This statistic shows the restaurant industry food and drink sales in the United States from 1970 to 2017. In 2016, food and drink sales of the U.S. restaurant industry amounted to approximately *** billion U.S. dollars.

More statistics and facts on fast food, the U.S. restaurant industry and the pizza (delivery) market.

U.S. restaurant industry - additional information

In 2016, food and drink sales in the United States restaurant industry amounted to *** billion U.S. dollars, up from ***** billion U.S. dollars in the previous year. Restaurants in the United States have created a booming industry that employed more than ** million people nationwide in 2015.

Unsurprisingly, the majority of food and drink sales in the U.S. restaurant industry take place in commercial restaurants. In 2016, full-service restaurant sales amounted to *** billion U.S. dollars and limited-service sales were *** U.S. dollars. The second largest contributor in 2015 was retail, vending, recreation and mobile vendors with sales of ***** billion U.S. dollars. The smallest proportion came from came from bars and taverns.

As of December 2016, things were still looking up for the U.S. restaurant industry: the monthly Restaurant Industry Tracking Survey, conducted by the National Restaurant Association, recorded a performance index score of ***** – any score over 100 indicates a period of expansion. The lowest performance index score between 2011 and 2017, ****, was recorded in August 2011. In November 2016, ** percent of U.S. consumers reported that cheaper restaurants would make them dine out more often.

The restaurant and takeaway industry in Europe was valued at over *** billion euros in 2025. Within this industry, there were approximately ** million employees and a total of roughly *********** businesses.

Dataset Overview This comprehensive dataset contains detailed information on 58,376 active restaurants across Bangladesh, scraped from Google Maps in 2024. The dataset comprises 221 columns spanning spatial, temporal, and operational metrics, making it the first large-scale, publicly available restaurant operations dataset from Bangladesh.

Key Features 1. Geographic coverage: Complete mapping of restaurants across Bangladesh's major urban areas 2. Temporal data: 24-hour traffic patterns for all seven days of the week 3. Operational metrics: Opening hours, customer ratings, review counts 4. Business information: Names, addresses, cuisine types, contact details 5. Facility data: Detailed amenities and service offerings 6. Online presence indicators: Websites, social media links 7. Customer feedback: Ratings (5-point scale) and review counts

Data Specifications 1. Format: JSON, CSV 2. Size: 58,376 records 3. Dimensions: 221 columns 4. Time period: Data collected in 2024 5. Source: Google Maps Platform 6. Data types: Categorical, numerical, and text data

MealMe offers in-depth restaurant menu data, including prices, from the top 100,000 restaurants across the USA and Canada. Our proprietary technology collects accurate, real-time menu and pricing information, enabling businesses to make data-driven decisions in competitive intelligence, pricing optimization, and market research. With comprehensive coverage that spans major restaurant platforms and chains, MealMe ensures your business has access to the most reliable data to excel in a rapidly evolving industry.

Platforms and Restaurants Covered: MealMe's database includes data from leading restaurant platforms such as UberEats, Postmates, ToastTakeout, SkipTheDishes, Square, Appfront, Olo, TouchBistro, and Clover, as well as direct menu data from major restaurant chains including Raising Cane’s, Panda Express, Popeyes, Burger King, and Subway. This extensive coverage ensures a detailed view of the market, helping businesses monitor trends, pricing, and availability across a broad spectrum of restaurant types and sizes.

Key Features: Comprehensive Menu Data: Access detailed menu information, including item descriptions, categories, sizes, and customizations. Real-Time Pricing: Monitor up-to-date menu prices for accurate competitive analysis. Restaurant-Specific Insights: Analyze individual restaurant chains such as Raising Cane’s and Panda Express, or platforms like UberEats, for market trends and pricing strategies. Cross-Platform Analysis: Compare menu items and pricing across platforms like ToastTakeout, Olo, and SkipTheDishes for a holistic industry view. Regional Data: Understand geographic variations in menu offerings and pricing across the USA and Canada.

Use Cases: Competitive Intelligence: Track menu offerings, pricing strategies, and seasonal trends across platforms like UberEats and Postmates or chains like Popeyes and Subway. Market Research: Identify gaps in the market by analyzing menus and pricing from top restaurants. Pricing Optimization: Use real-time pricing data to inform dynamic pricing strategies and promotions. Trend Monitoring: Stay ahead by tracking popular menu items, regional preferences, and emerging food trends. Platform Analysis: Assess how restaurants perform across delivery platforms such as SkipTheDishes, Olo, and Square. Industries Benefiting from Our Data Restaurant Chains: Optimize menu offerings and pricing strategies with detailed competitor data. Food Delivery Platforms: Benchmark menu pricing and availability across competitive platforms. Market Research Firms: Conduct detailed analyses to identify opportunities and market trends. AI & Analytics Companies: Power recommendation engines and predictive models with robust menu data. Consumer Apps: Enhance app experiences with accurate menu and pricing data. Data Delivery and Integration

MealMe offers flexible integration options to ensure seamless access to our comprehensive menu data. Whether you need bulk exports for in-depth research or real-time updates via API, our solutions are designed to scale with your business needs.

Why Choose MealMe? Extensive Coverage: Menu data from 100,000+ restaurants, including major chains like Burger King and Raising Cane’s. Real-Time Accuracy: Up-to-date pricing and menu details for actionable insights. Customizable Solutions: Tailored datasets to meet your specific business objectives. Proven Expertise: Trusted by top companies for delivering reliable, actionable data. MealMe empowers businesses with the data needed to thrive in a competitive restaurant and food delivery market. For more information or to request a demo, contact us today!

MealMe offers in-depth restaurant menu data, including prices, from the top 100,000 restaurants across the USA and Canada. Our proprietary technology collects accurate, real-time menu and pricing information, enabling businesses to make data-driven decisions in competitive intelligence, pricing optimization, and market research. With comprehensive coverage that spans major restaurant platforms and chains, MealMe ensures your business has access to the most reliable data to excel in a rapidly evolving industry.

Platforms and Restaurants Covered: MealMe's database includes data from leading restaurant platforms such as UberEats, Postmates, ToastTakeout, SkipTheDishes, Square, Appfront, Olo, TouchBistro, and Clover, as well as direct menu data from major restaurant chains including Raising Cane’s, Panda Express, Popeyes, Burger King, and Subway. This extensive coverage ensures a detailed view of the market, helping businesses monitor trends, pricing, and availability across a broad spectrum of restaurant types and sizes.

Key Features: Comprehensive Menu Data: Access detailed menu information, including item descriptions, categories, sizes, and customizations. Real-Time Pricing: Monitor up-to-date menu prices for accurate competitive analysis. Restaurant-Specific Insights: Analyze individual restaurant chains such as Raising Cane’s and Panda Express, or platforms like UberEats, for market trends and pricing strategies. Cross-Platform Analysis: Compare menu items and pricing across platforms like ToastTakeout, Olo, and SkipTheDishes for a holistic industry view. Regional Data: Understand geographic variations in menu offerings and pricing across the USA and Canada.

Use Cases: Competitive Intelligence: Track menu offerings, pricing strategies, and seasonal trends across platforms like UberEats and Postmates or chains like Popeyes and Subway. Market Research: Identify gaps in the market by analyzing menus and pricing from top restaurants. Pricing Optimization: Use real-time pricing data to inform dynamic pricing strategies and promotions. Trend Monitoring: Stay ahead by tracking popular menu items, regional preferences, and emerging food trends. Platform Analysis: Assess how restaurants perform across delivery platforms such as SkipTheDishes, Olo, and Square. Industries Benefiting from Our Data Restaurant Chains: Optimize menu offerings and pricing strategies with detailed competitor data. Food Delivery Platforms: Benchmark menu pricing and availability across competitive platforms. Market Research Firms: Conduct detailed analyses to identify opportunities and market trends. AI & Analytics Companies: Power recommendation engines and predictive models with robust menu data. Consumer Apps: Enhance app experiences with accurate menu and pricing data. Data Delivery and Integration

MealMe offers flexible integration options to ensure seamless access to our comprehensive menu data. Whether you need bulk exports for in-depth research or real-time updates via API, our solutions are designed to scale with your business needs.

Why Choose MealMe? Extensive Coverage: Menu data from 100,000+ restaurants, including major chains like Burger King and Raising Cane’s. Real-Time Accuracy: Up-to-date pricing and menu details for actionable insights. Customizable Solutions: Tailored datasets to meet your specific business objectives. Proven Expertise: Trusted by top companies for delivering reliable, actionable data. MealMe empowers businesses with the data needed to thrive in a competitive restaurant and food delivery market. For more information or to request a demo, contact us today!

This dataset contains Wake County Restaurant information and location data pulled from Wake County's GIS REST endpoint. For more information see Wake County's webpage.This dataset is updated daily.

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Food Service Market Size 2025-2029

The food service market size is forecast to increase by USD 53709.5 billion, at a CAGR of 47.5% between 2024 and 2029.

Major Market Trends & Insights

APAC dominated the market and accounted for a 44% growth during the forecast period.
By the Service - Conventional segment was valued at USD 1173.40 billion in 2023
By the Sector - Commercial segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 1.00 billion
Market Future Opportunities: USD 53709.50 billion 
CAGR : 47.5%
APAC: Largest market in 2023

Market Summary

The market continues to evolve, with significant shifts in consumer preferences and industry trends. According to recent studies, the sector is witnessing a notable increase in the demand for convenience and customization, leading to a surge in the adoption of off-premise dining options. In fact, off-premise sales are projected to account for over 50% of the total foodservice revenue by 2025, marking a substantial growth compared to the 35% share in 2020. Moreover, the snacking market within the foodservice industry is experiencing a remarkable expansion, with consumers opting for more frequent and diverse snacking occasions. This trend is particularly prominent among millennials and Gen Z, who are driving the demand for innovative, on-the-go snack solutions. Despite these positive developments, the foodservice sector faces challenges such as labor shortages and rising operational costs, which may impact profitability and growth. However, industry players are responding by adopting technology solutions, including automation and contactless ordering systems, to streamline operations and enhance the customer experience. Overall, the foodservice market's continuous evolution underscores the importance of staying informed about emerging trends and consumer preferences to capitalize on new opportunities.

What will be the Size of the Food Service Market during the forecast period?

Explore market size, adoption trends, and growth potential for food service market Request Free SampleThe market exhibits a consistent growth trajectory, with current industry performance registering at approximately 6% yearly expansion. Looking ahead, this trend is anticipated to continue, with future growth expectations hovering around 5%. Notably, the adoption of advanced technologies, such as online ordering platforms and kitchen workflow optimization solutions, is driving this growth. For instance, the integration of technology in food service operations has led to a 15% increase in order accuracy and a 10% reduction in wait times for customers. Furthermore, the implementation of inventory management software has resulted in a 12% decrease in food waste and a 7% improvement in overall operational efficiency. These figures underscore the significant impact technology is having on the food service industry, setting the stage for continued innovation and growth.

How is this Food Service Industry segmented?

The food service industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ServiceConventionalCentralizedReady-preparedAssembly-serveSectorCommercialNon-commercialCuisine TypeAmericanItalianAsianPrice RangeBudgetMid-rangePremiumTarget AudienceFamiliesProfessionalsStudentsGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKMiddle East and AfricaUAEAPACChinaIndiaJapanSouth KoreaSouth AmericaBrazilRest of World (ROW)

By Service Insights

The conventional segment is estimated to witness significant growth during the forecast period.

In the dynamic the market, energy efficiency solutions have gained significant traction, reducing operational costs by up to 15% for restaurants and cafeterias. Simultaneously, pest control procedures and equipment maintenance schedules ensure food safety and hygiene, maintaining a 20% reduction in pest infestations. Online ordering platforms and table management systems streamline operations, increasing revenue by 18% through improved customer experience and streamlined workflows. Revenue management strategies, such as dynamic pricing and demand forecasting, have become essential tools, contributing to a 21% increase in revenue for food service providers. Supply chain traceability and nutrition labeling requirements foster transparency and trust, with a reported 25% of consumers preferring establishments that provide detailed information about their offerings. Restaurant reservation systems, HACCP implementation, and ingredient sourcing strategies are crucial components of the food service industry, enabling efficient workflows and ensuring regulatory compliance. Food service technology, including kitchen w

Introduction

This dataset is a comprehensive collection of information about the top 240 restaurants recommended in Los Angeles, as listed on Yelp. It aims to provide valuable insights into various aspects of these restaurants, such as customer reviews, star ratings, styles of cuisine, and more. The data was collected using a Python script that leverages web scraping techniques to extract relevant information from Yelp's website. 240 restaurants are identified and their URLs are retrieved.

Only the latest 10 comments/reviews are collected for each restaurant. The objective is to unveil the recent performance of the restaurants rather than that in their lifetime.

Methodology

The data was scraped from Yelp's search results for top recommended restaurants in Los Angeles. The Python script uses the BeautifulSoup library to parse the HTML content and extract the required data.

Summary of Results

The dataset contains a total of 240 entries, each representing a top-recommended restaurant in Los Angeles according to Yelp. Each entry is enriched with various details like star ratings, number of reviews, styles of cuisine, and customer comments, among others.

Column Descriptions

Rank: The ranking number of the restaurant in the list of top-recommended restaurants by Yelp CommentDate: The date when the comment was posted. Date: The date when the data was scraped. RestaurantName: The name of the restaurant. Comment: Customer comments about the restaurant. Address: The physical address of the restaurant. StarRating: The average star rating of the restaurant. NumberOfReviews: The total number of reviews the restaurant has received. Style: The style or type of cuisine the restaurant offers. Price: The price range of the restaurant, usually represented in terms of dollar signs (e.g., $$).

Suggested Usages of the Dataset

Market Research: Understand the competitive landscape of restaurants in Los Angeles. Customer Sentiment Analysis: Analyze customer comments to gauge public sentiment about different restaurants. Trend Analysis: Identify popular styles of cuisine or other trends in the restaurant industry. Price Benchmarking: Compare the price ranges of different restaurants to identify potential market gaps. Location Strategy: Use the address data to strategize the best locations for opening a new restaurant.

By leveraging this dataset, stakeholders can make more informed decisions in various domains, from business strategy to customer engagement.

The quick service restaurant sector (QSR) in the United States has seen a near year-over-year growth since 2004, with its peak consumer spending exceeding ***** billion U.S. dollars in 2024. Consumer spending in this sector saw a notable decline in 2020, however, as a result of the coronavirus (COVID-19) pandemic. Fast food industry in the U.S. - additional information Quick service restaurants (QSRs) are fast food restaurants, set apart from full service or table restaurants by their limited menus, minimal table service and, as their name implies, fast service. According to the American Customer Satisfaction Index (ACSI) carried out in 2024, the quick service restaurant chain in the United States with the highest ACSI score was Chick-fil-A. With a score of ** out of 100. McDonald’s scored the lowest with a score of **. Is McDonald's the largest QSR chain? Despite McDonald's low score on the American Customer Satisfaction Index, ********** was the largest fast food company worldwide in terms of brand value in 2022. That year, the company generated a global brand value of almost ***** billion U.S. dollars. McDonald's closest competitor in terms of brand value was Starbucks, with **** billion U.S. dollars. KFC followed with **** billion U.S. dollars.

YELP DATASET TERMS OF USE Last Updated: February 16, 2021 This document (“Data Agreement”) governs the terms under which you may access and use the data that Yelp makes available for download through this website (or made available by other means) solely for academic or non-commercial purposes (the “Data”). Yelp Terms of Service: By accessing or using the Data, you agree to be bound by the Data Agreement and represent that the contact information you provide to Yelp is correct. If you access or use the Data on behalf of a university, school, or other entity, you represent that you have authority to bind such entity and its affiliates to the Data Agreement and that it is fully binding upon them. In such a case, the term “you” and “your” will refer to such an entity and its affiliates. If you do not have authority, or if you do not agree with the terms of the Data Agreement, you may not access or use the Data. You should read and keep a copy of each component of the Data Agreement for your records. In the event of a conflict among them, the terms of this document will control. 1. Purpose The Data is made available by Yelp Inc. (“Yelp”) to enable you to access valuable local information to develop an academic project as part of an ongoing course of study or for non-commercial purposes. With this in mind, Yelp reserves the right to continually review and evaluate all uses of the Data provided under the Data Agreement. Under certain circumstances, Yelp may authorize limited commercial use under certain circumstances, for example, access and use by journalists to explore our data to generate ideas prior to formal data access requests from Yelp’s PR department. 2. Changes Yelp reserves the right to modify or revise the Data Agreement at any time. If the change is deemed to be material and it is foreseeable that such change could be adverse to your interests, Yelp will provide you notice of the change to this Data Agreement by sending you an email to the email you provided to Yelp. Your continued use of the Data after the notice of material change will constitute your acceptance of and agreement to such changes. IF YOU DO NOT WISH TO BE BOUND TO ANY NEW TERMS, YOU MUST TERMINATE THE DATA AGREEMENT BY IMMEDIATELY CEASING USE OF THE DATA AND DELETING IT FROM ANY SYSTEMS OR MEDIA. 3. License Subject to the terms set forth in the Data Agreement (specifically the restrictions set forth in Section 4 below), Yelp grants you a royalty-free, non-exclusive, revocable, non-sublicensable, non-transferable, fully paid-up right and license during the Term to use, access, and create derivative works of the Data in electronic form for solely for non-commercial use.. Non-commercial use means use of the Data by registered nonprofits, government, educational institutions, and think tanks which (a) is not undertaken for profit, or (b) is not intended to produce works, services, or data for commercial use. You may not use the Data for any other purpose without Yelp’s prior written consent. You acknowledge and agree that Yelp may request information about, review, audit, and/or monitor your use of the Data at any time in order to confirm compliance with the Data Agreement. Nothing herein shall be construed as a license to use Yelp’s registered trademarks or service marks, or any other Yelp branding. Prior to any public presentation or publication of the academic results or conclusions that involve the Data and/or the Yelp brand name, you must submit your findings to Yelp for review and approval, and Yelp will approve of the public release within five (5) business days of its submission to Yelp. 4. Restrictions You agree that you will not, and will not encourage, assist, or enable others to: A. display, perform, or distribute any of the Data, or use the Data to update or create your own business listing information for commercial purposes (i.e. you may not publicly display any of the Data to any third party, especially reviews and other user generated content, as this is a private data set challenge and not a license to compete with or disparage with Yelp); B. use the Data in connection with any commercial purpose; C. use the Data in any manner or for any purpose that may violate any law or regulation, or any right of any person including, but not limited to, intellectual property rights, rights of privacy and/or rights of personality, or which otherwise may be harmful (in Yelp's sole discretion) to Yelp, its providers, its suppliers, end users of this website, or your end users; D. use the Data on behalf of any third party without Yelp’s consent; E. create, redistribute or disclose any summary of, or metrics related to, the Data (e.g., the number of reviewed business included in the Data and other statistical analysis) to any third party or on any website or other electronic media not expressly covered by this Agreement or without Yelp’s ...

This data compiles information on general restaurants operating in Seo-gu, Daejeon Metropolitan City. Key information, including industry name, business name, street address, road address, administrative/legal dong code and name, and phone number, is provided in a standardized structure for each restaurant, enabling a clear understanding of the distribution and characteristics of the local restaurant industry. This data can be utilized by administrative agencies for restaurant hygiene management, commercial district analysis, restaurant industry statistics, and regional economic trends. Address-based location information also makes it suitable for integration with external platforms such as map services, private portals, and restaurant search services. Furthermore, it serves as a foundation for various analytical tasks, such as comparative analysis at the administrative/legal dong level and understanding the regional industry composition.

[226+ Pages Report] The global Hospitality market size is expected to grow from USD 3953 billion in 2021 to USD 6716.3 billion by 2028, at a CAGR of 10.24% from 2022-2028

A poor food safety culture has been described as an emerging risk factor for foodborne illness outbreaks, yet there has been little research on this topic in the retail food industry. The purpose of this study was to identify and validate conceptual domains around food safety culture and develop an assessment tool that can be used to assess food workers’ perceptions of their restaurant’s food safety culture. The study, conducted from March 2018 through March 2019, surveyed restaurant food workers for their level of agreement with 28 statements. We received 579 responses from 331 restaurants spread across eight different health department jurisdictions. Factor analysis and structural equation modeling supported a model composed of four primary constructs. The highest rated construct was Resource Availability (

=4.69, sd=0.57), which assessed the availability of resources to maintain good hand hygiene. The second highest rated construct was Employee Commitment (=4.49, sd=0.62), which assessed workers’ perceptions of their coworkers’ commitment to food safety. The last two constructs were related to management. Leadership (=4.28, sd=0.69) assessed the existence of food safety policies, training, and information sharing. Management Commitment (=3.94, sd=1.05) assessed whether food safety was a priority in practice. Finally, the model revealed one higher-order construct, Worker Beliefs about Food Safety Culture (=4.35, sd=0.53). The findings from this study can support efforts by the restaurant industry, food safety researchers, and health departments to examine the influence and effects of food safety culture within restaurants.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Small, clean dataset for learning purposes.

Data sourced from QSR Magazine, a business-to-business magazine in the quick service restaurant industry. This dataset includes the top 50 fast food chains in the U.S. in 2020. Contains information on the total sales, sales per unit, franchise units, company owned units, and unit change from 2018.

Columns include: - Company Name - Category (pizza, burger, etc) - Sales in Millions (2019) - Sales Per Unit in Thousands (2019) - # of Franchised Units (2019) - # of Company Owned Units (2019) - # of Total Units (2019) - Unit # Change from 2018

Download Free Sample
According to frozen food industry statistics, North America was identified as the largest consumer of frozen food. The frozen food market research report considers consumption patterns of several regions including Europe, North America, APAC, South America, and MEA to present a clear picture of the demand of the product globally during the forecast period 2020-2024.

The frozen food market report also provides several other key information including:

CAGR of the market during the forecast period 2020-2024
Detailed information on factors that will drive frozen food market growth during the next five years
Precise estimation of the frozen food market size and its contribution to the parent market
Accurate predictions on upcoming trends and changes in consumer behavior
The growth of the frozen food market industry across Europe, North America, APAC, South America, and MEA
A thorough analysis of the market’s competitive landscape and detailed information on vendors
Comprehensive details of factors that will challenge the growth of frozen food market vendors

Provide national restaurant industry (F501060) business registration information.

This dataset contains 21,321 food order records from various restaurants, capturing crucial details about customer preferences, order trends, pricing, and delivery performance. It includes 6 unique imaginary restaurants, such as Swaad, Aura Pizzas, Dilli Burger Adda, Tandoori Junction, The Chicken Junction, and Masala Junction. The dataset provides a comprehensive view of food delivery operations, making it highly valuable for data analysis, predictive modeling, and machine learning applications.

Key attributes in this dataset include restaurant details (restaurant name, subzone, city), order information (order ID, timestamps, order status, delivery time, distance, number of items), pricing breakdown (bill subtotal, packaging charges, total cost, discounts), and customer feedback (ratings, reviews, order cancellations). It also tracks key delivery insights such as rider wait time, preparation duration, and distance traveled, which can be useful for logistics optimization and demand forecasting.

This dataset can be leveraged for predicting delivery times, analyzing customer behavior, identifying top-performing restaurants, and optimizing pricing strategies. It is particularly useful for food delivery platforms, restaurant managers, and data scientists looking to improve delivery efficiency and customer satisfaction. With rich historical data, this dataset can also be used for building recommendation systems, identifying peak ordering times, and enhancing user experience in food delivery applications.

Toast, Inc. operates a cloud-based and digital technology platform for the restaurant industry in the United States and Ireland. The company offers Toast Point of Sale (POS), a hardware product; Toast Order & Pay, which allows guests to order and pay from their mobile devices; Toast Flex that is used for on-counter order and pay, as well as used as a server station, guest kiosk, kitchen display system, or order fulfillment station; Toast Go, a handheld POS device that enhances the table turn times through tableside ordering and payment acceptance; and Toast Tap, a card reader. It also provides kitchen display system software that connects the front of the house with the kitchen staff; multi-location management software, which allows customers to manage and standardize their operations and configure menus; xtraCHEF that provides back-office tools; and Toast Flex for Kitchen, a larger format mountable piece of hardware that can be used as a kitchen screen. In addition, the company offers Toast Online Ordering & Toast TakeOut app, a software-based platform that provides restaurants to take off-premises orders directly through their branded website; First-Party Delivery services for restaurants to manage a fleet of drivers, and customize delivery hours, zones, fees, and minimum ticket sizes; Toast Delivery Services, which enables restaurants to utilize a partner network of delivery drivers; and Toast Delivery Partners services. Further, it provides loyalty programs and gift cards; payroll and team management products; business owner policy insurance and restaurant-specific add-ons; payment processing solutions; loans advanced to restaurants; purchase financing; reporting and analytics solutions; Toast Partner Connect that allows customers to discover, select, and connect their restaurant to its partners; and bi-directional APIs. The company was incorporated in 2011 and is headquartered in Boston, Massachusetts.

For information on economic census geographies, including changes for 2012, see the economic census Help Center..Includes only establishments of firms with payroll. SeeTable Notes for more information. Data based on the 2012 Economic Census. For information on confidentiality protection, sampling error, nonsampling error, and definitions, see Methodology..Table NameAccommodation and Food Services: Subject Series - Misc Subjects: Primary Type of Food Service for the U.S. and States: 2012ReleaseScheduleThe data in this file are scheduled for release in the first quarter of 2016.Key TableInformationSee Methodology for information on data limitations.UniverseThe universe of this file is selected establishments of firms with payroll in business at any time during 2012 and classified in Accommodation and Food Services (Sector 72).GeographyCoverageThe data are shown at the United States and state levels.IndustryCoverageThe data are shown for 2012 NAICS code 722513, Limited-service restaurants.Data ItemsandOtherIdentifyingRecordsThis file contains data on:Establishments by primary type of food serviceSales by primary type of food serviceResponse coverageEach record includes a FDSVCTYPE code which represents a primary type of food service.FTP DownloadDownload the entire table athttps://www2.census.gov/econ2012/EC/sector72/EC1272SXSB01.zip. ContactInformation. U.S. Census Bureau, Economy Wide Statistics Division. Data User Outreach and Education Staff. Washington, DC 20233-6900. Tel: (800) 242-2184. Tel: (301) 763-5154. ewd.outreach@census.gov. . .Symbols:D - Withheld to avoid disclosing data for individual companies; data are included in higher level totalsN - Not available or not comparableFor a complete list of all economic programs symbols, see the Symbols Glossary.Source: U.S. Census Bureau, 2012 Economic Census.Note: The data in this file are based on the 2012 Economic Census. To maintain confidentiality, the U.S. Census Bureau suppresses data to protect the identity of any business or individual. The census results in this file contain sampling and nonsampling error. Data users who create their own estimates using data from this file should cite the U.S. Census Bureau as the source of the original data only. For the full technical documentation, see Methodology link in above headnote.