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How Fast Food Can Make Use of Big Data and Analytics

Mar 31, 2017

Though often criticized for its nutritional value, fast food is here to stay. The increasing prevalence of fast food restaurants is offering a greater number of people with affordable and varied meal options, as well as treats, beverages, baked goods, and more. The fast-paced nature of service and sizeable menus of these restaurants require them to run smoothly and efficiently in order to keep customers happy and profits rolling in, a task that can seem difficult to anyone who has been in a crowded fast food restaurant trying to get a chicken nugget meal at 2 am. Luckily, big data and food and beverage data analysis are here to save the day. Using data analytics, every french fry, late-night chicken nugget, and ice cream sundae sold generates data for fast food chains to analyze and act on, improving quality across the board. Here are a few ways that the fast food industry can use data and analytics to change their business practices and make business decisions:

Test New Products

Fast food chains can use data analytics to evaluate the financial impact and popularity of new products—including food items and in-restaurant technologies—before they implement them. Using food and beverage analytics to look at how customers interact with drive-through menus, for example, can give chains insights as to how they will react to certain technologies and changes. They can also utilize publicly-available data for further knowledge of customer preferences and habits. Additionally, chains can conduct surveys that will allow customers to give them direct feedback about how they would respond to a new product or in-store attraction or service.

Improve Operations

As more and more fast food restaurants begin to offer delivery, they can use analytics to increase the speed and quality of service. They can also derive insights from the data collected from delivery orders, and get a better picture of where their customers live and what they are willing to spend money on having delivered. Analytics and big data can also improve in-store operations—for example, chains could analyze data on wait times to improve service and decrease the amount of time customers spend standing in line to order and receive their food, or could use findings from food and beverage data analysis and food and beverage industry predictive analytics to alter staffing schedules in accordance with the busiest days and times an individual restaurant experiences.

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Cater More Effectively to Customers

Analysis of data about what food products customers prefer can help fast food chains to optimize their menus and increase sales. The use of food and beverage analysis for fast food menus lets chains know what the most popular or most frequently purchased menu items are, as well as which largely unpopular items they can cut to save costs without much outcry from customers. It can also tell them what changes they can make to their menu to expand their customer base—data about the prevalence of food allergies, for example, can help chains decide what ingredients to alter or omit so that a larger number of people can safely access their products.

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