By Devon Hopkins, Marketing Director, Content, Carto
If you’ve ever been part of a new development project for a store or building, you know how many factors go into making decisions about physical location.
Whether you’re opening new stores, consolidating stores, or deciding on an optimal location for a distribution site, understanding the surrounding context of a site is vital to success.
Retailers, restaurant chains, hotels, and a new wave of brick-and-mortar industries have to make site planning decisions and they have to get them right the first time. These businesses are turning to location intelligence and advanced spatial analysis techniques to make sure they have everything they need to make the best decision possible.
Is spatial analysis a core part of your site planning process?
Below, we’ll explore several ways that visualising and analysing location data can benefit your business in today’s hyper-competitive landscape.
Use Demographic and Lifestyle Data to Uncover Potential Markets
Most of us are familiar with the benefits of leveraging data — in marketing analytics or business intelligence, for example. By adding new sources of data to your existing data sets, you can gain strategic and cost-saving insights that help create a better picture for your site planning.
You’ll understand the potential customer base of an area — not just how many people are there, but whether they are your ideal customers.
Here’s an example: A leading pharmacy retail chain wanted to know the best locations for 5 new pharmacies they were planning to open in a Los Angeles metro area. We mapped their current pharmacy locations and then enriched the data (from our Data Observatory) with census tract polygons, demographic data, median household income, and car ownership data.
Using the ‘create centroid of geometries‘ spatial analysis, we were able to find the 5 best locations based on a variety of factors. When the retail chain adjusted the ideal median household income and customers driving data, the location intelligence application dynamically adjusted. This then provided the number of “Seniors Served” — who fall within the 8 mile radius of each location — and the “Potential Seniors Served” — which show the total number of seniors within the map.
The pharmacy retailer can now take this visualisation to the next level with their own location data, validating recommendations from this platform with their own customer transaction data from the Los Angeles region.
Combine Location Data and Spatial Analysis with Online Transaction Data
A retail company provided us with 16 retail locations and 1700 online transactions in the Los Angeles region. With an increased demand for delivery from online orders, they wanted to convert 3 of their stores into online distribution centers. The distribution centers needed to be spaced to cover a wide area to serve the most customers.
The spatial analysis above shows the 3 optimal locations for distribution based on location of online sales and existing store locations. The shaded regions represent a 15-minute driving radius around the distribution centers, giving us insight into how many customers we can serve.
This US-based e-commerce company (we’ve provided an image only to protect the customer’s data) wanted to expand into the European market. They wanted to know, based on their current transaction data, where the best place would be to open additional distribution centers in Europe.
This application shows — based on transactions from their top 5 european countries (aggregated to protect privacy) — the optimal 2 locations for distribution centers (near Frankfurt and London). Obviously, the company will take into account other factors in their decision-making process, but this application provides a good starting point for exploring different potential sites.
Understand Where Your Customers Will Likely Travel To
Sanitas, a healthcare provider in Spain, uses CARTO to gain insights related to their customer’s location. They are able to identify areas which a higher number of potential customers by combining demographic data from the Data Observatory with traffic, mobility and routing data.
If you’re only looking at zip code or geographic segmentation, you’re missing vital context about how your customers move in relation to where they live and work. For example, Sanitas was able to see how crossing a railway track or a specific road with heavy traffic was a big factor in customers avoiding a certain site.
No one can predict the future with absolute certainty, but the more data — and more kinds of data— you include in your site planning, the more likely you are to make decisions that help your business compete, grow, and fill a genuine need in the marketplace and the community.
Article first appeared on the Carto blog.
Lava Labs brings together innovation and technology, combined with expertise and deep understanding of businesses and their needs by engaging with industry leaders to empower organizations. We specialize in building custom web and mobile applications in Malaysia and around the APAC region.