDonald’s successfully serve millions of customers each day in over 35,000 locations around the world? 

They’ve embraced big data collection, analysis, and technology for insight into what’s coming next for their global brand. Without effective collection methods—like surveys, apps, and payment data—they might have lost their market footing. 

Let’s follow suit and explore big data collection methods for restaurants.

Customer Feedback Surveys

A staple of restaurant intelligence, the customer survey remains one of the most personal, effective ways to gain the trust of customers. 

Surveys reveal the specific quantitative (number-based) and qualitative (feeling-based) elements that create healthy, and haphazard, customer experiences. By profiling customers through survey data, restaurants see the traits or opinions of loyal guests and eager orders. 

Of course, it’s vital to structure customer surveys with a specific emphasis on identifying strengths, weaknesses, and opportunities. For help, read our article on the four types of customer survey questions, with over 20 examples.

Mobile Data Collection

Smartphones are magnets of information. Your customers' device can help you steer restaurant strategy if you can store location information with cookies, permissions, and GPS. 

Your restaurant equipment and smartphones are themselves key drivers of business or restaurant intelligence as well. Mobile restaurant data is real-time, meaning all-staff alignment as labor solution. 

Equip restaurant teams with a route-optimizing delivery provider.

POS System Integration

Because they handle all transactions, point-of-sale (POS) systems open incredible possibilities for restaurants. Coming from registers, custom devices, or cloud software on tablets or phones, POS system data captures insights about inventory, sales, customers, and staff. 

To the benefit of restaurant owners and managers, modern mPOS system data and even those using POS partners go to the item level, giving a fine-toothed clarity to decision-makers.

3 Analytical Takes on Big Data for Restaurants

Analysis will transform your data from siloed stillness to material, measurable action. As you monitor staff, order accuracy, customer retention, and more KPIs, several tools can help you climb the growing data mountain to get a bird's-eye view of your operations. 

In truth, your analysis will always include a measure of statistical probability, and uncertainty, but gaps close as you train systems to anticipate customers and conditions.

Measure with Machine Learning

In previous years, restaurant owners relied on long-game guesswork (and observation of results) to fine-tune revenue, satisfaction, and service. Today, the situation is changed. 

You won't need to know how to code learning algorithms to take advantage of machine-speed data analysis. By feeding your data into online ordering solutions that feature advanced restaurant reporting and analytics, you quickly uncover connections that it could take human minds weeks, months, or years to work out. 

Conceive of optimizing a menu thanks to machine learning: you’d know precisely which dishes to feature in your restaurant menu designs. And, online ordering software would allow menu management for changing items, recipes, and descriptions instantly across platforms. It’s not a bad way to maximize restaurant profits.

Visualize with Intelligence Tools

Many tools assist with data analysis through much simpler means than artificial intelligence, neural networks, or advanced algorithms.

Simply by visualizing your data and business intelligence through interactive charts, dashboards, and graphs—you quickly observe and monitor relationships. Sometimes by showing data in a tangible format, hidden patterns, trends, and relationships are revealed. 

There are many tools you can turn to for visualizing your data. While you’ll have access to easy, live dashboards through Revolution Ordering—there are also solutions from Microsoft, Tableau, and Looker—for example.

Anticipate with Statistical Modeling

Beyond noticing live relationships between order volumes and inventory levels (for instance), you can start to predict future events and business patterns with big data analysis approaches. 

One such technique in data analytics is known as predictive modeling. The point is to see ahead. An event, behavior, or effect can be determined by multiple signals that already sit in your data. 

For instance, restaurant tech sporting predictive modeling would set every variable against itself. Think of revealing hidden chains of events based on order times, order amounts, order volumes, promotional decisions, customer feedback, reviews, or even social media data. 

Some restaurants scrape data from publicly available databases and relevant social media accounts to inform their models and forecasting. If you want to enhance your stored data for even more predictive insight, consider plugging into food data sources.

3 Biggest Benefits of Restaurant Data Analysis

Big data balances challenges and pressures for restaurants. For instance, online ordering systems help restaurants collect buying data, shopping trends, customer preferences, and profile information. 

In turn, this growing database can inform decisions that impact customer experience, improve menus, and streamline operations.

Improve Customer Experiences

You can use big data to increase revenue by tailoring marketing and service strategies according to the best guesses, forecasts, and predictions made by increasingly accurate analysis of your data. 

Some examples include knowing precise portioning in recipes for cost reduction as well as better scheduling for labor savings and lower operating expenses according to decisive data insight. 

That’s why it’s key to combine data from multiple sources—like POS systems, CRM solutions, and ERP software. Your insights are only as reliable and helpful as your data is clean, comprehensive, and complete.

Maximize Menu Profitability

Menu management demands an almost cellular-level of insight into which items attract customers and their food costs. In doing the right analysis of food data and offers, you can identify the popular and unpopular, profitable and unprofitable. 

Working with your data, you’ll finally find support for where to increase item pricing, lower overhead, and make restaurant strides into more profitability, productivity, and satisfaction for all. 

Restaurants who successfully use these data collection and analysis methods to implement new policies and recipes increase their profits by 10% on average. Of course, gains can be much larger with the size and strength of the restaurant’s dataset.

Streamline Restaurant Supply

Finally, in the supply chain, it’s valuable to know how to minimize waste and predict demand based on trend and behavior analysis. You then make better logistical decisions, determine inventory orders more precisely, and know just which customers to anticipate and when. 

Ultimately, as restaurants place more trust in data, analytics, and algorithms (or restaurant AI), the entire industry is seeing a revolution in the meaning of hospitality, service, and customer satisfaction. 

Frequently Asked Questions About Big Data in Restaurants

In today's data-driven era, understanding the subtle interplay of customer preferences, operational efficiencies, and culinary innovation can set your restaurant apart. 

We want to demystify how industry leaders leverage big data to supercharge their strategies and revenue. Learn how to use big data for restaurants below.

How is big data used in restaurants?

Big data fuels restaurant analytics, deciphering the "what" and "why" behind sales patterns. 

In other words, it looks at order volumes, consumer information, and buying behavior to provide meaningful, accurate predictions.

How do restaurant chains use big data?

Major restaurant chains leverage insights from mobile, food data analytics, AI, and ordering integration technology to improve their approach to the market.

Just like any other restaurant, well-known chains like KFC, McDonald's, and Golden Corral’s online ordering analyze customer data and behavior to boost experiences and increase sales.

How can data analytics help restaurants?

Big data analytics help guide menu decisions, identify marketing opportunities, and highlight popular or underperforming dishes for improved consideration. 

For instance, a high-ordered item with few re-orders invites further investigation. Restaurant tech innovations can stir up many more questions for managers and stakeholders to ponder—and then take action.