The Temporary Program, is no longer accepting applications. *Visit Permanent Dining Out website for information: https://www.diningoutnyc.info/ The New York City Open Restaurant is an effort to implement a citywide multi-phase program to expand outdoor seating options for food establishments to promote open space, enhance social distancing, and help them rebound in these difficult economic times. For real time updates on restaurants registered in the program, please visit NYC Open Restaurants dashboard: https://bit.ly/2Z00kn8 ** Please note this Open Restaurant Applications dataset may contain multiple entries (e.g. restaurants submitting 2 or more applications). The Open Restaurants dashboard website containing real time update, noted above, will have fewer total records due to the removal of multiple applications and only list the newest entry.

About this Dataset

Contact information for over 20,000 restaurants across the US. All restaurants from the NAICS code 72251: Restaurants and Other Eating Places. This includes all set down, fast casual, fast food, and ethnic restaurants. List includes name, address, phone number, website, contact email address, and a brief description. Data was collected from a combination of web scrapping and manual data entry. Similar lists cost over $1500 from lead generation and business data companies.

Category

Lead Generation

Keywords

restaurants,contact,mailing

Row Count

21210

Price

$499.00

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!

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance. Data were collected to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data can be used to determine when restaurants in states and territories were subject to closing and reopening requirements through executive orders, administrative orders, resolutions, and proclamations for COVID-19. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level. These data are derived from publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly close or reopen restaurants found by the CDC, COVID-19 Community Intervention & Critical Populations Task Force, Monitoring & Evaluation Team, Mitigation Policy Analysis Unit, and the CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

Comprehensive dataset containing 1,362 verified Dim sum restaurant businesses in United States with complete contact information, ratings, reviews, and location data.

About this dataset

Do you love the convenience of being able to drive through and pick up your food without having to wait? Well, you're not alone. According to a new study by Datafiniti, there are over 10,000 fast food restaurants across the United States.

That's a lot of restaurants! But what does that mean for the average person living in America? Well, it means that there are more than enough options for those who want to grab a quick bite on the go. And it also means that there are plenty of opportunities for those who want to open their own fast food restaurant.

So, if you're thinking about starting your own fast food business, or if you're just curious about where the most (and least) fast food options are in America, then this dataset is for you!

How to use the dataset

To find out where the most fast food restaurants are in the United States, you can use this dataset. The dataset includes the restaurant's name, address, city, state, and website. You can use this information to rank cities with the most and least fast food options

Research Ideas

1. Fast food delivery service that delivers from multiple restaurants

2. An app that allows users to find the healthiest fast food options near them

3. A website that ranks cities by their number of fast food restaurants per capita

Acknowledgements

The original source of the data is Datafiniti's Business Database. The dataset includes the restaurant's address, city, latitude and longitude coordinates, name, and more

Columns

File: Datafiniti_Fast_Food_Restaurants.csv | Column name | Description | |:----------------|:---------------------------------------------------------------------| | dateAdded | The date the restaurant was added to the database. (Date) | | dateAdded | The date the restaurant was added to the database. (Date) | | dateUpdated | The date the restaurant was last updated in the database. (Date) | | dateUpdated | The date the restaurant was last updated in the database. (Date) | | address | The street address of the restaurant. (String) | | address | The street address of the restaurant. (String) | | categories | The category or categories the restaurant is classified as. (String) | | categories | The category or categories the restaurant is classified as. (String) | | city | The city the restaurant is located in. (String) | | city | The city the restaurant is located in. (String) | | country | The country the restaurant is located in. (String) | | country | The country the restaurant is located in. (String) | | keys | The unique identifier for the restaurant. (String) | | keys | The unique identifier for the restaurant. (String) | | latitude | The latitude coordinate of the restaurant. (Float) | | latitude | The latitude coordinate of the restaurant. (Float) | | longitude | The longitude coordinate of the restaurant. (Float) | | longitude | The longitude coordinate of the restaurant. (Float) | | name | The name of the restaurant. (String) | | name | The name of the restaurant. (String) | | postalCode | The postal code of the restaurant. (String) | | postalCode | The postal code of the restaurant. (String) | | province | The province or state the restaurant is located in. (String) | | province | The province or state the restaurant is located in. (String) | | sourceURLs | The source URL of the restaurant. (String) | | sourceURLs | The source URL of the restaurant. (String) | | websites | The website of the restaurant. (String) | | websites | The website of the restaurant. (String) |

File: FastFoodRestaurants.csv | Column name | Description | |:---------------|:-------------------------------------------------------------| | address | The street address of the restaurant. (String) | | address | The street address of the restaurant. (String) | | city | The city the restaurant is located in. (String) | | city | The city the restaurant is located in. (String) | | country | The country the restaurant i...

Comprehensive dataset containing 944 verified German restaurant businesses in United States with complete contact information, ratings, reviews, and location data.

Eateries in in New York City Department of Parks & Recreation properties including snack bars, food carts, mobile food trucks, and restaurants.

This dataset provides restaurant inspections, violations, grades and adjudication information

The Delta Food Outlets Study was an observational study designed to assess the nutritional environments of 5 towns located in the Lower Mississippi Delta region of Mississippi. It was an ancillary study to the Delta Healthy Sprouts Project and therefore included towns in which Delta Healthy Sprouts participants resided and that contained at least one convenience (corner) store, grocery store, or gas station. Data were collected via electronic surveys between March 2016 and September 2018 using the Nutrition Environment Measures Survey (NEMS) tools. Survey scores for the NEMS Corner Store, NEMS Grocery Store, and NEMS Restaurant were computed using modified scoring algorithms provided for these tools via SAS software programming. Because the towns were not randomly selected and the sample sizes are relatively small, the data may not be generalizable to all rural towns in the Lower Mississippi Delta region of Mississippi. Dataset one (NEMS-C) contains data collected with the NEMS Corner (convenience) Store tool. Dataset two (NEMS-G) contains data collected with the NEMS Grocery Store tool. Dataset three (NEMS-R) contains data collected with the NEMS Restaurant tool. Resources in this dataset:Resource Title: Delta Food Outlets Data Dictionary. File Name: DFO_DataDictionary_Public.csvResource Description: This file contains the data dictionary for all 3 datasets that are part of the Delta Food Outlets Study.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset One NEMS-C. File Name: NEMS-C Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for convenience stores.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Two NEMS-G. File Name: NEMS-G Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for grocery stores.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel Resource Title: Dataset Three NEMS-R. File Name: NEMS-R Data.csvResource Description: This file contains data collected with the Nutrition Environment Measures Survey (NEMS) tool for restaurants.Resource Software Recommended: Microsoft Excel,url: https://products.office.com/en-us/excel

Graph and download economic data for Retail Sales: Restaurants and Other Eating Places (MRTSSM7225USN) from Jan 1992 to Aug 2025 about restaurant, retail trade, sales, retail, and USA.

Bitext - Restaurants Tagged Training Dataset for LLM-based Virtual Assistants

  Overview

This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [restaurants] sector can be easily achieved using our two-step approach to LLM Fine-Tuning. An… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-restaurants-llm-chatbot-training-dataset.

Comprehensive dataset containing 27,251 verified Taco restaurant businesses in United States with complete contact information, ratings, reviews, and location data.

Snapshot img

US Fast Casual Restaurants Market Size 2025-2029

The US fast casual restaurants market size is valued to increase USD 84.5 billion, at a CAGR of 13.7% from 2024 to 2029. Demand for innovation and customization in food menus will drive the US fast casual restaurants market.

Major Market Trends & Insights

By Channel - Dine-in segment was valued at USD 48.90 billion in 2022
By Application - Franchised segment accounted for the largest market revenue share in 2022

Market Size & Forecast

Market Opportunities: USD 148.40 billion
Market Future Opportunities: USD 84.50 billion
CAGR from 2024 to 2029 : 13.7%

Market Summary

The Fast Casual Restaurants Market in the US continues to expand, driven by consumer preferences for fresh, customizable meal options. According to recent data, the market is projected to reach a value of USD115.5 billion by 2026, growing at a steady pace. This growth is fueled by the demand for innovation and personalization in food menus, with fast casual restaurants offering a middle ground between the limited offerings of quick-service establishments and the higher prices and longer wait times of full-service restaurants. In response to this trend, fast casual chains have been increasingly focusing on digitalization, streamlining ordering processes and enhancing the customer experience through mobile apps and contactless payment options.
However, this market segment faces intense competition from quick-service restaurants, which have also been adopting similar strategies to cater to evolving consumer preferences. As a result, fast casual restaurants must continue to differentiate themselves through unique menu offerings, efficient operations, and exceptional customer service to maintain their market share. Despite these challenges, the future of the fast casual market in the US remains promising, with opportunities for growth in both urban and suburban areas and the potential to expand beyond traditional brick-and-mortar locations through delivery and catering services.

What will be the Size of the US Fast Casual Restaurants Market during the forecast period?

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Fast Casual Restaurants in US Market Segmented and what are the key trends of market segmentation?

The fast casual restaurants in US 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.

Channel

  Dine-in
  Takeaway


Application

  Franchised
  Standalone


Food Type

  Burger/Sandwich
  Pizza/Pasta
  Asian
  Latin American
  Chicken
  Others


Target Audience

  Millennials
  Working Professionals
  Families


Distribution Channel Specificity

  Specialty Chains
  Online Platforms
  Retail Foodservice


Geography

  North America

    US

By Channel Insights

The dine-in segment is estimated to witness significant growth during the forecast period.

Fast casual restaurants in the US, a hybrid of fast food and casual dining, have been continuously evolving since their inception, offering better quality meals with less frozen or processed ingredients. Operational efficiency improvements, such as revenue management techniques and table management systems, have been key to their success. Cost control strategies, including digital menu boards, inventory management software, and marketing automation tools, help maintain profitability. Third-party delivery services and brand positioning strategies cater to the growing demand for convenience. Sustainability initiatives, like food waste reduction and customer loyalty programs, enhance the dining experience and foster long-term relationships.

Kitchen display systems, food safety management, energy efficiency measures, and wait time optimization ensure consistent quality and customer satisfaction. Sales forecasting models, employee retention strategies, labor scheduling software, and restaurant management systems facilitate efficient operations. Data analytics dashboards, social media marketing, online reputation management, and order fulfillment process enhance customer engagement. Peak hour management, online ordering platforms, guest feedback systems, and customer experience metrics provide valuable insights for continuous improvement. Supply chain optimization and employee training programs ensure consistency and quality in menu offerings. According to a recent report, fast casual restaurants account for over 5% of total US foodservice sales.

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The Dine-in segment was valued at USD 48.90 billion in 2019 and showed a gradual increase during the forecast period.

Request Free Sample

Market Dynamics

Our researchers analyzed the data with 2024 as the base year, along with the key drivers, trends, and

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 provides restaurant inspections, violations, grades and adjudication information

Comprehensive dataset containing 6,885 verified Hot dog restaurant businesses in United States with complete contact information, ratings, reviews, and location data.

Graph and download economic data for Revenue for Limited-Service Restaurants, All Establishments, Employer Firms (LRRAEEF2722513) from 2013 to 2022 about restaurant, employer firms, revenue, establishments, and USA.

Comprehensive dataset containing 217 verified Nicaraguan restaurant businesses in United States with complete contact information, ratings, reviews, and location data.

Comprehensive dataset containing 1,315 verified Hot pot restaurant businesses in United States with complete contact information, ratings, reviews, and location data.