JD’s Zu Chongzhi opens data treasure trove for offline retailers

Online retailer JD is sharing its big data analysis capabilities with offline retailers.

The firm’s new retail-as-a-service platform is designed to help offline retailers with every step of the retail process, from choosing optimal locations for new stores to deciding on the assortment of merchandise to sell, as well as other store operations and marketing efforts.

The service – labelled “Zu Chongzhi” after a Chinese mathematician – leverages big data from both JD’s online platforms and the partner’s offline data to assist offline retail decision making. Retailers of any size, including those without the resources to hire thousands of engineers, are expected to benefit from the technology.

Suggestions for store locations, for example, are based on factors such as surrounding businesses and amenities, transport links, and local consumption trends, as well as detailed demographics for the surrounding area. In-store IoT devices provide information such as heat maps showing where customers spend the most time. The platform can also help improve product placement and shelving solutions, resulting in increased sales.

The platform is already being used by five brands across China, including furniture retailer QM, which used JD’s data to understand customer demographics in the area surrounding one of its outlets in Beijing. In order to boost the store’s customer entries, JD recommended the addition of 3000 high-selling, non-furniture SKUs to QM’s store. The addition of these products – not necessarily in line with QM’s main business but aligned with the needs of consumers – helped the store increase traffic with 30 per cent more customers entering the store than previously. More than 80 per cent of the new products generated sales in the store.

JD big data and smart supply chain president Jian Pei said the Zu Chongzhi platform shows the value JD can bring to offline retail partners through its technology.

“JD is well-known as a leader in online retail, while its rich big-data pool has already begun to transform the offline retail business. In the future, we look forward to working with more leading brands across China, and the world, to build out the future of retail.”

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