Retail Analytics

Case Study: Using Data To Land Anchor Tenants and Lift Visits 16%

Lyden Foust


August 17, 2022

This case study was adapted from Al Urbanski’s article in Chain Store Age.

The Context

The Village of Rochester Hills is a lifestyle center located in a suburb of Detroit. Today, the thriving center features more than forty inline tenants and two anchor stores: Whole Foods Market and Von Maur. But this wasn’t always the case.

The Challenge

On April 18th, 2018, the team managing the center found themselves in a tight situation. The parent company to Carson's, the main anchor tenant at the time, filed for chapter 7 bankruptcy and announced the closure of all its locations. 

This left the team with a gap to fill and prospects didn’t look great; the Detroit metropolitan area had not seen a new department store opening in a decade. 

The Solution

Going against the narrative that department stores are dead weight to a mall, the team used data to help potential department stores understand the unique interests of its visitors. Below is an excerpt from the article in Chain Store Age:

Before signing its lease, Von Maur used’s GeoWeb data and found that the Total Trade Area surrounding The Village had an index of 131 for department store shoppers—meaning that locals engaged in department-store-related content 1.3 times higher than the national average. 

The Result

What may be the first new department store in the Detroit metropolitan area in over a decade, Von Maur is driving visits to the shopping center. The department store’s March 2022 opening pushed Yo3Y visits up by 16.9% compared to the mere 4.3% Yo3Y increase the month before. 


How PersonaLive Segmentation System Works

Personalive segmentation uses social media, mobile foot traffic, online activity, and individual-level demographics to organize every US household into one of 80 behavioral segments. These segments provide visibility to the online and offline preferences of the customers visiting any US property.

01 Append

Draw a polygon around a property to identify the behavioral segment of every visitor.

02 Analyze

Rank the top customer types visiting a location. Then match retailers based on online and offline activities of visitors.

03 Activate

Demonstrate visitor brand affinity to close deals. Activate marketing campaigns to drive target segments to your location.

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