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Geo-location Analysis

Data

Driven

Value

Using enhanced data analytics to deliver
data that creates new insights

Leveraging multiple sources of publically available information, our US-based client asked us to deliver an analysis of the relationship between Play Center locations and regional demographic data across the US. The data analytics and visualisation solution delivered was integral in driving our clients strategic growth.

Industry: Retail & Leisure

Challenges

Data Sourcing

Which data? From where? How do you extract it?

Data Normalisation

Scrapping data from across various web-based sources required a nuanced approach to cleansing and aligning data sets to make them usable for the analytics.

Demographic Overlays

Inclusion of granular demographic data sets required us to create further dimensions to the existing graphical representation to allow our client to gain deeper insights.

Bringing the picture together

We worked closely with our clients to refine the solution to ensure they got the deepest possible insights, adding and removing datasets to sharpen the focus.

Rolling it out

The deal team consuming the data came from diverse organisational functions – the data visualisation solution delivered needed to cater for these different lenses.

Data Solution

Cloud Solution

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, cleaning 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.

Geo-location Data Visualisation

Data Visualisation showing potential over-supply

Geo-location Visualisation Screenshot

Data showing potential new play centers

Benefits

A new way of looking at things: demographics and geo-location

Deep Insights enabling better decisions

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.

Understanding their Data

The organisation has list of new location opportunities to explore, driven by a key factor in its catchment area strategy.

Organisations are growing increasingly interested in leveraging geo-location analytics to add new ways of assessing their activities and to provide enhanced overlays to their existing data assets – we are supporting them on this journey.

Related Data Solutions

Calimere Point have helped our clients gain value from the data revolution.