Foursquare Global Places

Foursquare has developed a map of the world using first-party data derived from over 14 billion explicit check-ins from our consumer apps. We’ve built and refined those maps for the past 11 years. We’ve also merged with leaders in the space to increase our breadth of sources and improve our ability to ingest, aggregate, and resolve billions of location data references. Over the last 10 years of focus on location data, we’ve also accumulated numerous geographic datasets, geospatial assets, and validation rules.

Foursquare programmatically crawls 46K authoritative sources for inputs. We combine our first-party data, ground truth data sets, web resources, and partner with 3rd parties to incorporate updates directly from business owners to ensure as close to 100% coverage as possible.

Our Places data dictionary can be found here:
https://view.highspot.com/viewer/60147d2db7b7391ebc892c5a

Samples/Tables Included:
- All places in New York City
- All places in San Francisco
- All places in London
- If you need a different type of sample, please contact us at [e-mail]

Standard Fields Included:
- venueID, venuename, and translatedvenuename
- latitude/longitude
- address
- city, dma, state, postalcode, and countrycode
- date_created
- category information (primary and secondary)
- chainid, chainname, parentid
- hours and hours_popular
- phonenumber, url, facebookid, instagramhandle, twittername
- rating
- description
- price
- popularity_score (i.e. Foursquare’s calculated foot traffic score)
- score_venuereality (i.e. Foursquare’s calculated confidence score)

Other rich fields (e.g. photos, tips, tastes) are also available. Detailed information on each field can be found here: https://view.highspot.com/viewer/60147d2db7b7391ebc892c5a

Example Use Cases:
- Place Search/Recommendation for Consumer Experience. Types of customers range from social platforms (e.g. enabling global geotags for Twitter) to Food Delivery (e.g. restaurant discovery for DoorDash) to Ride Hail (e.g. global Places for Uber).
- Site Selection or Retail Planning. Any company with a physical footprint of over 100+ locations will benefit from Foursquare Places data to better enable site selection decisions. Customers typically fall into the Retail, Dining, and Hospitality industries.
- Competitive Benchmarking. Understand how foot traffic to your locations indexes by neighborhood, market, state, or country versus your competition.
- Transaction cleansing for financial services companies.

搜集汇总

背景与挑战

背景概述

该数据集整合了Foursquare平台14亿次签到记录及多渠道数据，提供全球地点的详细位置信息、营业属性及人流评分等字段，适用于位置服务、商业选址等场景。数据包含标准地理字段和扩展属性，并通过持续更新确保覆盖完整性。