“Placer.ai is a convenient way for me to conduct initial research of the property and area with a few clicks, which lets me look at more properties than I could have before. Overall, Placer has shortened my initial review from weeks to hours, and that’s an incredible return on my time.”

~ Nam Cho, Investor

The Challenge

Looking for a Starbucks NN location as a 1031 exchange investment

Nam Cho, an investor with DU Real Estate, was in the market for a NN single-tenant real estate deal, and was specifically interested in a newer Starbucks acquisition. With a large rolodex of contacts in the brokerage space, Nam received a significant number of prospective stores (over 50 deals, spanning states from Michigan to North Carolina and many others) for purchases from brokers. He quickly ran into a few issues common to investors that invest as broadly as Nam:
1. Limited time and bandwidth to travel to and evaluate each location.
2. Limited knowledge of the local markets.

In short, Nam needed a faster, more efficient way to understand store performance, or nearby retailers if it was a new build, and overall market characteristics, all while preserving his ability to screen a large number of deals. He describes that “brokers bring me a lot of deals, so I need to have some kind of a quick tool to know whether to keep it or pass it.”

‍The Solution‍

Using Placer as the Local Guide on Retail Performance

A Placer client for approximately 6 months, Nam had benefited from Placer’s training and was already adept at using the platform when he set out to buy the Starbucks property. When a new deal came across his desk, he had a playbook to evaluate each deal before having to address financial considerations and modeling.

Using sample deals to illustrate, here are the evaluation steps Nam took.

For existing stores, first look at foot traffic and rankings, then review the performance of surrounding tenants.

The first thing Nam did for each property was log into Placer and pull the property report for that location. With Placer, he could see foot traffic by hour and day of week, as well as learn about visitor frequency, length of stay, and how well that Starbucks ranked compared to other Starbucks in that region, an important measure of a location’s overall strength.

One property he evaluated was a Starbucks location under construction in Ponca City, Oklahoma. The property had a Hobby Lobby and Dollar General, while the Starbucks was an outparcel location being built. Because the Starbucks property was still under construction, Nam turned to the other tenants to view performance and overall strength of the center.

Learn more about Tenants Overview

* Please note:  all evaluation criteria and investment decisions were made according to his investment strategy, which may not match the strategy of others reading this case study.

What he found allowed him to reject the deal in short order. Quite simply, the surrounding retail was not well ranked compared to other locations in the state and nationally, both in terms of overall visits and even visits / sq ft, a measure that allows for apples to apples comparisons.

If the store and nearby retail look good, dive further into performance with more advanced Placer analysis, including evaluating nearby traffic and the amount of correlation with co-tenants.
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Nam ultimately found a new construction property with strong nearby rankings, settling on one in Michigan. It was surrounded by a Chick-fil-A (top 80% nationally), Meijer grocery store (top 95% nationally), and Panera Bread (top 60% in the state). As he said on our call, “Chick-fil-A, we assume, always does well in terms of traffic, but seeing these numbers was a positive sign for us and helped reaffirm how we felt about the location.”

TRAFFIC ANALYSIS
Digging into things further, he asked his customer success manager, Dana, to do a traffic analysis of the street in front of the store, which showed 12M+ impressions in the preceding 12 months, while another traffic report showed an average of 33k cars / day traversed the location, which was a strong amount of traffic.

Learn more about Vehicle Traffic Volume

CHICK-FIL-A CO-TENANCY CORRELATION
Because the Starbucks would be located in the same parking lot as the Chick-fil-A, Nam also asked Dana to run a nearby location correlation analysis, evaluating all instances of Starbucks and Chick-fil-A co-tenancy in the U.S. to see how they perform when they’re within 1km of each other.

Dana had Placer’s Solutions Engineering team run the analysis and found that the Pearson correlation coefficient between the visits metrics was only 0.275, meaning they are commonly co-located, but there is little correlation/causation between either location and little impact of foot traffic on each other. While it would have been nice to see something stronger, Nam took comfort in the fact that 1) Chick-fil-A wouldn’t hurt the Starbucks, and 2) it would draw a large amount of traffic near his location.

‍The Outcome

SUCCESS: a new Starbucks, with 25% more deals in the funnel and initial diligence taking 4% of the previous time

Using Placer data and reports, Nam was able to settle on a new Starbucks location in Michigan, confident that his decision was well-researched and understood. One could imagine his surprise, and feeling of vindication, when he recently received notification from the city that there was a proposal for medical office space nearby, which would only drive more business to his location.

Indeed, Placer allowed Nam to vet a new deal in ways he couldn’t do previously:
1. He could vet more deals (50 off market deals) than before (30 to 40), an increase of at least 25%, giving greater exposure and potential for him to choose only the “best” deals

2. He could understand the performance of a market holistically, as well as the performance of a store and of nearby retailers, and

3. He could do it in a few hours per deal instead of 2 weeks for each deal (4% of the time it took previously)

Looking forward to future deals with Placer, we can’t help but share his enthusiasm.

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