How Data Science Plays a Role in the Food Industry

Image Credit: image via Pexels

With over 1 million restaurants in the U.S., the food industry is competitive. As a food industry professional, it’s crucial to cater to your customer’s needs so you can continue to run a successful business in this saturated market. A key challenge you face is learning what customers to target with your marketing and what your customers want in your food-related business.

Data science and data analytics can help you identify your customers’ needs with accuracy. You can easily hone in on what your business needs to focus on to grow and succeed. Your inventory levels, production process and delivery procedures may also be improved when you harness the power of data science in your business.

Mining the power of good data will help your food business please customers and thrive in the marketplace. There are several ways data science plays a crucial role in the food industry.

Daily Operations

When you’re educated in data science, such as master’s in data science, you can use this knowledge to analyze market trends and consumer patterns. This data helps you create daily operation schedules and procedures that are effective and attractive for potential customers.

Using data, you can analyze your stock and the menu choices that many consumers gravitate toward. This shows you what types of food items you need to order daily to ensure your employees have the right supplies to meet customer demand.

Analyzing customer traffic patterns may also help you create effective employee staffing schedules. You can keep your establishment adequately staffed to assist customers in busy times while avoiding wasting money by staffing too many workers during off-hours.


Convenient online food delivery companies, such as UberEats and GrubHub, have made it easier for households to order food regularly. Even if your establishment doesn’t specialize in food delivery, it’s crucial to ensure your food preparation times and delivery packaging is acceptable to accommodate customers who use these services.

By using data analytics to collect information and data governance to ensure the information is organized and easily accessible, you can better understand how your business is performing in the food delivery sector. By implementing data analytic systems and processes, you can easily monitor and track orders to accurately provide estimated delivery times to customers.

Food Shelf Life

According to a 2018 study, 60% of customers judge restaurants based on food quality. Serving food that has the highest quality and best taste may be what sets you apart from competitors. There’s a fine line between ensuring you have enough stock to provide to your customers without overbuying and wasting food.

Through effective big data governance organization techniques, you can sort through data that relates to the ingredients you carry on your shelves. Pinpointing the shelf life of these foods ensures you only serve fresh ingredients. It also eliminates waste and makes it easier to know exactly when you need to replenish inventory.

Marketing and Advertising

If you don’t use data analytics in your marketing, you could be wasting money on blind advertising campaigns that may not contribute to profit or growth. It’s crucial to first identify your target customer and the best platforms, times and strategies to market to them. A marketing analyst can assist in designing an effective marketing campaign by obtaining information about:

  • When your products are relevant.
  • Where your target customers spend their time.
  • What marketing platforms cater to your product.
  • The factors that affect your customers’ decision to buy.

For example, you may find your target customer is a city dweller in their late 20s to early 30s. You may also learn that this target consumer spends a lot of time on social media and is more likely to order food delivery than to eat in a restaurant. To reach consumers in this age group, you might launch a social media-heavy advertising campaign that focuses on your business’s quick and convenient food delivery.

Identifying when and how to reach your target customers before launching your marketing campaign can lead to more successful advertising that intrigues and attracts customers.

Quality Control

Data analytics can also be used to ensure your products meet certain quality control standards. If you’re manufacturing food products, the packaging and ingredients directly affect product quality. By analyzing all the components along your supply chain, you can use this data to identify different ways to improve quality control.

Catching these issues before they reach consumers preserves your brand’s integrity, setting you on track toward sales growth.

Supply Chain Transparency

Since most customers find food quality to be a top priority, it’s no wonder they also desire supply chain transparency. Consumers want to know where their food comes from, how it was raised or grown and how it was processed.

With data science, you can offer your consumers an in-depth look at the supply chain and show them where your product came from. You may even create data visualization aids to show that your meat was raised in a cruelty-free environment or that no pesticides were used where your produce was grown. These visualizations can integrate transparency with your marketing campaign, making your supply chain part of your brand identity.

Identifying the goods, sources and processes used to create your products allows your customers to understand what they’re consuming. When you use data to show customers that your supply chain processes are environmentally friendly and healthy, they may feel confident in the quality of your product.

While the roots of data science may be based in the technology sector, analyzing data is an important process in the food industry. Whether you’re using data to develop an effective marketing campaign or provide a visualization of your supply chain for consumers, data science plays a key role in your production and sales.

Last updated: September 2020