Front-end warehouses spreading across communities and the adoption of Internet of Things (IoT) that support efficient fulfillment, expedited and cost-saving delivery enabled by insights gained through big data analysis and artificial intelligence, as well as precise product recommendations made by algorithm, these are just some of the technology elements behind Chinese online fresh produce delivery startup MissFresh that have helped the company threw a punch above its weight and outcompete a formidable rival, Alibaba-backed Hema, according to MissFresh’s founder Zeng Bin.
Zeng shared the above during a keynote speech at the WISE New Economy Conference 2019 held on November 26 in Beijing. WISE is the flagship annual event organized by Chinese tech media outlet 36Kr which just completed its IPO in the US. This year’s edition highlights new technologies and discusses the shift from disruption to integration in the traditional industries.
Founded in 2014, MissFresh is an e-commerce platform that offers online sales and deliveries of fresh produce. The company uses front-end warehouses, which are located next to customers’ communities and neighborhoods, to deliver more than 2,000 types of products including fruits, vegetables, meat, and dairy products within an hour. It has opened more than 1,500 front-end warehouses in over 20 cities in China.
MissFresh has more than 10 million monthly active users on its app during the third quarter of 2019, and it has topped other players with a market share of over 50% in China’s first-tier cities including Beijing, Shanghai, Guangzhou, and Shenzhen, while Alibaba’s Hema came in second with a 30% market share, reported by 36Kr citing data from industry tracker Trustdata.
Zeng said in his speech that MissFresh has become a technology-driven fresh produce retail and delivery platform, as the company has fully adopted big data, AI and IoT in its marketing, delivery, and supply chain.
He said that a regular user of MissFresh will place 50 to 60 orders on the platform in one year. The company will use algorithms to analyze orders from different customers and learn the behaviors of customers living close to one front-end warehouse and then load the warehouse with products that match the preferences of potential customers nearby.
AI will also make recommendations to MissFresh’s users when they are placing an order online and making automated decisions about marketing strategies and discounts accordingly.
MissFresh has enhanced its front-end warehouse and delivery system using big data. Zeng said the company has combined together data from itself, Tencent and third parties to analyze the locations of MissFresh’s most frequent users and the most purchased items. Then the company can build warehouses and offer various stock keeping units (SKUs) according to these insights.
AI and big data also contributed to order distribution and delivery by estimating time used during the process, so that the orders can be completed within the shortest period of time. The algorithm will also evaluate the capacity of warehouses and send notifications to users even before placing an order if the warehouse is too busy so their orders might be running late.
“Currently it takes an average of 36 minutes for MissFresh’s riders to deliver an order, and a rider can complete about 80 orders per day,” Zeng said.
He also mentioned that MissFresh has optimized its supply chain with AI by creating a smart restock system. An algorithm will forecast the sales in the coming weeks and implement different restock strategies according to warehouse location, weather, and preferences of the targeting customers.
For example, normally the warehouse will receive more orders on rainy days than on sunny days, but it was previously unknown how the number of orders will change with the weather. After adopting AI, the algorithm will come up with a detailed pattern that tracks order volume change with different weather conditions. AI-related technologies can ensure warehouses to remain sufficient stock for orders and prevent products from being sold out completely or left unsold.
The fresh produce e-commerce platform also customized its supply chain and create new SKUs based on data and patterns provided by AI. Zeng used an example that they once created a supply chain for a long gone beverage brand based on the needs of customers in Beijing, and the beverage has become a best-seller product after its relaunch. According to him, by offering unique SKUs inspired by AI’s analysis of customers’ needs, the frequency and stickiness to MissFresh will be greatly increased.
36Kr is KrASIA’s parent company.
