The Current #5
by Hunter WorlandMay 16, 2024
As a private company, Shein does not disclose its financials. Perhaps the best indication of its scale didn’t come from a leaked P&L or report, but a slip of tongue. In an interview earlier this year, the CEO of a Shein retail partner said, with a bit of braggadocio, that the Chinese retailer “does a lot more than $30b” in annual revenue. Taken seriously, the estimation suggests Shein’s scale rivals Inditex, owner of Zara and largest publicly traded apparel retailer – a colossal feat for a company twenty-three years younger.
Americans (myself included) have often mistakenly assumed Shein is an anglicization of a Chinese name; Shein is rather a shortening of ‘She Inside,’ the company’s original name (Wayback Machine, Sheinside.com, March 2012)
The rise of Shein is a success story in an otherwise unforgiving retail ecosystem. Last month, Macy's announced the closure of 150 stores in a strategic pivot to luxury sales. Farfetch, the luxury e-commerce platform once valued at $25b, was acquired by Coupang in February for a mere $500mm. Outdoor Voices, previously a darling of direct-to-consumer brands, abruptly closed all its brick-and-mortar stores in March – a surprise to even its employees. Meanwhile, public market investors continue to discount brands like Warby Parker and Allbirds (the latter, as of writing, is valued at a modest .5x NTM revenue[1]).
How can merchants translate the success of Shein into their own business – and how commerce enablement software can support that translation – first requires answering a more fundamental question. What do consumers value about Shein in the first place? To uncover relative value, a panel of adult consumers in the United States familiar with Shein and Zara compared the two across purchasing criteria:
The value consumers identify underlie, by my account, Shein’s two greatest superpowers:
Low-batch manufacturing base: Shein leverages China’s basis of small and medium sized manufacturers not just for low-cost production but impossibly low minimum order quantity batches. That manufacturing basis enables an inventory agility and velocity that makes incumbents look outdated
Large-scale automated test and re-order (LATR) model[2]: Likened to Fordism or the Toyota Just-in-Time model, Shein has pioneered a new manufacturing model that continually optimizes production based on real-time data from the open web. The system scrapes social platforms and competitor sites to interpret trends, tests consumer demand with a low-batch order, scales up and down production based on product launch sales, and reiterates. LATR, the Darwinian mechanism behind the 6,000 SKUs Shein adds every day, represents the evolution beyond fast-fashion to what some commentator have called ‘real-time fashion’
The disruption of Shein and other real-time retailers presents an opportunity for the commerce enablement ecosystem. Examples include Raspberry AI who leverage custom trained models to shorten design schedule and increase sell-through rates, Syrup who optimize inventory allocation, replenishment, and buying to improve full-price sell-through without stockouts, and Portless who fulfill e-commerce orders directly from China, improving merchant shipping costs, cashflow, and inventory risk.
Reach out to hworland@nea.com to continue the conversation.
Notes and Sources
[1] Valuation data accessed via CapIQ
[2] More reading on Shein’s Latr system: Rest of World, Guardian, McMillan Doolitte
The consumer survey was conducted among a representative sample of 150 adults aged 18 to 30 living in the United States. The survey was fielded using the Pollfish platform during April 2024. Pollfish partners directly with app developers; the developer defines an appropriate and specific non-cash incentive in exchange for completed surveys that benefit real consumers but doesn’t motivate them to become career panelists. Please note that as with all survey research, there is a potential for sampling error and other forms of bias. Results should be interpreted as an indication of sentiment among the target population rather than an exact measure.
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