Goodwill Hunting: Is That My Old T-Shirt You’re Wearing?
By David Lobaugh, President, August Partners, Inc. | July 2020
An industry friend recently told me a story about her son, getting ready to go to college this fall (hopefully). She wanted to take him shopping for a new wardrobe.
What 18-year-old male wouldn’t want his mom to take him shopping?
But not for the obvious reason, he demurred, saying that he didn’t want to spend a lot of her money on his clothes… that it didn’t make good economic sense. Instead, he opted to visit a Savers store to stock up on his BTS essentials. She told me that he went to Savers, came home, and put on a one-man fashion show of his thrift store finds.
Her son explains, “You know they’ve been worn, that they’ve been washed, that they will hold up.” He says their street-cred status is confirmed when someone asks him, “Where did you get that?”
Thrifting is a thing. Resale is a thing.
Goodwill hunting is a thing.
Here in Atlanta, a 17-year-old and an 18-year-old in our family have both been prowling the aisles of Goodwill stores, coming home with T’s and more on a regular basis. It’s hard to go wrong for five bucks.
They have explored several stores and know which ones have the best stuff. It’s a sport. It’s the thrill of the hunt.
And it can also be profitable.
One of their friends is buying and reselling her Goodwill (and other) finds on Instagram. Not just selling. Merchandising, curating, arranging finds into outfits, soliciting bids, accepting payment via Venmo, posting weekly updates… generating revenues.
I just now saw a t-shirt being bid-up to $18. Her “wholesale” was probably $3-$4. Margins are a thing.
Location Data is a BIG Thing.
You may have noticed the buzz around location data, aka “geofence” or “GPS” or “mobile” data. This genie-out-of-the-bottle technology has – over the past six years – changed the way we define trade areas, quantify shopper metrics, track shopping visits and visit share, conduct void analyses, evaluate acquisitions… and how we merchandise, lease and market our centers and stores.
No more best guesses. No more 3-5-7-mile radius or 10-minute drive-time demo tables. And no more equating market demographics with shopper demographics. What’s “out there” in the market is not necessarily what your center or store is drawing. Big difference.
Let’s get a sense of what location data can do by looking at findings from a pre-COVID-19 study. In this case, we isolated a Goodwill unit in a 300,000+ sq. ft. center, to see what we could see.
We saw the center trade area and we saw the store trade area. Same general geographic coverage, but the microgrid mapping – weighted by shopping frequencies – provides definition in a way that old school analysis can’t match.
The Goodwill store – whose TA is a subset of the center’s – reflects the frequency patterns of the property, but with considerably less heat. Over the years, we’ve seen that measuring visit frequency is a key metric in evaluating center and store performance.
The Goodwill unit in this center represents 9.3% of the property’s square footage and generates 8.5% of total center shopper visits (See table below), so on an index basis, that’s a 0.9 ratio (8.5 ÷ 9.3 = 0.9). By comparison, the regional fitness center indexes at 1.5; Texas Roadhouse at 6.3; Olive Garden at 3.5 and Red Lobster at 2.5.
Why are those ratios important? Because they help us quantify co-tenancy dynamics and merchandising strategies from a GLA allocation POV.
Shopper Data vs. Market Data
Our industry has traditionally relied on ambient market demographics to define center and store shopper demos. Location data has proven that’s not a valid approach. Looking at our case study again:
By appending such findings as shopping frequency patterns, average HH income and category spend data to shoppers’ “home” location demographics (down to block/neighborhood level) we can compare how center and store customer bases compare to the “market” – in this case (see above) defined by MSA characteristics.
Pertinent findings:
- The overall Shopping Frequency Index (SFI = unique sampling observations ÷ total shopper visits) for the center is 4.3, which is influenced by the presence of a robust fitness center plus a good set of national/regional F&B tenants. The Goodwill store is at 1.6 – a considerably lower level. If I were a head honcho at Goodwill, I’d be looking at how my store could take advantage of the center’s SFI performance and how well my store benefits from cross-patronage patterns. If I were a center head honcho, I’d be looking at how I could cross-promote Goodwill:
- Overall center shopper average annual HH income is $98,710. Goodwill shopper average HHI is $90,204. The salient finding here is that both center- and store-shoppers “outdraw” the MSA market HHI average ($85,618) – by 15.3% and 5.4% respectively. If I were the center head honcho, I would be using the center vs. MSA data in my leasing materials
- Likewise, the Goodwill store – comped against the MSA – is good for the current (and future) F&B tenants at this property: Goodwill store shoppers outspend their MSA comp counterparts by 19.3% in the dining out spend category. More fodder for leasing materials and presentations…
Are Goodwill and Savers and re-seller Instagrammers just isolated findings or are there broader trends at work?
Deloitte Report: “Alternate Apparel Business Models”
In a recent Deloitte Insights Report its team of authors profile a major retail trend entitled “Alternate Apparel Business Models.”
You guessed it. One of four alternate models they profile is Resale. As in Goodwill and Savers and Instagrammers. The others are Rental, Subscription and Flash Sales. Collectively, these four models have already passed $22 billion in annual revenues and are projected to hit $46 billion by 2023.
The report reveals that Subscription business revenues (companies like Rent the Runway, e.g.) grew by 18.1% from 2012 to 2019, compared to a 3.8% growth for total US retail during the same period. Estimated CAGR from 2016-2023 is 20%, according to Deloitte.
Rentals are projected at a 10.6% CAGR; Flash Sales at 12.4% and secondhand Resales at 15.6%.
Resale Retail. More is Less, so Less is More.
ThredUp’s “2020 Resale Report” (https://www.thredup.com/resale/) claims that resale and thrift will be bigger than fast fashion by 2029, hitting total revenues of $80 billion. The TU website cites sustainability sensitivity, positive feelings about buying secondhand clothes and the obvious desire to stretch budgets as the motivators fueling the trend.
The report notes that resale grew 25X faster than the retail sector as a whole, and it also points out that Kim Kardashian West wears vintage designer duds. Well, there you go!
Another colleague in Southern CA, tells me that her offspring are re-selling out of their garage and through apps like Vinted, Poshmark and OfferUp. Backyard omnichannel. We could take lessons.
Takeaways:
The best minds in our business will Wayne-Gretzky their way to where retail is going to be.
They will re-tenant vacancies with variations on the alternate apparel business models. They will embrace Instagrammers and other new-wave resale influencers – maybe by providing “market day” spaces and online links within their center websites.
They will monitor their centers and stores – month-in and month-out – using the latest location data tools to better understand visit trending, shopper profile shifts and co-tenancy dynamics. And along the way they will reinvent our industry.
My wife gave away that T.
I want it back.
Name your price.