Use Geosocial data to select sites where people are already interested in your brand.

Let’s say we are representing Lululemon in the Cincinnati DMA. We need to find places that not only fit their standard criteria but also places that the people have an affinity towards Lululemon.

We see they have two locations in the Cincinnati DMA right now. And we want to find which block groups have segments that are really interested in Lululemon.

Lululemon locations in Cincinnati DMA

With most segmentation systems, it takes a while to figure out which segments have a certain brand affinity. Here are some of the typical methods:

  • Use a sales regression model to see which segments contribute to sales.
  • Use customer data, such as loyalty data, to match it to the segments.
  • Perform a portfolio analysis to identify which segments are dominant around successful locations.

But all of these take a long time. One of the great things about the PersonaLive™ segmentation is—because we already have these people's retail behavior—we can figure this out really quickly using a tool called the Brand Sorter.

The Brander Sorter allows users to rank the top segment for every brand based on the visitation patterns of 117 million devices. All of these devices are codified to their segment and, for each segment, we are looking at what types of retail are they over-indexing on, and are they showing up in the actual polygon for that brand.

Let’s do that with Lululemon.

Top 11 segments for Lululemon in the Brander Sorter

We see that #SkyHigh has an index of 436, meaning that this segment is 4.36x more likely than the national average to physically visit a Lululemon location. In fact, we have 11 segments that are at least 2x more likely to show up in Lululemon locations. Now, let’s take the sum of these 11 segments to create a Lululemon index. This is simply the sum of the population that falls into these segments.

Let’s go to Esri’s Business Analyst to map our locations and our new Lululemon index.

Immediately, we see Lululemon has done a pretty good job. There are two locations that are already in high-scoring areas (the darker the color, the more households there are that have an affinity towards Lululemon).

But there's an opportunity here. In the downtown area, there's a lot of households that fall in these segments. This is also true in the Clifton area, which essentially has the University of Cincinnati and some higher-income houses around the retail area. So, these two locations are great opportunities for Lululemon.

Top circle: Clifton, bottom circle: Downtown

Retail Analytics & Site Selection