Welcome to the convenience store of the future

Huawei's Executive Editor-in-Chief Gavin Allen finds out how China’s Meiyijia uses AI to manage 35,000 stores – while still preserving convenience retail’s all-important human touch.

Dai Di, CIO of Meiyijia

Dai Di: Meiyijia has developed rapidly, expanding by more than 4,000 stores every year. That presents complex challenges for store operations and logistics support. Many of our competitors in China work with partners to cover a specific region, but we provide services under a single platform, with an integrated operational network across the whole country. It’s a huge task to ensure every store provides the same level of service quality.

Gavin Allen: How is Meiyijia using smart retail technologies to personalize customer experience and improve operational efficiency?

Dai Di: We have applied intelligent technologies extensively, deploying IoT devices in stores to collect data and then leveraging cloud computing to help stores diagnose their operational status, delivering better services to consumers. We also leverage supply chain data to forecast store demands, calculating inventory levels, or anticipating the logistics support required to meet the needs of the next wave of store consumers. HQ assesses this information to plan marketing activities together with our partners and set reasonable prices.

Gavin Allen: So, data analytics plays a key role in shaping product selection and inventory management?

Dai Di: Data is very important to us. In retail, the profit margin is low, so we need to leverage data for precise analysis and to maintain good operational efficiency. Building a unified data platform was a critical part of our cooperation with Huawei, which is very strong in telecommunications and data analytics. We have to gather massive amounts of data in order to agilely respond to service demands. We have also established an IoT platform, connecting all the IoT devices from stores. By leveraging that, we developed AI algorithm services and other systems and platforms. Huawei assigned experts to help us deploy the basic technologies, addressed our specific business requirements and collaborated to co-create data-driven operations. For example, at peak hours, stores don't need part-time workers, because digital shop assistants can help consumers purchase goods or order food. The assistants can also answer even questions from non-Chinese shoppers.

Gavin Allen: What impact has the Huawei partnership had on your expansion and franchisees?

Dai Di: Franchisee store owners are the foundation of our business expansion and are really important to us. The priority for them is simplified store operations. Some stores run 24/7, so it's very challenging for the owner, with a lot of personal and professional daily duties.

Together with Huawei, we can precisely identify and schedule store tasks to lower the pressure on the owner. For example, goods can be received earlier or breakfast prepared in advance to meet peak customer demand at 7am, preparing goods for other sections later. In the evening, when perhaps the store owner has to pick up the kids from school, he can switch to the unmanned mode. The digital assistant helps look after the store. Consumer experience matters to Meiyijia, too. We can provide an app to help them participate in Meiyijia’s marketing activities. And in many stores in China, consumers can scan their face or touch their phone to pay, or even pay with their palm print. We’re interacting with consumers to help them have a profound and easy shopping experience with us.

Gavin Allen: The "AI Store Assistant" enhances operational efficiency, but how does Meiyijia preserve the "human touch" essential to convenience stores?

Dai Di: However advanced technologies are, convenience stores are part of the community. They’re not vending machines – consumers want a human touch and need to get emotional value. Meiyijia is an important member of this community. Stores usually open late so workers can go home, take a short rest and still come back to enjoy a hot meal and fast food. That can greatly improve customer stickiness. We also want to free up store managers to chat with consumers, and simultaneously improve self-service levels for consumers who want more privacy.

We’ve built leisure areas too, with music and warm ambient lighting – welcoming areas for friends to gather.

Gavin Allen: How is AI reshaping the industry, and what is Meiyijia’s core strategy in response?

Dai Di: Meiyijia has worked on AI since 2019, using data to improve logistics efficiency and control costs. It’s difficult for a single store manager to connect data and make the right decisions, but we have many stores constantly running, and that helps us find ways to improve operational efficiency and better serve our consumers. We also want to further reduce supply chain costs, maintaining a relatively stable level of traffic. AI is not optional for retail businesses. We must embrace it. No single person can quickly process complex information, but that is exactly where AI excels and humans can then provide assistance and enrich the customer experience. For example, behind an AI digital shop assistant is the wealth of experience accumulated by staff. We can record and apply this data, sharing successful experiences with more store managers. There are a lot of issues to deal with and we can use AI algorithms to make improvements.

We also need to deal with questions from potential franchisees, who are like new parents: there’s a lot of panic and concern. We can’t provide 24/7 instant help, but an AI store assistant can. For example, a new franchisee anticipating an early-morning rush might be concerned about preparing enough food in time to meet customer demand. They might want to know something basic, such as, “How long does it take to heat a tart?”

Gavin Allen: Have you learned from mistakes along the way?

Dai Di: When Meiyijia began to digitalize, there were a lot of doubts from our franchisees. “Why are you putting all these smart devices in my store?” they asked. They worried it would increase costs and there was a strong backlash. Some franchisees even terminated their partnership.

But we knew this was the strategic way forward. There would be a short-term cost, but not digitalizing would hinder development in the long run. We soldiered on. After a peaceful parting of ways with some partners, we started to attract new franchisees. Since then, smart technologies have been gradually integrated into all Meiyijia store operations and that data has helped us get to where we are today. Many other industry players are learning from Meiyijia, and curious to know how we maintain such rapid expansion. It’s data and then accumulated knowledge. More franchisees are willing to work with us and those partnerships create more knowledge. It's like a virtuous cycle.

Gavin Allen: So, your message to hesitant retailers is embrace technology now?

Dai Di: There’s no one-size-fits-all approach. At the beginning, it's difficult because you don't have many stores or data from which to extract value. You’re still relying on human experience. Actually, I don't suggest small businesses invest too much in innovation because that will affect capabilities. But there are some mature technologies. They can give those a shot. For example, in China, there’s very cheap, video-sensing technology to detect whether there are rats in the store because rats can destroy commodities. This can directly be adopted by retailers. But adjusting the shelf according to consumer demand may require more advanced technologies.

Gavin Allen: It’s about finding the tech that works for you?

Dai Di: Our experience suggests two criteria. First, look at the company’s value creation chain and find the technologies that can best help add value, balancing against the difficulty and cost of implementation and then adopting it as soon as possible. And second, technologies should always be used to address complex, high-value scenarios that humans find it difficult to complete. Prioritize finding the right tech for scenarios that occur frequently, or where solutions offer big returns.

Gavin Allen: What’s a challenge you’d still love technology to solve?

Dai Di: The Q&A accuracy for digital store assistants is, in many cases, still around 70%. It’s very challenging because you can never truly predict what consumers will ask. But many services demand precision to be effective. When consumers come to a convenience store, they may be in a rush, and want an efficient service. Research suggests they won't wait more than 20 seconds before going elsewhere. A 70% accuracy rate means a lot of needs can still be addressed and questions answered. It's impossible to achieve 100%, but we are gradually improving the accuracy.