How Big Data Benefits the Food Service Industry

The epidemic has accelerated the need for improved data analytics in the food industry.

FREMONT, CA: Most of today's data is in unstructured formats, such as tweets, blogs, photos, and videos. Historically, businesses were unable to gain insights from this type of data. However, using Big Data technology, people can combine unstructured and structured data to gain valuable insights into client behaviour and purchasing habits.

People can now connect tweets, Facebook posts, blogs, and other social media activity with sales and transaction data for a brand, sentiment, affinity, and propensity analytics.

Examples:

• Monitoring Big Data available on blogs, forums, customer review sites, video, photo portals, and other social media channels can provide real-time insights into customers, products, and competitors.
• Menu items that need to be improved or eliminated can be identified based on customer feedback obtained through customer feedback channels such as online surveys and suggestion lists.
• Apps based on Big Data technology track millions of restaurant menu items and their accompanying components; they use analytic approaches to provide high-quality, granular data for commercial and consumer use. This allows managers to acquire insight into dining trends in various regions and estimate how popular a new dish will be. Menus can then be tailored to a particular area or region based on ethnicity, seasonality, and demographics.

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Marketing and Advertising

Big Data analytics in marketing and advertising allows marketing departments to better target their customers by forecasting consumer behaviour and enhancing the efficacy of their marketing expenditure.

Examples:

• Advertising and promotional campaign efficacy can be measured to optimize promotional offerings and forecast future campaign success.
• Real-time campaign performance monitoring can assist reduce excessive campaign spending.
• Improve the efficiency of cooperative marketing campaigns with suppliers and other dealers by combining data from many CRM systems to discover what menu items particular customers want.
• Analyze prior orders to estimate what other dishes a client would like and generate real-time recommendations to enhance cross-selling.
• Contact clients the way they like, with customized real-time offers for pinpoint marketing at the correct time and place.
• Recognize connections between groups, purchases, and promotional offers.
• Dynamic pricing is achieved by comparing comparable rates in a particular geographic area.

Supply Chain, operation, and Security

Supply chain inefficiencies cost the consumer products and retail industries roughly 3.5 percent of annual sales. Big Data allows enterprises to understand their internal working in new ways by combining enterprise data with data from external sources. This helps reduce waste and supply chain expenses while also improving organizational efficiency.

Examples:

• Track food from farm to fork with barcodes and RFID. This provides smarter supply networks that help preserve food, prevent waste, and give the customers fresher food.
• Big Data analysis can help discover potential attacks, fraudulent transactions, and other security breaches by examining the relationships between many activities or events.

Operating system and application logs record daily user activity and give essential information about an organization's system architecture to enhance uptime.

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