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Spree StoreFront Zones API Search Results & Alternatives
Get global city, region, and country data. Filter cities by name prefix, country, location, time-zone, and even minimum population. Display results in multiple languages. Sort by name, country code, elevation, and population - or any combination of these. Get distances between cities. Get all country regions. Get all cities in a given region. RESTful API adheres to industry best-practices, including HATEOAS-style links to facilitate paging results. Data is periodically refreshed from GeoNames and WikiData. Backed by cloud-based load-balanced infrastructure for resiliency and performance! If you'd like to host the service internally, contact us for details through the dev portal site. Data licensed under Creative Commons, http://creativecommons.org/licenses/by/3.0
Hyperlocal Demographics, Vehicle Traffic, Economic, Market Signals, and More. !(https://www.google-analytics.com/collect?v=1&t=pageview&tid=UA-166301943-3&cid=2fbf3778-84e6-41a8-ad46-1765dbd5be20&dh=rapid.com&dp=%2Fidealspot-geodata-v1&dt=IdealSpot%20GeoData =1x1) Use this API to request IdealSpot hyperlocal geospatial market insight and geometry data. Broad categories include Demographics, Housing, Spending, Labor, Business Establishments, Economy, Consumer Segmentation, Vehicle Traffic, Polygons, Online Demand. We update more frequently and are more granular than alternatives. Trusted by large enterprise. Query US data and location geometries by rings, drive times, bike times, walk times, public transit times, nation, states, counties, tracts, zipcodes, block groups, opportunity zones. Frequently used for property reporting, retail, commercial real estate, financial and marketing applications, GIS, and spatial data science or machine learning.
Related APIs in Category: eCommerce
This is an API to check a website to determine if it's an online ecommerce store. We do this in a few ways -- first we check to see if it matches common e-commerce store platforms (ie. Shopify, Magento, etc). Next we check the page text to see if we can determine it has characteristics of an online store. Finally we parse the DOM, looking for clues to see if it links to the server that has a e-commerce backend.