Application of artificial intelligence in new retail industry

With the rapid development of the Internet, traditional offline retail channels have begun to show signs of sluggish development. China's retail industry is in urgent need of a "booster" at this moment. The development of AI (artificial intelligence) technology may become one of the best solutions for the future development of the retail industry.

AI technology can change the form of collection, analysis and value application of retail goods and consumer data, accelerate the optimization of the ring structure of "people, goods, and stores" in the retail industry, thereby Reconstruct consumer relationships and stimulate consumer demand.

At present, "AI retail" is still in the exploratory stage. As the level of digital infrastructure of retail enterprises improves, AI technology will bring greater imagination to the intelligent reform of retail enterprises. space to boost the overall value growth of the industry.

NO.1 Grab-and-go unmanned supermarkets

In many cities in my country, unmanned supermarkets have taken root and are distributed in some popular business districts or commercial plazas around. Compared with traditional supermarkets, unmanned supermarkets do not need to be equipped with tally, cashier and other personnel, and the labor cost investment is almost zero. Consumers only need to use mobile payment methods to pay, and even take and go, which is very convenient. .

Behind convenience is the support of technological power. It is reported that unmanned supermarkets use a variety of recognition technologies, including biometric technologies such as facial recognition and intelligent recognition technologies such as machine recognition. Products in unmanned supermarkets have barcodes or RFID tags, which can provide consumers with a convenient checkout experience. At the same time, biometric technologies such as facial recognition can not only provide security for unmanned supermarkets, but can also become a new payment method.

In addition to being reflected in identification, artificial intelligence technology is also used in the collection and analysis of operational data in unmanned supermarkets. By analyzing user data with the help of artificial intelligence technology, we can quickly and promptly understand the sales situation of products and customer preferences, thereby improving procurement accuracy, increasing actual operating profits, and providing consumers with better consumer services.

NO.2 Unmanned distribution improves efficiency

Unmanned vehicles, drones, unmanned warehouses, unmanned stations, delivery robots and other "unmanned vehicles" "Human Technology" is becoming the new favorite of e-commerce, takeout, and logistics. With the reconstruction of new technologies, the lifestyle of "lowering down to place orders and raising head up to receive express delivery" has become possible.

Drones solve the last mile of distribution in remote mountainous areas, unmanned vehicles solve the last mile of urban distribution, and distribution robots go deep into park buildings to match different solutions for batch operations according to different environments. Delivery, improve distribution efficiency... This is the practice of smart logistics after moving out of unmanned warehouses, and it is also the unmanned distribution that can be achieved at this stage. The ultimate goal of unmanned distribution is to transform the traditional logistics system architecture and completely realize wisdom. Unmanned operation under logistics.

NO.3 The future of intelligent customer service is promising

Benefiting from the continuous development of technologies such as AI and cloud computing, intelligent customer service systems represented by natural language processing technology are in The applications in retail enterprises are constantly increasing, covering the entire process of pre-sales, sales and after-sales.

The 24/7 service can efficiently and high-quality meet consumers’ needs for product consultation, self-service shopping, order inquiry, logistics tracking, automatic returns and exchanges, etc., and improve consumer satisfaction. , improve the store inquiry conversion rate and save customer service labor costs by more than 50%.

On this basis, the intelligent customer service system can also collect consumer information tags, gain insight into user behavior, and provide data support for precision marketing, intelligent operations and other links. In addition, with the continuous development of voice interaction technology, more and more consumer interactions are conducted through voice, and service scenarios such as voice robots and intelligent outbound calls are gradually enriched.

NO.4 Consumer Identification Analysis

Traditional offline retail scenarios lack effective means of collecting and analyzing consumer information. In addition to transaction data, the value of consumer dimensional fine data, shopping process data and data integration analysis has not been tapped. Relying on machine vision technology, consumers are the main identification objects, and information such as faces, movements, and trajectories are collected through cameras, supplemented by identification and analysis of product image information, which can help retail companies integrate "people, goods, and places" data to form a complete User portraits and consumer insights.

In addition, virtual try-on/makeup, a visual solution for consumers, is gradually being implemented through mobile APPs or offline smart large screens, providing consumers with customized product display effects and saving brands trial costs. Reduce packaging costs, expand the channels for products to reach consumers, and optimize consumer shopping experience, thereby effectively increasing conversion rates and reducing brand owner costs.

In addition, compared with e-commerce, offline retail stores lack necessary information acquisition methods for consumer behavior insights. Smart cameras can now be used as information collection portals to collect consumers’ faces, facial expressions, Clothing, body posture, hairstyle and other information can realize the whole-process perception of consumers in offline retail scenarios.

Currently, affected by factors such as the concentration of offline retail scenes and the foundation of IT construction, vision-based consumer behavior insight solutions have been implemented experimentally in retail formats such as 4S stores, home appliance 3C stores, and large commercial real estate. In the future, with favorable factors such as computing power upgrades, reduced algorithm costs brought about by technological development, and increased market demand, the scale of vision-based consumer behavior insight solutions will gradually increase.

NO.5 Payment method upgrade

Some merchants use automatic settlement to reduce store labor costs. For example, RFID technology is used to affix RFID tags to goods, and the RFID tag information of the goods is identified through the intelligent settlement channel. After the identification is completed, the mobile phone system automatically deducts the payment for the goods and completes the payment. After the settlement is completed, you can open the door and leave the store. In addition, image recognition technology can also be used to directly identify the price information of the product, eliminating the cost of label production and shortening the waiting time for product identification.

Conclusion·

Generally speaking, to improve the implementation effect of the "AI retail" solution, we need to rely on massive data to optimize the algorithm and polish the program logic during the actual implementation process, so as to " Solve real needs, truly solve needs.” Represented by retail giants, they are vigorously promoting the construction of the retail technology ecosystem and investing more and more heavily in AI. Finally, it is worth noting that in order to meet the needs of retail enterprises for intelligent transformation, cost reduction and efficiency improvement, emerging technologies such as the Internet of Things and 5G can, on the one hand, assist AI solutions and achieve win-win results, and on the other hand, project implementation experience and algorithm advantages And ecosystem construction is still the core of AI development competitiveness.

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