We were engaged by a client to map out the locations of Play Centers in the US, using the internet as a data source, to explore the relationship between the locations and demographics.
Such information is useful to highlight areas of saturation, under supplied areas or as a proxy for a growing company or product.
A logical process to follow
The geo-location process involves a few stages: obtaining the relevant address data, cleaning it, resolving the address data to latitude and longitude co-ordinates, cleanng it again and plotting the results on a map.
We use a data analytical tool that allows easy manipulation of data and also to act as a versatile container that can call on a variety of third party tools such as web services calls and statistics packages.
Displaying the locations
Having resolved addresses to a latitude and longitude, it is easy for us to display the locations on a map.
However, though this confirms Calimere Point’s ability to accurate geo-locate retail locations on a map at this stage it’s not incredibly useful to the client: more analysis is required.
Demographics and Statistical Models
The client wanted us to link demographic data to the Play Center locations: they wanted to discover locations that had a high infant population but had no Play Center within n kilometres.
Using demographics data per zip code, the centre of mass, Play Center location, spherical distance calculations and n-th nearest neighbour modelling we could identify potential opportunities of growth and of oversupply.
A new way of looking at things: demographics and geo-location
The map shows zip codes that have do not have a Play Center within 100 km. The density of purple colouring indicates zip codes that have a high infant population and are at least 100 km from a Play Center.
The client has list of new location opportunities to explore, driven by a key factor in its catchment area strategy.