Key Insights

• Spatial analysis is a process focused on the wider network rather than on individual locations, identifying the wider ripple effect changes can have on the business as a whole.
• Most businesses already collect geospatial data, such as customer postcodes or service records. The key is to integrate these data sets in with external information, like competitor activity or changing demographics.
• GMAP can deliver a toolkit that helps businesses get started with spatial analysis, including access to DVLA data and geodemographics.

It's the same old story...

…Three potential sites and a budget that can only accommodate one. Each has a compelling case to present: the first site is likely to have the most customers, the second the lowest operational costs, and the third is a mere three miles from the highest-performing store. So, which one comes out on top?

This is where spatial analysis comes into play, identifying the wider network interactions that are rarely ever obvious from studying the figures of one site in isolation. Supported by strong geospatial data, implementing spatial analysis into location planning can help you locate coverage gaps, preempt customer trends, and gain greater insight into the impact of a particular decision.

In this guide, we’ll explore what spatial analysis is, what geospatial data means, and how GMAP can help businesses implement an effective spatial analysis process into their own location planning.

What is spatial analysis?

Spatial analysis is the process of examining geospatial data - such as customer postcodes or store catchments - in order to pick out potential patterns or relationships that may not be apparent when examining a site’s numbers in isolation. 

On paper, for example, Shop A might produce £3.9m in turnover a year. Spatial analysis, however, notices that £1.6m occurred primarily due to it sharing a catchment area with Shop B.

It highlights how factors such as site location, customer demographics, and competitor activity can all influence network performance as a whole, as well as the ripple effect just one small change could have on the performance of nearby sites.

Some examples of spatial analysis techniques typically utilised, include:

• Visualisation - Plotting your sites, customers, and competitors onto a map.
• Measurement - Calculating commute distances or catchment areas.
• Benchmarking - Segmenting your sites based on commonalities so locations can be accurately compared against each other.
• Pattern detection -  Identifying hotspots or gaps.
• Modelling and prediction - Forecasting revenue or testing outcomes.

An effective implementation of this process requires the use of good geospatial data at all stages.

What does geospatial data mean?

Geospatial data means any data with a geographic component that can be linked with a place strongly enough to analyse it. 

Most of the data businesses collect is already geospatial in nature, even if it is never referred to as such. Examples of this geospatial data include: nearby parking availability, customer delivery addresses, and typical commute times.



This data is inputted into the spatial analysis process, helping to provide more impactful location intelligence for site planning.

What is location intelligence, and how does it differ from spatial analysis?

Location intelligence is the insight a company benefits from when spatial analysis is applied to a business question they’re considering. It’s best to think of spatial analysis as the means, while location intelligence is the conclusion reached at the end of the process.

Location intelligence applications are varied, and can be seen in a diverse group of sectors, such as:

• Automotive  - Assessing dealer network coverage, identifying potential gaps and overlaps, and influencing EV charge point locations. This is covered in greater depth in automotive location planning for dealer networks.
• Retail - Network strategy, expansions and closures, catchment overlap, and impact of competitor activity. 
• Leisure and hospitality - Understanding demand or travel patterns and how that might vary by time of day or day of the week.

For more detail on what location intelligence is and why it’s important, read our full article here.

Examples of spatial analysis tools in location planning

At GMAP, there are a range of approaches that we take:



Network and site location analysis

Network and site location analysis is the mapping of your own network directly onto your customers and competitors. 



Once this has been completed, it is then possible to identify where important relationships lie. It can show where the demand is and isn’t being met, as well as where your own sites could actually be competing with one other.

Geodemographic data and consumer profiling (CAMEO)

Geodemographic classifications go beyond the usual population statistics to provide greater insight into the exact demographics of your customer base.



At GMAP, we offer CAMEO, an industry-standard geodemographic classification tool, that helps you to understand who your customers really are. After all, the better you know your consumers, the more likely you are to retain them with location planning that actually matches their needs.

DVLA vehicle data

DVLA data is an important tool for those planning an automotive network. This dataset is essentially a census of UK car ownership, and includes make and model, as well as new vehicle registrations and partial postcodes.



This is a valuable tool for automotive businesses to have during location planning, as it shows the number of vehicles registered in the region and the number your network sold, highlighting precisely what percentage of the market you are capturing  in contrast to what was available.

Hexagonal geographies

Administrative geographies can be misleading for spatial analysis, with postcode sectors in central London and rural Cumbria the complete opposites in area and population. 



With hexagons, there is one consistent distance from the centre to every neighbour, keeping analysis smoother and more reliable. At GMAP, we use hexagonal geographies to provide data within MVPLUS, as well as to include datasets into projects, such as the LeisureVision Destinations.

How to get started with spatial analysis?

Most organisations simply need to progress through three stages to get started:



1) View Your Own Network

Begin with the data you already own, such as site locations, performance data, and customer postcodes, whether that is a loyalty scheme or service records. Plot them onto a map, and measure them alongside real catchments instead of assumed ones.

2) Add In Market Context

Next, add in the external factors. This can be competitor networks, population changes, geodemographic classifications, or industry-specific market data. MVPLUS is the perfect tool to bring in at this stage, with map layers and GMAP datasets all available within the product to enhance your analysis.

3) Test the Decisions Before You Make Them

This is where you begin scenario modelling - what happens if we open this site, close that one, or open up in a new region.



How can GMAP help with spatial analysis?

Contact our team today

Whether you’re just starting out collecting your own network data, or preparing to run complex business-wide scenario testing, GMAP is here to help you at every stage. Contact our team and discover how you can enhance your location planning today.

FAQs

What is spatial analysis?

Spatial analysis is the process of examining geospatial data in order to locate potential certain relationships between sites. It primarily focuses on how the positioning of your sites, customers demographics, and competitor moves all influence network performance.

What does geospatial mean?

Geospatial data means any data that includes information about where something is, from exact coordinates to customer postcodes. 

What are some common location intelligence applications? 

There are a range of common location intelligence applications, including site selection, network expansion, competitor impact assessment, and infrastructure planning.



What are the limits of spatial analysis?

There are limits to what spatial analysis can offer: 

• It cannot tell you if a deal is fair  - Analysis will demonstrate a site’s worth to your network, but it won’t tell you what a fair cost is.
• It isn’t able to fully consider operational factors - Details such as management capability, staffing, and effective marketing aren't usually included within a spatial model.
• Strong geospatial data is required - Out-of-date or poor quality information will produce incorrect information, so strong data input is non-negotiable. 
• Human judgement is still necessary - Effective spatial analysis may be able to cut down a shortlist from forty sites to three, but a person will always have to make the final decision.