Method for monitoring attention degree classification of chaussure products in sale terminal

Abstract

The invention discloses a method for monitoring the attention degree classification of shoe products at a point-of-sale terminal, which comprises the following steps: information is acquireed from a shoe rack, a shoe fitting area, and a POS system by arranging RFID devices in the shoe rack and the shoe fitting area and combining the POS system which is frequently seen at the point-of-sale terminal, and is transferred to a data analysis system in a real-time mode, the result is displayed on a screen of the data analysis system, and a point-of-sale terminal operator can analyze the information displayed on the data analysis system to obtain the attention degree condition of different shoe products. The method has quick information acquireion, can also judge the attention degree condition ofdifferent shoe products even if customers do not buy the shoes and the operator fails to acquire final sales data, and provides more reference data for the purchase of best-selling shoes by the point-of-sale terminal operator.

Description

Technical field: [0001] The present invention relates to a monitoring method, more specifically, relates to a method for monitoring (received) degree of attention of footwear products at sales terminals. Background technique: [0002] There are many kinds of shoes. According to the shoemaking materials, they can be divided into: leather shoes, cloth shoes, rubber shoes and plastic shoes, etc.; Because different people have different choices of shoes, this makes it difficult for sales terminal operators to grasp when purchasing shoes. It is risky to blindly choose shoes according to their own preferences. Once the shoes do not meet the public's vision, It will accumulate inventory and cause certain losses. Therefore, whether you can choose popular footwear products suitable for the public is very important to the profitability of the sales terminal. [0003] At present, sales terminal operators usually purchase a batch of different types of shoes for sale first, and then cou...

AI Technical Summary

Problems solved by technology

In this way, the analysis of sales data is somewhat lagging behind, and there is also a lack of understanding of some intermediate data, such as which shoes are more popular with customers in terms of color, style and material; Satisfied with its detailing and style; what other shoe customers are satisfied with its color, style, material, detailing and style, but are not satisfied with its specification or fit its size, etc. Intermediate data is unknown

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