What is Restaurant Traffic Data? Examples, Datasets and Providers
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
What is Restaurant Traffic Data?
Restaurant traffic data is information gathered and analyzed regarding the number of patrons visiting a restaurant within a specific period. This data helps restaurant owners and managers make informed decisions about staffing, marketing strategies, and overall business operations to enhance customer experience and increase profitability.
What are Examples of Restaurant Traffic Data?
Restaurant traffic data includes attributes such as latitude, longitude, timestamp, and device ID. Additional attributes might include visit duration, frequency, and demographic information such as age and gender, depending on the data provider. Examples of restaurant traffic data include the number of customers visiting a restaurant during specific time periods, the average length of time customers spend in a restaurant, and the peak hours of customer activity.
- Customer Count: Number of customers visiting during specific time periods.
- Average Dwell Time: How long customers spend in the restaurant.
- Peak Hours: Times of highest customer activity.
- Repeat Visits: Frequency of customer return visits.
- Demographic Data: Age, gender, and other demographic information of customers.
For example, a restaurant might notice through restaurant traffic data that weekends see a significant increase in customers between 6 PM and 8 PM. This insight allows managers to schedule more staff during these peak hours to maintain service quality.
Best Restaurant Traffic Databases & Datasets
The best restaurant traffic datasets provide accurate visitor counts, time-of-day patterns, and demographic insights. This curated list features the top restaurant traffic datasets, selected for precision, quality, and trusted providers.
Global Bar & Restaurant Data | Point of Interest (POI) & Foot Traffic Data | 31M+ Locations
Store Location Data | 230M+ Global POIs & Retail Locations | 5000+ Categories with Restaurant, Retail & Business Coverage
PREDIK Data-Driven I US Aggregated Foot Traffic Data & Visit Data I Analyze the US South Eastern Area
Factori Geospatial Data | Global | Location Intelligence | POI , Foot Traffic, Store Visit
Autoscraping | USA Restaurant Data | 500K+ Listings with Addresses, Ratings & Delivery Fees
Brazil Point of Interest (POI) & Foot Traffic Data | 17M+ Businesses
Mobility data | Traffic Flow Bundle | Origins/ destinations of vehicles passing a road segment | Gas stations | Out-of-Home Ads | Retail
Automaton AI Restaurant Image (multi-camera CCTV data)
Sound Level data to gauge foot traffic, popularity, ambiance and noise levels of venues
PREDIK Data-Driven I Point of Interest (POI) Data + Foot Traffic Data I +60 Data Variables for the LATAM Market
Can't find the data you're looking for?
Let data providers come to you by posting your request
Post your request
Top Restaurant Traffic Data Providers & Companies
-
Consumer Edge
CoverageUSAUK+248Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Transaction data, scanner data, web data, and email receipt data spans dozens of industries, hundreds of companies, and global geographies to empower strategic decision-making.100M+Credit & Debit Cards30K+Public & Private Brands700+Parent Companies -
DRAKO
CoverageUSAUK+248Drako Data is your trusted partner for value-added geolocation data solutions. We enhance and simplify data extraction, enabling clients to gain insights quickly and efficiently. Our aim is to empower your data-driven decision-making, driving your business forward.CCPACompliantSDKSourced Data5 YearsLookback -
Automaton AI
CoverageUSAUK+238We are a full-stack AI company with a mission to democratize Data. Automaton AI is an AI industry expert who is Transforming how businesses see the world with end-to-end AI services ranging from Data sourcing to Application Development and Model Deployment. -
dataplor
CoverageUSAUK+247VMy firm decided to make the switch over to dataplor from a manual data collection effort once we saw measurable lift in accuracy, coverage, and cost-savings. Their resolution was far beyond what we could achieve on our own, and we no longer had to juggle the labor-intensive process of duplicates, new places, and pulling in updates. We now have a reliable stream of data in difficult markets that is high-fidelity and always current. And because they are global, adding new datasets is a breeze.
-
Factori
CoverageUSAUK+247BMobility data was used to track where people flock during quarantine, and to understand how people moved out of the urban centers and to the provinces. Might also be used for retail clients to understand what adjustments are needed to adapt better to the situation.
Popular Use Cases for Restaurant Traffic Data
Restaurant traffic data is used for improving operations and strategic planning. A key use case is location planning, where traffic patterns and visitor trends help identify optimal locations for new restaurants or expansions. Understanding customer flow also supports decision-making for menu planning, staffing, and marketing strategies.
Main Attributes of Restaurant Traffic Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| Float | The latitude of a point on earth's surface. Commonly abbreviated as "lat". | View 7 datasets | |
| String | The address of a company or contact (street name, number, zip code, city, county, country). | View 4 datasets | |
| String | The name of a city. | View 4 datasets | |
| Float | The longitude of a point on earth's surface. Commonly abbreviated as "long". | View 4 datasets | |
| String | The category of a point of interest (POI). | View 4 datasets | |
| String | The North American Industry Classification System (NAICS) code of a company. | View 3 datasets |
Restaurant Traffic Data Use Cases in Detail
Restaurant traffic data is used by restaurant owners and managers to analyze customer behavior, make informed decisions about staffing and scheduling, optimize marketing strategies, and improve overall operational efficiency. Restaurant traffic data is employed in different operations and strategies:
- Location Planning: Adjusting staff levels based on peak and off-peak times.
- Marketing Strategies: Targeting promotions during high traffic periods.
- Menu Optimization: Analyzing which menu items are popular at certain times.
- Customer Experience: Enhancing the dining experience based on traffic patterns and feedback.
For instance, a restaurant might use foot traffic data to identify that lunchtime on weekdays is particularly busy, prompting them to introduce a special lunch menu to cater to the rush.
How is Restaurant Traffic Data Collected?
Restaurant traffic data is collected using various methods. Modern technology provides several effective tools to gather this data accurately:
- POS Data: Point of Sale (POS) data track transactions and can give insights into customer counts..
- Wi-Fi Analytics: Tracking devices connected to the restaurant’s Wi-Fi network.
- Foot Traffic Counters: Devices installed at entrances to count visitors.
- Customer Surveys: Collecting data directly from customer feedback.
- Third-Party Services: Partner with companies specializing in traffic analytics.
What Types of Restaurant Traffic Data are Available?
Restaurant traffic data comes in various forms, each offering different insights:
- Foot Traffic Data: Information on the number of visitors.
- Mobility Data: Insights into how customers move within and around the restaurant.
- Transactional Data: Details of sales and transactions.
These types of data can be combined to create a detailed picture of restaurant performance and customer preferences.
Restaurant Traffic Data Attributes
| Attribute | Description | Example |
|---|---|---|
| Foot Traffic Volume | Number of customers visiting the restaurant over time. | E.g., 500 visits per day. |
| Time of Visits | Specific times when customers visit the restaurant. | E.g., Peak hours: 12 PM - 2 PM. |
| Visitor Demographics | Age, gender, or other characteristics of visitors. | E.g., 60% male, 40% female, aged 25-45. |
| Visit Frequency | How often customers return to the restaurant. | E.g., Average of 2 visits per week. |
| Dwell Time | Duration customers spend in the restaurant. | E.g., Average of 45 minutes. |
| Traffic Sources | Origins of customer visits, such as nearby offices or tourist areas. | E.g., 40% from nearby shopping mall. |
| Day of Week Trends | Traffic patterns based on the day of the week. | E.g., Highest traffic on Saturdays. |
Do Restaurants Use Data Analytics?
Restaurants use data analytics extensively. By analyzing data, they gain valuable insights into customer behavior, operational efficiency, and market trends.
Analytics tools can process vast amounts of data, providing actionable insights that help in making informed decisions and improving overall business performance.
Frequently Asked Questions
How Frequently is Restaurant Traffic Data Updated?
Restaurant traffic data updates can differ based on your needs. Some datasets are refreshed in real-time, giving you up-to-the-minute insights, while others update daily or weekly. If you’re working on something that requires constant monitoring, we recommend opting for real-time or daily updates. This way, you’ll always have the most current information to guide your decisions.
How is the Data Quality of Restaurant Traffic Data Ensured?
The quality of restaurant traffic data is a top priority. Data providers use smart algorithms and regular cleansing processes to filter out any inaccuracies, duplicates, or corrupted points. If data accuracy is critical to your project, we suggest going with providers known for their stringent quality control. This ensures you’re working with clean, reliable data from the start.
How Can Restaurant Traffic Data Be Delivered?
Restaurant traffic data is typically delivered through multiple formats to fit your workflow. Whether you prefer API integration for real-time access, S3 buckets for bulk downloads, or formats like JSON, CSV, or XLS for analysis, there’s flexibility. If you’re unsure, we recommend trying out a sample dataset first to see which format works best with your system.
How is Privacy Managed in Restaurant Traffic Data?
Privacy is taken seriously with restaurant traffic data. The data is anonymized and aggregated, meaning individual users aren’t identifiable. Providers comply with strict regulations, like GDPR, to protect user privacy. If privacy is a concern for your project, we suggest using data providers that adhere to the latest privacy standards, so you can work confidently and responsibly.
How Much Does Restaurant Traffic Data Cost?
The cost of restaurant traffic data depends on several factors, such as the size of the dataset, the geographic coverage, and how often you need updates. There are options ranging from one-time purchases to monthly or yearly licenses. For larger projects, custom pricing might be available to better match your specific needs. We recommend starting with a trial or smaller dataset to ensure it fits your budget and use case.
What are the Similar Data Types to Restaurant Traffic Data?
Similar data types to restaurant traffic data include visit data, real-time foot traffic data, and aggregated foot traffic data.
