Innovation center series report – OSA special research From China Chain Operation Association
The following is the Innovation center series report – OSA special research From China Chain Operation Association recommended by recordtrend.com. And this article belongs to the classification: Electronic Commerce, research report, network marketing.
The digitization of retail store shelves is a typical representative. Through the use of mobile phone applications, shelf cameras, shop inspection robots and other media, as well as machine vision, image recognition algorithms and Internet of things, we can actively capture and record the commodity information on the shelves, digitize the image data and master the commodity dynamics in real time. At the same time, on the basis of shelf digitization, machine learning model is used to integrate, process and analyze the data, provide retailers with data insight services such as sales forecast and shortage forecast, help retailers understand the overall consumer demand, and promote the common business development of suppliers and retailers through zero supply collaboration. From the perspective of resources, automatic identification, statistics and analysis of data by machines are gradually replacing manual operations, which can free up time for employees to engage in more valuable work.
A very important content of zero time difference consumption is to promote digital transformation and establish an organizational structure and culture driven by science and technology, without boundaries and adapting to the era of zero time difference consumption. With the help of machine learning and deep learning, consumer labels no longer need to be generated manually, and the fineness and depth of label feature description have been greatly improved. Through the data analysis of consumer behavior, accurately locate consumer consumption level and obtain important information such as consumption preference. Push products that meet customers’ preferences through online shopping malls and mobile applications, fully integrate offline experience with online consumption, realize precision marketing and greatly improve the efficiency of retail. From customers and commodities to transaction and management, achieve automation, informatization, digitization and intelligence, improve customer experience, and promote the mining of enterprise’s own value.
The digitization of retail store shelves is a typical representative. Through the use of mobile phone applications, shelf cameras, shop inspection robots and other media, as well as machine vision, image recognition algorithms and Internet of things, we can actively capture and record the commodity information on the shelves, digitize the image data and master the commodity dynamics in real time. At the same time, on the basis of shelf digitization, machine learning model is used to integrate, process and analyze the data, provide retailers with data insight services such as sales forecast and shortage forecast, help retailers understand the overall consumer demand, and promote the common business development of suppliers and retailers through zero supply collaboration. From the perspective of resources, automatic identification, statistics and analysis of data by machines are gradually replacing manual operations, which can free up time for employees to engage in more valuable work. Zero time difference consumption and shelf digitization create unlimited possibilities for the retail industry.
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