Best Store Location Datasets, Databases & APIs
Store location data is information about the geographical locations of retail businesses. This data is very similar to point of interest data and can be useful in learning where a brand’s best performing area is and where they are looking to target their audience.Learn more
Location Data | Global Store Location Data on 11M+ POI | SafeGraph Places
Global Point-of-Interest Data | POI, Geospatial, Sentiment (Reviews), Footfall, Business Listings & Store Location | 200 Million+ POIs Mapped
Factori Visits Data | Point-of-Interest (POI) data for APAC & MENA
Locationscloud - Grocery Store Location Data | Complete List of All Grocery Store Locations | USA
Datahut Microsoft Store Location Data for USA (complete list of all Microsoft store locations)
Location & Territory Data |Geospatial, Sentiment (Reviews), Footfall, Business Listings & Store Location | 200 Million+ POIs Mapped
Quadrant Point-of-Interest (POI) Data - Store Location Data - with custom, on-demand metadata and attributes
POI & Building Footprint Data | +2.5M Locations USA | Echo Analytics
Xtract.io - POI data ( Point-of-Interest ) | Global locations data | 6 million POIs
#Crosswalk by Stirista: Behavioral Intent Visitors Location Data
The Ultimate Guide to Store Location Data 2022
What is Store Location Data?
How do you determine if a site is a good location for a new store? Even if it is a good site in a good location, how can you be sure your particular store will do well there? When siting a new retail store, getting the right location is everything. It can determine whether your new store thrives or dives. So how can you be sure you make the right decision and pick the location with the best business potential? More powerful technology has made more and richer data available to help with these decisions. Data which has never been available in such complexity before and which can make you more certain of success. Retail site selection is not only becoming more crucial and difficult; it is also becoming more valuable than ever. Retail Store Location Data helps companies decide on the best locations to expand their business. It does this by combining different types of data to get the most accurate insights. It allows businesses to investigate potential areas and quantify how robust they are and identify the local population make-up. It can provide information on the locations of other stores, including the stores of competitors, and identify areas that are growing and shrinking. It can provide information on areas of increasing or decreasing foot traffic.
Who uses Store Location Data and for what use cases?
All businesses can benefit from using Store Location Data analytics in their intelligence and decision making. With location intelligence, you can detect patterns and improve location based marketing. Historical analysis and present and future forecasts can be gathered from this data so you can make better decisions and choices on where to site your new business. You can’t remain in business unless there are people in your location willing to come into your new store and purchase from you. But even knowing you have the right type of customers nearby right now is only half the battle. What about five years from now, or ten, or fifteen? Store Location Data not only gives you the relevant insights on where to site your store today, but can make predictions on how your business is likely to progress in the future. Store Location Data can help in other ways. It can help identify untapped markets. It can provide insights on where to source raw materials. Store Location Data will make sure you are better equipped all round to find the perfect location for your new business.
A good Business Location Data system should flag up any concerns on your store placement. It should also make you aware of any potential opportunities. It should keep you informed of any potential competitors in your proposed area and can supply demographics on existing stores in the area. The customized analysis and demographics supplied by your Store Location system allows your company to make better informed decisions.
The demographics of the particular potential customers in your proposed area may affect how you want to present your store. Is the local population a young, smart urban set or a rural community of older retirees? Store Location Data demographics can suggest a customer-centric approach that will appeal to the particular demographic groups in the proposed site area. Other information your Store Location data may take into account are consumer behaviours and traffic patterns.
Accurate count and analysis of footfall trends, supplied at a granular level, will enable forensic insights into flow and trends around a physical space. Local area demographics and potential consumer behaviour datasets give insights into whether an area is the optimum site to locate a new store. Store Location Data analytics helps you evaluate potential customers and profile them using data analytics for consumer classifications, to measure market demand in a potential area and if the area contains your ideal customer base. Opening a new store is a major decision and an expensive undertaking. Markets are demanding and finding the right customers who will be attracted to your new businesses location is key. Identifying sites businesses can target for expansion is a valuable part of your business decisions going forward. In retail, it’s important to stay ahead of your competitors in any way you can. Using Retail Location data means you can be sure you are locating your new business in the best site to achieve optimum revenue.
What are typical Store Location Data attributes?
Store Location Data provides information about locations you may wish to build a store. Users can simulate location-built applications to activate interactions. You can click on the area on the map you are considering building your store to trigger the interactions you have set up. Typical Store Location Data attributes include: Latitude and Longitude - which show the position of the location. Additional attributes such as Horizontal Accuracy - which highlights the degree of error in a particular data point, and Altitude and Elevation - which pinpoint the height above a reference point (usually sea level), may be included for a more accurate picture of geographical positions. Foot traffic can be built in as an attribute in a customised system.
How is Store Location Data typically collected?
It is important to know how Store Location Data is collected as this determines the accuracy and depth of the collected data. This has direct implications for the suitability and usability of the data for your business. Typically Store Location Data is collected by data collection providers by way of SDKs (software development kits). SDKs are really useful as they contain a collection of development tools built into one package, such as a compiler, debugger, and software framework, enabling customised applications to be designed.
Companies usually purchase Store Location data from data providers. A company would give data collection providers details about the data they would like to have, such as foot traffic in an area or how many competitive companies in a given area. The data collection provider would then use POIs (points of interests) combined with other types of location data such as catchment area analysis to supply data that fits your needs, based on your requirements.
The data collection provider gathers Store Location Data by cross mapping and analysing the geolocated data, performs quality checks, and provides companies with it in raw form. If you require it, they will clean the data and supply it in a form that you just have to load into your system. The Store Location Data provider may also supply you with areas of concern they have identified and areas of opportunity relevant to your business. As more datasets are added and combined, more information will become available to enhance the value of data analytics for businesses and allow companies to understand data sets in a way that was previously unimaginable.
How to assess the quality of Store Location Data?
The quality of the data you receive is paramount to the success of your business but can vary from one data provider to another. The Store Location Data provided to you will be of no use or even harmful to your business if it is not good quality data. So how do you ensure you receive good quality Store Location Data which is complete, timely and valid? There are some steps you can take:
- Ensure you buy from a reputable company.
- Get recommendations from other companies already using a Location Store Data provider
- Ensure the provider has best-practice rules in place, up-to-date protocols and encryption mechanism
- Monitor the Store Location Data for accuracy over time
- Use AI systems to monitor for incomplete records and double entries
- Ensure alerts and trust scores are built in
How is Store Location Data typically priced?
Prices for data analytics varies greatly depending on the kind of data you require. Store Location Data analytics typically can cost up to several thousand dollars a month, which is paid by monthly subscription. Many businesses consider this reasonable compared to the losses incurred by siting a potential business in a disadvantageous location. Prices may drop as computer power becomes more readily available. But if you wait to purchase Store Location data until prices drop, you may find you have already lost out to competitors.
What are the common challenges when buying Store Location Data?
There are several challenges for companies when purchasing Store Location Data, such as:
- ensuring you receive real time, up-to-date data and not data that is outdated
- ensuring the data you receive is unique to your company and completely fulfils your needs; and not stale data that is being sold to multi companies, including your competitors
- ensuring data is good quality
Take your time when first using Store Location Data. Where to site a new store is not a decision to be treated lightly. Test and retest your system, using varied questions to get the optimal results. Although setting up a Store Location Data analytics systems may take a bit of time at first, it will be worth it when your new store starts generating loads of revenue.
What to ask Store Location Data providers?
There are a number of questions companies should keep in mind when talking to data providers. Businesses may want to ask:
- Is the Store Location Data realtime data and is it updated regularly?
- How is the Store Location Data collected?
- Will the Store Location Data be customized to the exact business requirements of your company?
- Will your Store Location Data analysis results be stored in an individual database?
- How quickly can the Store Location Data analysis be supplied?
- Will the Store Location Data analysis report include causes of concern and opportunity assessments?
Where can I buy Store Location Data?
Data providers and vendors listed on Datarade sell Store Location Data products and samples. Popular Store Location Data products and datasets available on our platform are Location Data | Global Store Location Data on 11M+ POI | SafeGraph Places by SafeGraph, Global Point-of-Interest Data | POI, Geospatial, Sentiment (Reviews), Footfall, Business Listings & Store Location | 200 Million+ POIs Mapped by The Data Appeal Company, and Factori Visits Data | Point-of-Interest (POI) data for APAC & MENA by Factori.
How can I get Store Location Data?
You can get Store Location Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Store Location Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Store Location Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Store Location Data?
Store Location Data is similar to Business Listings Data, Electric Vehicle Charging Stations Data, POI Visitation Data, Business Location Data, and POI Sentiment Data. These data categories are commonly used for Store Visit Tracking and Retail Intelligence.