Blog

How Fragmented Data Can Boost Food Service Profits

05.11.2016 by Naini Mandala


The more consumers disrupt the food service industry, the more pervasive big data and analytics solutions become. Operators and franchisees are finding that data analytics solutions provide them with insight into how they can drive sales and increase their bottom line. This motivates them to revamp strategies and create customer incentives to maximize profits. There’s only one problem: Operators aren’t really maximizing big data’s potential. They’re not using the data to tailor strategies to consumer preferences.

As you very well know, the key to maintaining relevance in the eyes of your customers is to understand (and give them) what they want. This requires continual innovation, as consumer preferences are constantly changing. This means that food service operators need to have constant insight into consumer preferences across all locations. It’s not enough to know which items customers purchase at one location. You have to collect data from each location in order to have a comprehensive view of customer purchases and find patterns among consumer preferences.

This is where prescriptive analytics come in. Prescriptive analytics gather location-specific data to provide you with a holistic view of your operations. This holistic view allows you to understand fragmented information like which products customers purchase most at each location or what foods are most popular during a particular daypart. You can then use this information to better understand what and when your customers purchase, allowing you to make more informed operational decisions and tailor marketing efforts to maximize sales.

More Informed Operational Decisions
Because your consumers are the lifeblood of your organization, it’s essential that they’re at the center of every decision made throughout your operations. Implementing a solution like Spark Analytics provides you with insight into customer preferences—down to the daypart. You’re able to see what and when customers are purchasing, which gives you the opportunity to offer products and promotions they will be most interested in. By collecting data from every location, you see which products and promotions perform better in which regions. With this kind of visibility, you know where sales are falling and where you need to improve to better serve customers as soon as they walk in the door. This allows you to be more efficient throughout your organization, which helps you better manage food and labor costs.

Maximize Marketing Effectiveness
As we move towards a digitized food industry, understanding how well promotions perform is more important than ever—and prescriptive analytics can help. When it comes to gauging a current promotion’s effectiveness, analytics will show you the purchase frequency of products associated with the promotion. This will tell you which specific locations and employees are pushing a promotion as well as which ones aren’t, so you can take immediate action to improve performance.

Analytics also allow you to discover new opportunities to push promotions. If you notice customers are purchasing an item during a particular daypart, this presents an opportunity to create a BOGO promotion or offer a supplemental item at a discount to increase sales. The analytics solution can then track the new promotion’s performance and recommend action items to improve effectiveness when and wherever necessary.

Fragmented Data Makes the Difference
As it does with everything else, “the whole is greater than the sum of its parts” pertains to data analytics. By itself, siloed data from each location won’t do your company a lot of good. It’s the collecting and analyzing of fragmented customer data that makes a difference. This bird’s eye view of consumer preferences is what enables you to make changes in your organization, allowing you to better serve your customers at every location. Because happy customers are the difference between increased profit margins and losing to the competition.


« Back to Main Blog

Recent Posts

Subscribe to Our Blog

A Few of Our Clients

Customers across the globe rely on Spark Analytics for ground-level visibility into their daily operations.

  • Supervalu
  • Compass
  • Ahold
  • Boots
  • Ruby Tuesday