Initiating Coverage of Zozo, Japan’s Top Fashion E-Commerce Platform

We initiate coverage of Japanese apparel e-commerce platform Zozo 3092 with a fair value estimate of JPY 3,500 and a narrow economic moat rating. With its broad range of fashion brands and attractive customer base, as well as its extensive fashion fulfillment capabilities built over the past 20 years, we believe the company is well positioned to benefit from the growth in online penetration in fashion, driven by the shift in consumer habits and technological advancement in the next five years. We believe the shares are moderately undervalued because we have more confidence than the market in Zozo’s medium- to long-term growth.

We believe Zozo will be able to maintain its leadership position in the fashion e-commerce market through leveraging its network effect and intangible assets. Zozo differentiates itself from competitors with its over 8,000 fashion brands (closest competitor Rakuten Fashion has 2,800 brands and PayPay Mall has 1,100 brands) and its userbase of 9.5 million fashion-conscious young customers who visit the Zozotown platform specifically for fashion. The huge traffic on the platform generates a large amount of user data that contributes to building Zozotown’s advanced recommendation algorithm, leading to superior conversion rates of 14%-16% versus the industry average of 4%. Zozo can charge a much higher take rate of 20%-40% than the industry average of 7%-8.5%, because its fulfillment services include size measurement, photographing, storage, product picking and packing, shipping, and returns. Meanwhile, other e-commerce platforms in Japan tend to only provide an outlet for products and do not support the cumbersome day-to-day management of tenants’ shops—these capabilities are very difficult for any e-commerce platform to copy. We forecast Zozo’s market share in the general apparel e-commerce market to reach 27.6% in 2026, from 21.5% in 2021, as Zozo continues to grow its brand repertoire and improve its algorithm and personalized recommendations.