AWS for Industries

How restaurants are augmenting data to drive insights

The restaurant industry (restaurants, catering, and food service distribution), is experiencing massive change, including the need to adopt dynamic business models such as delivery, pickup, and contactless service. At the same time, competition, labor costs, and consumer expectations are greater than ever. This environment creates an opportunity for organizations to augment existing data with third-party data to improve insights, drive decision-making, and leap into the future through digital transformation.

I am fortunate to work with restaurant industry customers around the world and in all segments of the industry. These customers tell me that they are awash with data; though not always extracting the most value from it. They have proprietary data from their key information systems that support specific business functions such as:

  • Point of sale (POS)
  • Customer loyalty, rewards, CRM
  • Supply chain systems
  • Inventory
  • Human resources and labor
  • Accounting and finance

These customers are looking to augment their existing datasets with third-party data to make more informed business decisions utilizing advanced analytics and machine learning; injecting the results back into business applications to make quicker decisions and shift their resources away from non-value-added tasks. I have observed common patterns around improving key industry outcomes including; enhancing the customer experience, improving operational efficiencies, site selection and analysis, forecasting, and competitive benchmarking. Normally, customers are reluctant to share use cases as they believe it drives competitive advantages for them, but recently teams from McDonald’s, Foursquare, Lovealytics, and Wavicle all shared their experiences via two webinars.

The National Restaurant Association (NRA) held a webinar with McDonald’s and Wavicle, which is available on demand. The session covered the “Voice of Customer” and a text analytics solution built using Amazon Comprehend and other AWS solutions by Wavicle. The solution mines text from the top social media platforms to classify, categorize, and provide sentiment analysis of the free-form text to surface actionable operational insights. Malia Katts, Senior Director of Global Consumer Insights for McDonald’s, referenced how the solution provides insights for her at both the brand and individual restaurant level from a combination of guest surveys and social media.

I was then privileged to join Foursquare and Lovelytics for a panel discussion of the value of location data for site selection alongside a demo of an industry solution, which is available on demand. At the heart of the conversation and demo is the realization that restaurant companies are accelerating the creation of “Digital First” stores. These stores capitalize on the newly emerged premium of drive thrus, outdoor patios, and proximity to essential services. During the conversation, I share the innovation of the inclusion of supply chain experts to store location development teams. The driver of this innovation is network design. Network design in commonly defined as a process that determines the best mix of suppliers, locations, logistics, and facilities for optimizing product production and the best methods for delivering goods to customers. With the continued advancement of Ghost Kitchens and Virtual Brands, the configuration of the restaurant location network directly impacts a brands ability to market itself and operate. Panelists then shared how access to quality third-party data can boost confidence, enable growth, and optimize across markets, all made possible through making data-driven decisions with extreme precision.

So how can restaurant brands locate a consolidated marketplace to find, subscribe to, and analyze datasets to improve business insights in the cloud with security and ease-of-use? The AWS Data Exchange is how.

With the AWS Data Exchange for restaurants, brands:

  • Dramatically reduce the time it takes to securely source data from months down to minutes
  • Accelerate access to data from qualified data providers to make strategic business decisions
  • Complement machine learning programs with data to train and influence models
  • Free expensive resources, such as developers and data scientists, from searching for high-quality data sources
  • Find and use data on the cloud – where data is already being generated and stored, as opposed to having to obtain, ingest and normalize data. Providing focus for staff to produce differentiated products and value-added activities rather than ingesting data, maintaining infrastructure, and managing revisions.

While there are over 2,000 data products available on the AWS Data Exchange, many are restaurant industry specific. A curated list of 26 datasets to accelerate your learning is provided in the following table. With the eight types of data presented, you could look to improve forecasting accuracy for menu items, promotions, labor scheduling, and purchasing. Enhance your store development process similar to the Foursquare webinar, best determining where to open stores, relocate stores, and better understand trade areas with competition down to the local level. Gain workforce intelligence to reduce turnover and increase team member retention. Take the guess work out of marketing and R&D innovation with improved segmentation, demographics, population densities, and footfall and traffic patterns. Benchmark and understand your “share of stomach” to stay ahead of your competition and answer questions posed by your finance and executive suite leadership teams. For multi-brand operators, you can tailor your brand portfolio across markets.

Type of Data Provider (link to all listings) Free Sample/Trial
Consumer Insights Epsilon Dining – Consumer Data Insights
ALC Price Driven Consumers
Acxiom Japan Consumer Segmentation
Experian US CAPE Census Ratios and Percentages
Location (Foot Traffic, Point of Interest) Foursquare QSR Visits Data Sample
Cuebiq QSR Visits Data Sample
TruFactor Daily Visits to Subway Restaurants Sample
PlaceIQ QSR Visits Data Sample
NinthDecimal QSR Visits Sample Data
Mobile App Activity AppTopia Mobile App Intelligence* (paid)
TruFactor Daily Web Mobile Activity 
Transaction Facteus US Consumer Debit Card Transactions
Weather Planalytics Weather Driven Demand for Grocery Stores
Weather Trends Daily NYC Weather
ClimaCell Historical Weather Data Sample – US
Weather Source Historical Weather Data Sample
Sentiment Prosper Insights US Consumer Food: Home and Away Sentiment* (paid)
LikeFolio Dine-In Restaurants Consumer Purchase Intent and Sentiment
Fast Food Restaurants Consumer Purchase Intent and Sentiment
COVID Response/Recovery Rearc Rearc’s free NYTimes Reopenings/Closures dataset
Tableau Coronavirus Data Hub
Enigma Enigma’s free government response tracker dataset

Use the AWS Data Exchange to reduce risk and speed up experimentation in your organization in four ways:

  • Rapidly add-on new datasets, test theories, and make decisions in real time
  • Move into new markets with confidence and quantify market potential based on real data
  • Break data silos, provide all your resources access to valuable data
  • Reduce hefty consulting fees, test with free datasets, and turn datasets on and off as needed

Begin using third-party data and the AWS Data Exchange to have a clear, deep, and profound understanding of your customers, operations, and supply chain.Learn more about how AWS is helping transform the travel and hospitality industry at

Steven M. Elinson

Steven M. Elinson

Steven M. Elinson is the head of worldwide restaurants and food service, the global industry practice for Amazon Web Services (AWS), with a charter to support customers as they accelerate cloud adoption. As a trusted adviser, Steven uses his broad knowledge and 32 years of experience to drive guest experiences and to increase operational efficiency.