Faire: A Retail Revolution
How Faire is transforming local retail by bringing ML to every corner
Preface
Faire recently announced that it raised an additional $150m to hit a $1 billion valuation. As a wholesale marketplace for local retailers and makers, it cuts against the prevailing narrative that Amazon and e-commerce will eventually replace physical retail.
I believe Faire represents a revolution in local retail in the same way Walmart transformed retailing across the US.
For those unfamiliar with Faire, my goal is to explain why I think Faire has been able to build a successful business around local retail in spite of the competition from Amazon and e-commerce.
For those who already know the basics of Faire, I want to show how the company is poised to transform local retail by unlocking insights for every retailer from its growing machine learning engine. I conclude with two recommendations for accelerating Faire’s advantage in retail. (Feel free to skip ahead to the section titled Retail Machine Learning if this is you.)
TL;DR
Faire has a vision that local, physical retail stores still hold a powerful distribution strength, especially when paired with a much larger selection of inventory and easy risk-free ways to test new products. The company scaled its marketplace with an incredibly compelling offer of free returns on any unsold inventory and a cash flow boost (Net 60 payment terms).
On the back of this growth, Faire is creating an insurmountable moat by making product recommendations through its growing retail machine learning model. Better recommendations lead to more sales which lead to better recommendations in a compounding growth loop.
I finish with two recommendations for Faire:
- Build or acquire a retail POS system to fill the biggest gap in its retail dataset.
- Add market insights and product recommendations for makers to kick off another growth loop for makers.
When all is said and done, Faire will have transformed the way small, local retailers do business and captured a massive share of total retail sales.
Amazon vs Local Retail — How Faire Competes
Max admitted that one of his concerns in starting Faire was the threat of Amazon — so why has Faire found success?
There’s no question that e-commerce’s share of retail sales has been steadily growing. But what’s under-discussed is that e-commerce has only now cracked 10% of total US retail sales.
Amazon has been able to eat away at physical retail sales by aggregating enough consumer demand such that it is able to offer the widest variety of goods, at the cheapest price, and with the best delivery experience. However, Amazon only has that edge in one place — online.
Faire’s calculation is two fold:
- Physical retail has certain distributional advantages that cannot be challenged by Amazon
- The unlimited SKU selection of Amazon is beat by algorithmically-aided curation and vast product selection through supplier aggregation.
In short, Faire’s bet is that a great selection of the right products in the right retail location is an advantage that can win against Amazon’s e-commerce model.
Faire believes that local retailers’ competitive advantage is in physical distribution — a store in a desirable location, and an amazing, curated shopping experience — two attributes that Amazon’s online model definitionally cannot compete with.
A 2019 AT Kearney study on Gen Z attitudes towards retail found that 73% of Gen Zers liked to discover new products in stores and an astounding 81% of Gen Zers preferred to purchase in-store.
Furthermore, 74% of shoppers felt that it was extremely or moderately important to have “a well curated store experience focused on a limited number of products” [emphasis added].
Amazon’s monolithic nature actually works against it because a single online storefront viewed by millions can never match the diversity, curation, or creativity of thousands of individual stores.
Furthermore, by providing access to thousands of makers on its platform, Faire has given local retailers a powerful tool to mitigate one of the biggest limitations of retail — a limited inventory of products. Faire lets every local retailer emulate the vast SKU selection and sourcing of an online e-commerce store through sourcing, standardized deals, return handling, payments, etc.
Retailers are limited by physical space in stores, but now they functionally have the inventory and supplier connections of all of Faire’s marketplace rather than their own individual businesses.
An Offer Retailers Can’t Refuse — Test New Products Without Risk
Faire built out its network of retailers and makers with a simple, but extremely compelling product offer.
Faire’s first key feature is to offer free returns of any unsold inventory to retailers. This achieves two important things:
- Free returns neuter the key advantage of physical trade shows for finding new products by allowing retailers to touch and feel the physical products.
- Free returns of unsold inventory changes the risk equation for retailers who typically are extremely cash constrained and for whom one bad “bet” on a new product can be an existential crisis.
Then by adding favorable Net 60 payment terms, Faire created an irresistible product for retailers by removing nearly all financial costs and risks from offering new products in their stores. On the back of this extremely compelling feature set, Faire hit initial product market fit with retailers and has grown rapidly from $1m in sales per month to $1m in sales per day from the beginning of 2018 to today.
But Faire has actually tapped into a much deeper vein of opportunity, and I suspect the most recent raise is a massive bet on this future business.
Retail Machine Learning — Faire Becomes More than a Marketplace
Where the most interesting future opportunity is, and the reason I think Faire is much more exciting than “just a marketplace”, is that Faire is helping retailers make better product decisions.
Faire is making smart suggestions to retailers by recommending specific makers and products to retailers to reduce the risk of a “dud”. As the company scales, Faire’s platform gives it a privileged view of the market and its product recommendations will continue to grow more accurate and powerful.
Imagine how valuable this would be to a retailer — “Based on your location and our sales data, stock this dinnerware set and you will likely drive an additional $5,000-$8,000 in revenue next month.”
This creates a massive moat over time through the virtuous cycle of better product recommendations driving more sales to retailers which will drive retailers to order more products through Faire which will ultimately drive even better recommendations.
No other player will be able to provide the same insight to retailers.
Expect retailers to increasingly source their products from Faire and even for retailers to pressure their current makers to list their products on Faire for both insights and logistical ease.
One could even imagine that local retail stores eventually become “plug and play” through Faire — simply open up a store in a desirable location, and Faire will provide you with a complete set of recommended inventory to maximize revenues. (Faire could even be well positioned to open up its own stores in the future — creating the indie equivalent of the Amazon stores which are stocked with guaranteed hits.)
This opportunity to become the essential tool for retailers in making profitable product decisions is ultimately why Faire has such a massive growth opportunity ahead of it.
Faire has natural growth loops and moats that will trend towards owning an increasing cut of all retail sales.
By sitting as a layer behind the retailers, Faire is able to transform traditional low-tech retailers into businesses powered with machine learning without having to achieve Amazon-level scale.
Recommendations for Faire
1. Filling in the Gaps — Pushing into Retail POS
If Faire’s long-term moat is built on product recommendations to retailers, there’s one big glaring hole in the company’s retail dataset: non-Faire sales.
Even with its own set of retailers, Faire products will only be a portion of each store’s sales. Being able to see a detailed, complete set of all of a retail store’s sales would be a step change in the completeness of Faire’s dataset and the quality of its product recommendations.
For example, Faire could see how different products influence each other’s sales.
Are sales down for a Faire product because they’re being cannibalized by a new product addition?
Is there a sweet spot in terms of how much of a clothing store’s product line is composed of sweaters?
All of these questions become much less speculative if Faire gets access to all of a store’s sales, not just the slice of sales that are Faire products.
As an additional benefit, Faire would also get an excellent lead list of other makers that it should add to its platform.
The best possible option would be for Faire to get access to the retail point of sale system itself, most likely through an acquisition.
Building an inventory system or POS product is an option as well, but there are already tons of POS options for SMBs. It’s very likely that some of them are getting squeezed by Square and Clover, so Faire should explore if any of the smaller players are possible acquisition targets. The POS systems that have strengths in inventory management like Shopkeep or Bindo may be particularly attractive for an even more seamless retailer order experience.
2. Creating an Efficient Market — Adding a Maker Growth Loop
One way to think about Faire is that the company is successful when it can accurately and quickly translate consumer demand through its “supply chain” of retail locations and makers.
Because Faire doesn’t actually manufacture any of the items itself, Faire has to rely on its entire collection of makers to match their own supply of products with retailer demand.
The retail market is likely inefficient today, but Faire should be perfectly positioned to increase market efficiency and thereby increase total marketplace sales while capturing a greater share.
Imagine that there is a massive demand for knit socks one season. Faire’s retailers are demanding it, but its makers have underestimated the trend. As the makers sell out, the end result is that there would be less sales on the Faire marketplace unless the company can quickly find, vet, and onboard new makers — an undesirable outcome given Faire is quite selective with its makers.
Faire has the opportunity to address this in two unique ways.
- Sales insights and product recommendations — Faire can predict the early signs of demand and relay that back to the makers, nudging them to increase or decrease their production. These recommendations could range from a suggested trending color to an entirely new product line.
- Surge pricing for makers — For the first time, makers can get timely information that demand is higher than anticipated and respond by pricing their products at a premium.
The value to makers is immense.
Much like the growth loop on the retailer side, these market insights and product recommendations to makers would create a highly valuable and defensible moat that would attract more and more makers to sell through Faire.
Conclusion
Every action that improves Faire’s recommendations to retailers and makers is a massive boon for its ecosystem and will only accelerate its flywheel.
In the same way Walmart revolutionized general stores, I predict that Faire is going to become the Walmart of local retail.
But instead of replacing the retail stores, Faire will equip thousands of individual retailers and makers with algorithmically optimized products and pricing.
P.S. I’m looking for new Growth opportunities.
Find me on Twitter @kelvinltse
Thanks to Ashley Dotterweich, Eric Wolfe, and Sriram Krishnan for reading drafts of this post and providing tons of helpful feedback.
