Faire

Faire is an online wholesale marketplace, founded in 2017 by four ex-Square engineers (Max Rhodes, Marcelo Cortes, Daniele Perito, and Jeff Kolovson), that connects independent retailers with independent brands and makers. Its two stories share one insight: in a market where both sides already existed offline, the way to spark liquidity was to remove the financial risk that stopped them transacting, and the data thrown off by every transaction then became the moat that let the network compound.

Cold Start: Buying the first order by absorbing the retailer's inventory risk

The problem. When Faire launched in 2017, wholesale ran on trade shows and sales reps, and the marketplace faced the classic chicken-and-egg deadlock: without retailers ordering, brands had no reason to list, and without brands, retailers had nothing to browse. The deeper block was financial, not just a missing side. A small boutique with limited cash and shelf space would not gamble $2,000 on candles from an unknown maker, because unsold stock is dead capital, so buyers froze and neither side moved first.

The approach. Rather than seed a missing side, Faire attacked the risk directly. In its first year it introduced net-60 payment terms (buy now, pay 60 days later, after the goods have had time to sell) plus free returns on opening orders, so a retailer could stock a new brand, try it for two months, return whatever did not move, and never pay for unsold inventory. This converted the buyer's decision from a risky bet into a near-free trial, manufacturing demand-side liquidity that pulled supply-starved makers onto the platform.

How it solved it. The unlock was immediate: within three months of launching net-60 in late 2017, monthly gross merchandise value jumped from roughly $100K to about $1 million. The offer was initially too generous (by January 2018 returns and defaults were unsustainable), so Faire added credit limits and a ranking system for wholesalers and products, which cut return rates by about 75% within six months while keeping the risk-removal that had ignited the market.

Network Effect: Turning transaction data into a flywheel and a moat

The problem. Kickstarting liquidity by extending credit and eating return losses is expensive, and a marketplace that only subsidizes both sides forever has no durable advantage. Faire needed the early liquidity to compound into something a well-funded copycat could not simply replicate, and it needed the costly financing offer to get cheaper and safer over time rather than bleed indefinitely.

The approach. Faire let the two-sided flywheel turn (more retailers made it more attractive to brands, more brands meant more selection, more selection drew more retailers) while treating every order as proprietary data. Who buys what, which products sell through, and who pays on time fed credit-underwriting and merchandising models that no offline trade show or new entrant could match, so the same data that powered recommendations also let Faire extend net-60 and free returns more precisely and cheaply.

How it solved it. The network scaled to over 300,000 retailers and more than 40,000 brands across 80 countries, and by 2021 Faire reached a $12.4B valuation on a $400M Series G. The flywheel's health shows in the numbers Faire later reported: net dollar retention above 110%, driven specifically by retailers expanding the number of brands they buy from on the platform, alongside eight straight quarters of GMV growth toward roughly $3B in 2025. (The generosity remained costly: a November 2025 tender repriced Faire to about $5.2B, a reminder that risk-absorption ignites a network but must eventually tighten into sustainable unit economics.)