Method, device and storage medium for realizing agent product marketing based on RPA, AI and LLM

By analyzing potential customer data through RPA, AI, and LLM intelligent agents, customer mining and maintenance are automated, solving the problem of low efficiency in existing technologies and achieving efficient and accurate customer cooperation management.

CN121961687BActive Publication Date: 2026-07-24BEIJING BENYING NETWORK TECH CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
BEIJING BENYING NETWORK TECH CO LTD
Filing Date
2025-12-19
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

In existing technologies, customer acquisition and maintenance processes rely on manual operation, which is inefficient, especially when there are many potential customers. It is time-consuming and labor-intensive, and it is difficult to efficiently identify high-value customers and accurately judge cooperation intentions.

Method used

By employing an intelligent agent based on RPA, AI, and LLM, the system analyzes trade-related data of potential customers, extracts key characteristics of business cooperation, assesses the value of cooperation, generates personalized product promotion content, and identifies customer feedback intentions, thereby achieving automated customer discovery and maintenance.

Benefits of technology

It improves the efficiency of customer acquisition and maintenance, accurately identifies high-value customers, reduces labor costs, ensures customer quality, increases the success rate of cooperation, and avoids the loss of potential customers.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a product marketing method and device based on robot process automation (RPA), artificial intelligence (AI) and large language model (LLM), an equipment and a storage medium. The product marketing method comprises the following steps: extracting key features related to business cooperation from trade-related data of each potential customer, and determining the cooperation value of each potential customer based on the key features, wherein the key features include product order quantity, transaction amount and / or import and export quantity; taking the potential customer whose cooperation value meets the requirement as a to-be-mined customer, and generating product promotion content matched with each to-be-mined customer; sending the product promotion content to the corresponding to-be-mined customer; and identifying the feedback content of the to-be-mined customer about the product promotion content to determine the cooperation intention. Through the above technical solution, the problem of low efficiency of manual follow-up of potential customers is solved, and the follow-up efficiency and cooperation success rate of potential customers are effectively improved.
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