Xingbianli

About Xingbianli

Xingbianli, operated by Ojiao Network Technology (Shanghai) Co., emerged in June 2017 as a key player in China's burgeoning "New Retail" sector. The company was founded by Michael Lv, the former COO of dianping.com and an ex-president at Meituan-Dianping, who brought significant experience from the O2O (online-to-offline) internet industry. The founding team also included veterans from major retail and internet companies like Lawson China and Alibaba, aiming to merge deep retail knowledge with a strong internet background.

The company's business model focused on providing instant and convenient consumption experiences, primarily targeting the white-collar demographic in urban centers. Xingbianli deployed a dual-pronged strategy: setting up unmanned, self-service snack shelves in office buildings and establishing smart, self-service convenience stores. The unmanned shelves offered a nearby,自助式 (zìzhùshì - self-service) option for immediate purchases, leveraging mobile internet and LBS location technology. Customers could use an app to complete their purchases via online payment. This was complemented by larger, intelligent convenience stores that offered a wider variety of products, including fresh food, coffee, and imported snacks, creating a comprehensive consumption ecosystem.

Xingbianli experienced rapid growth fueled by substantial venture capital funding. The company secured a significant angel round of over 100 million RMB (approx. $15 million USD) in September 2017, led by Lightspeed China Partners and backed by founders of Meituan-Dianping. This was quickly followed in November 2017 by a 380 million RMB (approx. $57.6 million USD) Series A1 round led by Sequoia Capital China. By June 2018, Alibaba's affiliate, Ant Financial, also made a strategic investment in the company. This capital influx enabled aggressive expansion, and within months, Xingbianli had deployed over 10,000 snack shelves across first and second-tier cities and opened multiple smart stores in Shanghai. The company utilized data analytics to inform product selection and store layout, aiming for a "thousand stores, a thousand faces" approach tailored to specific locations.