Enrichment of catchment areas for store characterization
In this example we are going to characterize all Starbucks locations in the US by the total population covered by their catchment areas. We are going to define these catchment areas as a 3km buffer around each store.
First, let’s start by visualizing all Starbucks locations in the US, extracted from Safegraph’s Places dataset sample, freely available through Snowflake’s Data Marketplace.
To quickly explore this data, using the Analytics Toolbox, we can easily compute an aggregation of these locations using Quadkeys at resolution 15, which lets us visualize the result as a heatmap. Here is a close-up of the Manhattan area, where we can easily identify the areas of highest concentration of Starbucks stores.
Next, we enrich the resulting Quadkeys with the total population and the population by gender using CARTO’s Spatial Features dataset, available for free in the Snowflake Data Marketplace. Since this dataset is already delivered in Quadkeys at resolution 15, enrichment can be performed by a simple JOIN.
By zooming into a particular area we can see the distribution of the total population (where darker colors represent higher population levels).
Once we have this data ready, we can now calculate the total population that is within a 3km radius from each store location. This catchment analysis can be performed from start to finish with the following query: