CN-121981733-A - AI-based intelligent customer service operation analysis and humanized interaction method and system for electronic commerce

Abstract

The invention discloses an AI-based intelligent customer service operation analysis and humanized interaction method and system for electronic commerce, which can automatically count daily, monthly and quarterly receipts and profits of merchants, visually display the merchant by a chart, automatically identify burst money, remind goods replenishment, analyze difference comments and give improvement suggestions, output different care sentences to old people and young people through head portrait identification in late night period, generate individuation commend according to commodity colors and categories, and automatically push predicted arrival time after payment is completed. The invention realizes the integration of management, intelligent after-sales, personal care and user experience, and is suitable for various e-commerce platforms, malls and applets.

Inventors

• MENG XINYUE

Assignees

• 孟新越

Dates

Publication Date

20260505

Application Date

20260225

Claims (7)

1. 1. An AI-based intelligent customer service operation analysis and humanized interaction method for an electronic commerce is characterized by comprising the following steps: Store orders and transaction data are collected in real time, the daily, current month and current quarter revenues and profits are automatically counted, visual data in the form of charts are generated, the exploded commodities are automatically identified, replenishment is reminded, meanwhile, poor evaluation of users is analyzed, and improvement suggestions are pushed; in the late night period of 00:00-06:00, identifying age groups according to user head portraits, and outputting corresponding rest care sentences for different groups; according to the colors and categories of the commodities purchased by the user, automatically generating corresponding personalized commend speaking techniques; and after the payment of the user is completed, the predicted arrival time is automatically pushed immediately without manual inquiry of the user.
2. 2. The method of claim 1, wherein the business data is visually presented in a graph, bar chart, or chart form and automatically pushed to the merchant.
3. 3. The method of claim 1, wherein the system automatically identifies high-sales items and generates replenishment alerts, automatically analyzes the review content and outputs improvement advice.
4. 4. The method of claim 1, wherein the late night hours identify the elderly and young people from the head portrait using different mood care statements.
5. 5. The method of claim 1, wherein the personalized commend session is generated based on automatic matching of commodity colors, styles, categories.
6. 6. The method of claim 1, wherein the estimated time of arrival is automatically pushed without delay after the payment is successful.
7. 7. An AI-based e-commerce intelligent customer service system, comprising a data statistics module, a visualization module, an after-sales analysis module, a late night care module, a personalized evaluation module, and an automatic delivery notification module for performing the method of any of claims 1-6.

Description

AI-based intelligent customer service operation analysis and humanized interaction method and system for electronic commerce Technical Field Technical field: The invention relates to the technical field of artificial intelligent customer service, the technical field of electronic commerce data analysis and the intelligent interaction field, in particular to an AI intelligent customer service implementation method and system for integrating automatic statistics of operation data, data visualization, after-sale intelligent analysis, late night humanity care, personalized evaluation and automatic arrival time notification. Background At present, the traditional E-commerce customer service system can only realize basic functions such as simple question and answer, automatic reply and the like, and has the following obvious defects: 1. The method can not automatically count the today, month and quarter camp, profit and sales data for the merchant, and can not automatically generate a visual chart, so that the merchant needs manual accounting, and the efficiency is low and mistakes are easy to occur; 2. The method can not automatically identify the burst goods, intelligently remind the replenishment, automatically analyze the bad evaluation content and give out improvement suggestions; 3. the human care mechanism at late night period is lacking, and different people such as old people, young people and the like cannot be identified according to the head portraits of the users to carry out differential care; 4. the post-purchase evaluation speech is single, and individuation commend cannot be carried out according to the commodity color and the class; 5. The expected delivery time cannot be automatically pushed after payment is completed, and the user needs to manually inquire and experiences poorly. The prior art cannot integrate the functions, so the invention has obvious practical value and innovation significance. Disclosure of Invention 1. Object of the invention The AI intelligent customer service method and system integrated with the functions of operation data analysis, visual display, intelligent replenishment reminding, difference evaluation automatic analysis, late night personnel care, personalized evaluation and automatic delivery notification are provided, and the E-commerce operation efficiency and user experience are improved. 2. Technical proposal An AI-based intelligent customer service operation analysis and humanized interaction method for an electronic commerce comprises the following steps: 1. automatic statistics and visual display of business data Order data, transaction data and commodity data of the electronic store are collected in real time, and are automatically counted and output: today's revenue, this month's revenue, this quarter's revenue, profit data; The sales of all commodities are ranked, and the exploded commodities are automatically identified; Visual display is carried out in the forms of charts, graphs, bar graphs and the like; Automatically pushing the product to a merchant without manual accounting. 2. Smart after-market feedback and improvement advice Automatically analyzing user evaluation contents through an AI algorithm: identifying bad evaluation reasons, and intelligently pushing improvement suggestions; automatically reminding merchants of goods with higher sales volume to timely replenish the goods; and uniformly pushing the management condition, the after-sale problem and the improvement direction to a merchant. 3. Human care interactions during late night hours The late night period is set to be 00:00-06:00. When the user completes the purchase during this period: identifying age characteristics through the head portrait of the user, and distinguishing old people, young people and children; output to the elderly "stay up night, have a good rest for the body, breakfast"; outputting "early sleep, stay up night" to young people/children; realizing differentiation and humanization care. 4. Personalized evaluation based on commodity attributes After the user purchases, automatically generating commend a conversation according to the commodity color and the class: purchase black commodity, you really have eyes, black classical and see-proof; purchasing red commodity, namely' you have individuality, red is especially bright; Different commodities and different colors correspond to different evaluations, so that thousands of people and thousands of faces are realized. 5. Automatic push of estimated arrival time When the user finishes paying, the system directly and automatically pushes the predicted delivery time, The user does not need to manually click the query, and the operation flow is simplified. 3. System architecture (write-in protection scope is bigger) An AI-based e-commerce intelligent customer service system, comprising: Data acquisition and statistics module; a data visualization module; An after-sales analysis and replenishment reminding module; A time ide