Market Optimization AI System

Abstract

We provide a market optimization system that utilizes generative AI to dramatically improve work efficiency by automating the creation of product descriptions, pricing, and product recommendations, which were previously done manually by sellers. [Solution] The market optimization AI system uses generative AI and ensemble learning to automatically generate product descriptions, optimize prices, and provide personalized product recommendations. Furthermore, it is offered as a cloud-based service on a subscription model, making it easy for sellers to use. Ensemble learning integrates multiple algorithms to improve the accuracy of data analysis.

Description

Technical Field

[0001] The present invention relates to a system for optimizing the processes of product registration, price setting, personalized recommendation, and advertisement generation in an online marketplace. In particular, it belongs to the technical field of providing functions such as automatic generation of product descriptions, price optimization, product recommendation based on purchaser behavior data, and improvement proposal functions for sellers, centered on generative AI technology using ensemble learning.

[0002] Furthermore, the present invention is a system that provides these functions via the cloud based on a subscription model, enabling sellers and platform operators to efficiently utilize the advanced functions of generative AI. This system is characterized by combining multiple data sets such as product data, purchaser preference data, price data, etc., and performing highly accurate analysis using ensemble learning.

Background Art

[0003] In conventional online marketplaces, when sellers offer products, they have to manually create product descriptions and set appropriate prices. This has been a time-consuming and labor-intensive task, especially for sellers handling a large number of products or those operating on a small scale. Also, regarding price setting of products, it has been difficult to respond to real-time market trends, and it has frequently occurred that appropriate prices cannot be set.

[0004] In conventional technologies, there were product recommendation systems and price optimization tools, but these tools operated individually and did not perform automatic generation of product descriptions or integrated analysis based on market trends. Therefore, there was a lack of a system that comprehensively supported the entire offering process, and sellers had to use each tool individually.

[0005] Furthermore, with the advancement of AI technology, it is becoming possible to optimize product descriptions and pricing, and automate product recommendations. However, implementing these technologies requires high costs and technical expertise, making them difficult to adopt, especially for small and medium-sized enterprises and individual sellers. Conventional AI-powered systems required dedicated development, and their maintenance also incurred significant costs.

[0006] Furthermore, conventional AI-based systems often relied on specific algorithms and were unable to cope with data variability and diverse factors. In particular, there were limitations when analyzing combinations of different datasets, making accurate prediction and optimization difficult. To solve this problem, it was necessary to introduce ensemble learning, which combines multiple algorithms, but this also faced significant technical hurdles.

[0007] Furthermore, there were few AI-based systems offered on a subscription model, resulting in significant costs and management burdens for sellers. While some attempts have been made to provide cloud-based generative AI, there has been a lack of readily available solutions that are both general-purpose and easily implemented by small and medium-sized sellers. [Prior art documents] [Patent Documents]

[0008] [Patent Document 1] Public Relations Issue No. 6665547

[0009] [Patent Document 2] Public Relations Issue No. 6444082 [Overview of the project] [Problems that the invention aims to solve]

[0010] Traditional online marketplaces required sellers to individually handle product description creation, pricing, and personalized product recommendations, which was time-consuming and labor-intensive. Furthermore, these tasks relied on the seller's subjectivity, leading to inconsistencies in product description quality and pricing accuracy. Even AI-powered systems often relied on a single algorithm, making it difficult to accurately analyze complex market data and diverse buyer behavior patterns.

[0011] In particular, the high cost and technical barriers to implementing AI made it impractical for small and medium-sized sellers to utilize generative AI technology. Traditional systems lacked adequate methods for providing AI technology in a user-friendly format, making it difficult to effectively utilize extensive data for price optimization and product recommendations. Furthermore, implementing these technologies individually required managing multiple systems simultaneously, increasing operational costs. [Means for solving the problem]

[0012] This invention provides a market optimization system that uses generative AI to automatically generate product descriptions, optimize prices, and provide personalized product recommendations to buyers in a single process. This system leverages ensemble learning and combines multiple algorithms to accurately analyze various data, such as market data and user behavior history. This overcomes the limitations of conventional AI systems that rely on a single algorithm, enabling accurate pricing and recommendations.

[0013] Furthermore, this invention is cloud-based and, through a subscription model, allows sellers to utilize the advanced features of the generative AI without incurring significant initial investment. Sellers simply input product data into the system, and the generative AI automatically generates product descriptions, provides pricing based on market trends, and offers personalized product recommendations. The system also features an automatic moderation function that detects inappropriate products and spam, ensuring the security of the entire platform. [Effects of the Invention]

[0014] The market optimization system utilizing generative AI according to the present invention can dramatically improve work efficiency by automating the creation of product descriptions, pricing, and product recommendations that were previously performed manually by sellers. This allows sellers to significantly reduce time and effort, and the highly accurate analysis by the generative AI enables attractive product descriptions and pricing for buyers. By utilizing ensemble learning, multiple algorithms are optimized, which has the effect of improving data accuracy.

[0015] Furthermore, because this invention optimizes prices based on real-time market data, it can flexibly respond to price fluctuations and supply-demand balances of competing products. This maximizes sales opportunities for products and enables sellers to earn fair profits. In addition, the personalized product recommendation function allows for highly accurate recommendations of relevant products to buyers, which is expected to improve purchase rates and customer satisfaction.

[0016] Because this system is cloud-based, a subscription model allows sellers and platform operators to use advanced generative AI technology at a low cost. This eliminates the need for high initial investment, making it easy for small and medium-sized businesses to implement. Furthermore, it features an automated moderation function, which helps maintain the overall health and security of the platform and automates the removal of inappropriate products and content.

[0017] By utilizing ensemble learning, advanced analysis combining diverse datasets and factors becomes possible, allowing for accurate capture of complex market trends and consumer behavior patterns that traditional single algorithms could not address. This is expected to improve the accuracy of pricing and product recommendations, thereby supporting business growth. [Brief explanation of the drawing]

[0018] [Figure 1]This is the overall system configuration diagram of the market optimization AI system according to the present invention. [Figure 2] This is a flowchart diagram of the market optimization AI system of the present invention.

Mode for Carrying Out the Invention

[0019] The market optimization AI system according to the present invention is a cloud-based system that uses generative AI to achieve automatic generation of product descriptions, price optimization, personalized product recommendations, advertisement generation, and automatic moderation. When a seller registers a product, the system automatically generates a product description based on the input product data, and a description text for conveying the details of the registered product to the buyer is created. This generative AI utilizes ensemble learning and combines multiple algorithms to generate a more accurate and optimal description text.

[0020] This system is operated by a cloud server, and the seller terminal, buyer terminal, and database are connected via a network. When a seller inputs product information, the data is processed by the generative AI module on the cloud server and stored in the database. The generative AI collates the stored data with market data collected in real time to optimize prices. In addition, the seller can confirm and modify the product description and price settings generated through the system, and can quickly publish the optimized product information to the market.

[0021] The personalized product recommendation module automatically recommends the most suitable products based on the buyer's past purchase history and browsing history. The generative AI analyzes the buyer's preference data and makes customized recommendations for individual buyers. Through this process, buyers can easily find products that meet their needs, which has the effect of increasing their willingness to purchase. Furthermore, the generative AI has an advertisement generation module that can automatically generate personalized advertisements based on the buyer's behavior history and preferences, and can launch effective advertising campaigns.

[0022] This system has a function to analyze market data and product sales data stored in a database on the cloud in real time. The generative AI predicts market trends and demand fluctuations based on this data and proposes to the seller the timing of price changes and inventory replenishment. Also, the automatic moderation function uses the generative AI to detect inappropriate products and spam behavior and notifies the platform operator and the seller. As a result, the reliability of the marketplace is improved and a safe trading environment is ensured.

[0023] The present invention is provided in a subscription format, and sellers and platform operators can use the AI functions provided on a cloud basis according to a subscription plan. A plurality of plans are prepared, and users can select an appropriate plan according to their business scale and needs. Plans with a monthly fee system or a usage-based billing system are provided, and flexible price settings are possible, so it is possible for small and medium-sized businesses to introduce the system with reduced initial investment.

[0024] This system is designed to always be able to utilize the latest generative AI technology, and since it is provided on a cloud basis, updates and maintenance are automatically performed. As a result, an environment is prepared in which sellers and platform operators can always use the latest AI technology without having technical expertise. Also, the system has high scalability and can flexibly respond to the expansion of the seller's business scale.

Example

[0025] As an example of the market optimization AI system of the present invention, an example of automating and optimizing the product listing process in an online marketplace will be described. This system aims to use generative AI to streamline the work when a seller registers a product and maximize sales opportunities.

[0026] When a seller enters product information, the system first uses a generative AI to automatically generate a product description. Based on the basic information provided by the seller, such as the product name, category, and features, the AI ​​utilizes natural language processing technology to create a detailed product description. This description is optimized to accurately convey the product's appeal to buyers and is designed to easily attract their interest. For example, when listing a "smartphone case," the generative AI automatically generates a description such as, "Highly durable and lightweight design, protects your smartphone from impacts."

[0027] Next, the system analyzes real-time market data and optimizes product pricing. The price optimization module considers factors such as competitor prices, supply and demand balance, and seasonal fluctuations, and proposes an optimal price calculated by the generating AI to the seller. This price is constantly adjusted based on fluctuating market conditions, and sellers can accept the proposed price with a single click. This allows sellers to list their products at a fair price without any hassle.

[0028] Once a product is released, the system analyzes buyer behavior data and provides personalized product recommendations. Based on the buyer's past purchase and browsing history, the generating AI recommends the most relevant products to each individual buyer. This recommendation feature makes it easy for buyers to find products that match their interests, increasing their purchase intent. For example, users who have previously purchased smartphone-related products will be given priority recommendations for smartphone cases and accessories.

[0029] Furthermore, the system incorporates an ad generation module, where a generation AI analyzes the buyer's preferences and behavioral history to automatically generate personalized ads. These ads are displayed to the buyer at the optimal time, maximizing their effectiveness. For example, ads for smartphone-related products are displayed as cross-sell items such as related accessories and screen protectors.

[0030] Furthermore, after a product is sold, the generating AI automatically analyzes buyer reviews and feedback, suggesting improvements to the seller. This allows sellers to revise their product descriptions and pricing, enabling them to relist their products on the market with optimal content for future listings. This review analysis feature helps improve product quality and optimize sales strategies, providing sellers with valuable feedback.

[0031] The entire system is cloud-based, allowing sellers to access it via API and utilize the various functions of the AI-generated content in real time. It's also offered on a subscription basis, allowing sellers to choose a plan that suits their business size and needs. For example, the basic plan provides automatic product description generation and price optimization, while the premium plan offers additional features such as personalized product recommendations and ad generation.

[0032] This implementation allows sellers to automate and optimize the entire process from product registration to sales promotion, reducing time and costs. Furthermore, the use of generative AI provides buyers with optimal product recommendations and personalized advertising, which is expected to improve conversion rates and encourage repeat purchases. For small and medium-sized sellers in particular, the cloud-based subscription system offers significant advantages, such as the ability to leverage advanced AI capabilities while minimizing initial investment. [Industrial applicability]

[0033] The market optimization AI system according to the present invention is widely applicable to companies operating online marketplaces and sellers selling products through e-commerce. By utilizing generative AI technology, a series of tasks such as automatic product description generation, pricing optimization, personalized recommendations, and advertisement generation can be automated, significantly reducing the burden on sellers and enabling efficient operations.

[0034] In particular, because this invention is cloud-based and available on a subscription basis, it does not require the high initial investment of developing an AI system in-house, as was the case with conventional methods, making it applicable to businesses of all sizes. This allows small and medium-sized enterprises and individual sellers to easily adopt advanced AI technology and strengthen their competitiveness. The subscription model also allows for flexible adjustment of service fees, so users can choose a plan that suits the size and growth of their business.

[0035] The system of this invention is applicable not only to online shopping and e-commerce, but to any industry that sells goods. For example, in situations where product descriptions and pricing play a crucial role, such as B2B marketplaces, auction sites, and crowdfunding platforms, applying this system can be expected to improve operational efficiency. Furthermore, in the advertising industry, utilizing the personalized ad generation function is expected to improve advertising effectiveness.

[0036] Furthermore, with advancements in AI technology, it becomes possible to analyze customer preferences and market trends in real time and automatically provide improvement suggestions to sellers, thereby accelerating corporate decision-making processes and supporting business growth. In addition, AI-powered automatic moderation functions can quickly detect and remove inappropriate products and content, improving the reliability and security of the entire online platform.

[0037] Thus, this invention is expected to have applications in a variety of industries, and will serve as an important technological foundation for improving operational efficiency and increasing sales, particularly for companies involved in online product sales and advertising. Furthermore, by providing AI technology on a subscription basis, it will be possible to easily allow a wide range of users to utilize the latest technology, and is expected to have the effect of promoting technological innovation across industries.

Claims

1. A market optimization system using generative AI and ensemble learning, characterized in that when a seller registers a product, it automatically generates a product description using generative AI and ensemble learning, and has a function to optimize the price based on market data collected in real time.

2. A market optimization system according to claim 1, characterized in that ensemble learning integrates multiple algorithms to improve the accuracy of product descriptions and pricing.

3. A market optimization system according to claim 1 or 2, characterized in that it includes a function to provide personalized product recommendations based on buyer preference data, past purchase history, and browsing history, using generative AI and ensemble learning.

4. A market optimization system according to any one of claims 1 to 3, characterized in that it includes a function to analyze image data of listed products using generative AI and ensemble learning, and to automatically extract features within the images and reflect them in the product description.

5. A market optimization system according to any one of claims 1 to 4, characterized in that it optimizes prices based on real-time market data, supply and demand data, and competitor product data using ensemble learning.

6. A market optimization system according to any one of claims 1 to 5, characterized in that it analyzes buyer behavior data and reviews by ensemble learning and makes suggestions to sellers for product improvements and optimization of pricing.

7. A market optimization system according to any one of claims 1 to 6, characterized in that it has a function to analyze market trends and demand fluctuations in real time using generative AI and ensemble learning, and to suggest to sellers the timing of price changes and inventory replenishment.

8. A market optimization system according to any one of claims 1 to 7, characterized in that it includes a function to automatically generate search keywords and tags related to a product by ensemble learning, and to display the product in the most optimal search results.

9. A market optimization system according to any one of claims 1 to 8, characterized in that it has a function to automatically generate advertising campaigns based on past purchaser behavior data using ensemble learning and to display advertisements optimized for target users.

10. A market optimization system according to any one of claims 1 to 9, characterized in that it includes an automatic moderation function by ensemble learning, and a generating AI monitors listed products and content, and automatically detects and addresses inappropriate products and spam activities.

11. A market optimization system according to any one of claims 1 to 10, characterized in that it employs a subscription model and allows sellers to use each function of the system based on a monthly or pay-per-use fee plan.

12. A market optimization system according to any one of claims 1 to 11, characterized in that it is provided on a cloud-based basis and that the ensemble learning and generative AI functions are always provided in their latest state.

13. A market optimization system according to any one of claims 1 to 12, characterized in that it automatically proposes new products to sellers and forecasts market demand based on product categories and characteristics, using generative AI and ensemble learning.

14. A market optimization system according to any one of claims 1 to 13, characterized in that when a product is listed on multiple platforms simultaneously, the generating AI and ensemble learning automatically generate product descriptions and pricing suitable for each platform.

15. A market optimization system according to any one of claims 1 to 14, characterized in that, based on data collected by the generative AI and ensemble learning, it automatically generates sales analysis reports and product performance reports for sellers to use in their next sales strategy.

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