// function to pull cookie value Skip to main content

Optimal Store Location

Optimal Store Location Analysis

Choosing the optimal location to open a new store is a strategic and potentially pivotal business decision. Depending on consumer interest and proximity to competitors’ stores, brands may decide to open their next store in a completely new region or in a familiar area with existing locations. Our Optimal Store Location Analysis allows you to use Spectus data to visualize a brand’s market penetration to help determine the best location for a new store. See it in action or continue reading to learn more about how Spectus can help you determine optimal store locations.

The Spectus Data Clean Room is equipped with visitation insights for millions of stores in the US. Store visits are obtained from our GPS data by using our proprietary algorithms to establish which device visited each location, as well as its arrival time and dwell time inside a store.

Determining Optimal Store Location

To conduct an Optimal Store Location Analysis, we first define the relevant parameters, such as the brand, vertical, and geographic locations of existing stores. In Spectus, you can also identify the main US chains’ store locations along with their opening hours, popular visit times, and SIC code. In this example, we’ll consider a national QSR chain as a reference brand and look at several other QSR brands in the US to compute the market size and other competitor-based factors.

To start, we’ll visualize the locations of our chosen QSR brand:

Optimal Store Location AreasTo find the most optimal locations to open new stores, we first decide whether to conduct the analysis by country, state, county, census tract, census block group, or zip code. For this example, we’ll determine the optimal county to open a new store.

We look at several characteristics to identify the best counties to open a store for our brand:

  • Number of existing stores in the county
  • Number of competitors’ stores in the county
  • Distance to the nearest existing location
  • Distance to competitors’ locations
  • Frequency of visitors to all stores in the vertical (i.e. the reference brand and its competitors)

To determine the optimal county to open a new store we primarily consider two independent factors: 

  • Market size – Market size represents the number of visits to competitors’ stores in the county in the last four weeks. If there is high visitation to competitors’ stores we assume there is high interest in that vertical and infer a large market size. This metric is then transformed with a logarithm and scaled between 0 and 10 where 10 represents a large market size.
  • Reachability – Reachability represents the distance people need to travel to reach a brand’s nearest store. We calculate reachability by considering stops, computing their distance to the closest store, and taking the median. This metric is then transformed with a logarithm and scaled between 0 and 10 where 10 represents high reachability. For a deeper analysis, we can also compare a brand’s reachability score with any competitors’ in a given area.

Once we’ve determined a brand’s market size and reachability we can plot the distribution of counties without any of the QSR’s stores (blue) and counties with at least one (orange). Market size is quite high in counties with existing stores, but some counties have a high market size and no stores. Reachability is – by definition – higher in counties with at least one brand location than in counties without any.

Market Size Analysis
Market Size
Market Size Analysis Opportunity
Reachability

Using market size and reachability, we can define two opposite scores:

  • Exploration score: a score from 0-10 where 10 represents a county with high market size and low reachability. By looking at counties with high exploration scores, brands can identify new counties in which to expand business operations.
  • Escalation score: a score from 0-10 where 10 represents a county with high market size and high reachability. By looking at counties with high escalation scores, brands can identify counties in which to increase business operations.

The Results

Here are the top counties sorted by Exploration score. These counties have low reachability and high market size scores, meaning they are far from the brand’s existing locations, and that people in these counties are highly interested in QSRs. Hawaii and Texas might surely be sweet spots for opening new stores!

Optimal Store Location Results 1

Here are the top counties sorted by Escalation score. These areas have high reachability and high market size scores, meaning they are close to the brand’s existing locations, and that people in these counties are highly interested in QSRs. These may be strategic counties to double down on business operations and open additional stores.

Optimal Store Location Results Escalation

Interactive Web App to Demonstrate Optimal Store Locations

These results are visualized on the map below, where the black points represent the brand’s current store locations. Counties highlighted in yellow are considered the most optimal for a new store location according to the exploration score (left) or escalation score (right).

Start using Optimal Store Location Analysis and other spatial data analysis tools today:

Let's talk