Clustering analysis-based protection delay strategy optimization system for e-commerce platform

Abstract

The invention, which relates to the technical field of the e-commerce platform, discloses a cluster analysis-based extended insurance policy optimization system for an e-commerce platform, comprising a policy optimization module for optimizing the formulation of a pricing policy under an extended insurance policy of the e-commerce platform; the strategy optimization module comprises a strategy making unit, a function construction unit and a price making unit, the strategy making unit is connected with the function construction unit through a network, and the function construction unit is connected with the price making unit through the network. According to the invention, the strategy optimization module is designed, so that the optimal platform extended insurance strategy selection function of the e-commerce platform in the supply chain environment of manufacturer competition is realized, the operation efficiency and market response capability of the e-commerce platform are improved, and the scientificity and accuracy of the e-commerce platform in the extended insurance strategy making process are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of e-commerce platforms, and in particular to an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform. Background Art

[0002] With the continuous innovation of Internet technology, the e-commerce industry continues to develop rapidly. E-commerce platforms provide consumers with a convenient and efficient shopping platform, while also opening up new sales channels for manufacturers. With the increasing saturation of the e-commerce market and the intensification of competition, the profits of e-commerce platforms have declined.

[0003] As a value-added service that improves consumers' shopping experience, extended warranty service can help e-commerce platforms attract and retain consumers. In a supply chain environment with manufacturer competition, the choice of extended warranty strategy and the optimal pricing of extended warranty by e-commerce platforms are related to the profitability and user satisfaction of e-commerce platforms. Therefore, an extended warranty strategy optimization system based on cluster analysis for e-commerce platforms is extremely important.

[0004] 1. Patent document CN110414902B discloses an Internet-based e-commerce platform system. The above patent enables users to view the evaluation of the sold goods by accessing after-sales information and evaluation credibility, but the above patent cannot realize the optimal platform extended warranty strategy selection function of the e-commerce platform in a supply chain environment with manufacturer competition.

[0005] 2. Patent document CN110956528B discloses a recommendation method and system for an e-commerce platform. The above patent improves the prediction accuracy of the e-commerce platform on the probability of customer purchase, but the above patent cannot achieve the market segmentation function of consumer demand.

[0006] 3. Patent document CN112163227B discloses a multi-dimensional statistical analysis system and method for the sales of sellers on an e-commerce platform. The above patent realizes efficient statistical analysis of the sales of various commodities without leaking the privacy of sellers, but the above patent cannot realize the extended warranty service strategy selection function of the e-commerce platform.

[0007] 4. Patent document CN117788091B discloses a method and system for constructing a Metaverse e-commerce platform based on user consumption big data. The above patent realizes accurate detection of preferred products and reconstruction of product images, but the above patent cannot realize the monitoring function of the implementation effect of the extended warranty strategy of the e-commerce platform.

[0008] In summary, the above patents cannot realize the function of selecting the optimal extended warranty strategy of the e-commerce platform in a supply chain environment with competition among manufacturers, cannot realize the market segmentation function of consumer demand, cannot realize the extended warranty service strategy selection function of the e-commerce platform, and cannot realize the monitoring function of the extended warranty strategy implementation effect of the e-commerce platform, resulting in poor extended warranty strategy selection, lack of data basis, homogeneity of extended warranty services, and deviations in the implementation of extended warranty strategies on e-commerce platforms;

[0009] To this end, this application proposes an extended warranty strategy optimization system for e-commerce platforms based on cluster analysis, which realizes the optimal platform extended warranty strategy selection function of e-commerce platforms in a supply chain environment with manufacturer competition, the market segmentation function of consumer needs, the extended warranty service strategy selection function of e-commerce platforms, and the monitoring function of the implementation effect of extended warranty strategies of e-commerce platforms. Summary of the invention

[0010] The purpose of the present invention is to provide an extended warranty strategy optimization system for an e-commerce platform based on cluster analysis, so as to solve the technical problems proposed in the above background technology that the e-commerce platform's optimal platform extended warranty strategy selection function in a supply chain environment with manufacturer competition cannot be realized, the market segmentation function of consumer needs cannot be realized, the extended warranty service strategy selection function of the e-commerce platform cannot be realized, and the monitoring function of the extended warranty strategy implementation effect of the e-commerce platform cannot be realized, resulting in poor extended warranty strategy selection, lack of data basis, homogeneity of extended warranty services, and deviations in the execution of extended warranty strategies on the e-commerce platform.

[0011] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, comprising a strategy optimization module, wherein the strategy optimization module is used to optimize the formulation of pricing strategies under the extended warranty strategy of the e-commerce platform;

[0012] The strategy optimization module includes: a strategy formulation unit, a function construction unit and a price formulation unit, wherein the strategy formulation unit is connected to the function construction unit via a network, and the function construction unit is connected to the price formulation unit via a network;

[0013] The strategy formulation unit formulates a warranty extension strategy in which the e-commerce platform does not provide platform warranty extension, the e-commerce platform provides platform warranty extension for a single manufacturer, and the e-commerce platform provides platform warranty extension for two manufacturers in a supply chain consisting of two competing manufacturers;

[0014] The function construction unit constructs a product demand function and an extended warranty utility function under each extended warranty strategy based on the market segmentation and cluster analysis results, constructs an extended warranty demand function of the manufacturer and the e-commerce platform under each extended warranty strategy, and determines the profit function of the manufacturer and the e-commerce platform under each extended warranty strategy according to the extended warranty demand function;

[0015] The strategy selection unit calculates the optimal solution of the profit function, determines the commission rate and platform extended warranty price charged by the e-commerce platform to the manufacturer under different extended warranty strategies, uses Matlab software to perform numerical simulation, compares the optimal profit range of the e-commerce platform under different strategies, and determines the optimal extended warranty strategy of the e-commerce platform in a supply chain environment with manufacturer competition.

[0016] Preferably, the strategy optimization module is connected to a consumer demand module via a network, and the consumer demand module is used to segment consumer demand situations;

[0017] The consumption demand module includes: a data collection unit, a feature extraction unit and a cluster analysis unit, the data collection unit is connected to the feature extraction unit through a network, and the feature extraction unit is connected to the cluster analysis unit through a network;

[0018] The data collection unit collects the operation data of the e-commerce platform through the Internet, user feedback system and after-sales service system, collects the user's demand data on extended warranty of electronic products, and stores the data in the database;

[0019] The feature extraction unit receives data from a database, extracts features related to extended warranty pricing from the data, performs selection operations on the features of the data, removes redundant features from the data, retains a feature set related to extended warranty pricing, and performs standardization processing on the features;

[0020] The cluster analysis unit uses the clustering algorithm k-means to divide the data into different groups, analyze the characteristics of each group, identify user groups in different markets, and divide consumers into different market segments based on the characteristics of user groups.

[0021] Preferably, the strategy optimization module is connected to the extended warranty service module via a network, the extended warranty service module is connected to the consumer demand module via a network, and the extended warranty service module provides different extended warranty service strategies according to market demand;

[0022] The extended warranty service module includes: a service strategy unit, a model tuning unit and a service selection unit. The service strategy unit is connected to the model tuning unit via a network, and the model tuning unit is connected to the service selection unit via a network.

[0023] The service strategy unit conducts in-depth analysis of users in each market segment, identifies users’ extended warranty service needs, and develops differentiated extended warranty service strategies;

[0024] The model tuning unit builds a prediction model for the extended warranty service strategy based on the data in the database, and adjusts and optimizes the extended warranty service strategy through the prediction model, adjusting the extended warranty period, scope and service method;

[0025] The service selection unit evaluates each extended warranty service strategy, including cost-benefit analysis, user acceptance prediction, and market response prediction. Based on the evaluation results, it selects an extended warranty service strategy that meets the needs of each market segment.

[0026] Preferably, the policy optimization module is connected to a policy evaluation module via a network, and the policy evaluation module is used to monitor and evaluate the effect of the implementation of the extended warranty policy;

[0027] The strategy evaluation module includes: a strategy implementation unit, a monitoring and evaluation unit and a feedback and optimization unit. The strategy implementation unit is connected to the monitoring and evaluation unit through a network, and the monitoring and evaluation unit is connected to the feedback and optimization unit through a network.

[0028] The policy implementation unit deploys the extended warranty policy into the e-commerce platform system, accurately reflects the extended warranty policy in each link of front-end display, back-end processing, and user notification, and informs users and manufacturers about the details of the extended warranty policy;

[0029] The monitoring and evaluation unit collects real-time sales data, user feedback and complaints of extended warranty services on e-commerce platforms in a supply chain environment where manufacturers compete, and regularly evaluates the implementation effect of extended warranty strategies, including user satisfaction, sales volume and profit contribution;

[0030] The Feedback and Optimization Unit regularly collects user feedback on extended warranty services through online user evaluations and customer service feedback, organizes and analyzes the feedback content, and provides suggestions for optimizing extended warranty strategies.

[0031] Preferably, the consumer demand module is connected to a data integration module via a network, and the data integration module is used to convert the data into a unified standard format;

[0032] The data integration module includes: a data standardization unit, a data encryption unit and a data storage unit, the data standardization unit is connected to the data encryption unit via a network, and the data encryption unit is connected to the data storage unit via a network;

[0033] The data standardization unit converts data from different channels into a unified standard format, removes duplicate, erroneous and incomplete data, integrates data according to business logic and requirements, and establishes a structured data set;

[0034] The data encryption unit uses encryption algorithms to encrypt the integrated data, establishes a key management mechanism, generates keys of different levels, distributes keys according to security requirements and access rights, and regularly updates keys;

[0035] The data storage unit performs sharding on the encrypted data, stores the sharded data in different storage nodes, and sets user access permissions.

[0036] Preferably, the product demand function is:

[0037] The first manufacturer's product demand function:

[0038] The demand function of the second manufacturer's product is: k = N / A / B / AB;

[0039] in, and denote the product demand of the first manufacturer and the second manufacturer respectively, p i (i=a, b, representing the first manufacturer and the second manufacturer respectively) is the product retail price, ρ is the market share of the first manufacturer, (1-ρ) is the market share of the second manufacturer, τ1 and τ2 are the market expansion effects of the extended warranty of the first manufacturer and the second manufacturer respectively, α is the potential market size of the e-commerce platform, d is the price competition factor of the manufacturer, θ is the market expansion effect of the platform's extended warranty, N is the case where the e-commerce platform does not provide it, A is the case where the e-commerce platform provides extended warranty to the first manufacturer, B is the case where the e-commerce platform provides extended warranty to the second manufacturer, and AB is the case where the e-commerce platform provides extended warranty to the first manufacturer and the second manufacturer.

[0040] Preferably, the extended warranty demand function includes the following situations:

[0041] Strategy 1: E-commerce platforms do not provide platform extended warranty

[0042] Extended warranty demand functions for purchasing only the product, purchasing the product and extended warranty service from the first manufacturer, and purchasing the product and extended warranty service from the second manufacturer;

[0043] Strategy 2: E-commerce platforms provide platform extended warranty for first-tier manufacturers

[0044] Extended warranty demand function for purchasing only the product, purchasing the first manufacturer's product and extended warranty service, purchasing the second manufacturer's product and extended warranty service, and purchasing the first manufacturer's product and the platform's extended warranty service;

[0045] Strategy 3: E-commerce platforms provide platform extended warranty for first-tier manufacturers

[0046] Extended warranty demand functions for purchasing only the product, purchasing the product and extended warranty service of the first manufacturer, purchasing the product and extended warranty service of the second manufacturer, and purchasing the product and extended warranty service of the second manufacturer and the platform;

[0047] Strategy 4: The e-commerce platform provides platform extended warranty for two manufacturers

[0048] The extended warranty demand function for purchasing only products, purchasing products and extended warranty services from the first manufacturer, purchasing products and extended warranty services from the second manufacturer, purchasing products and extended warranty services from the second manufacturer’s platform, and purchasing products and extended warranty services from the first manufacturer’s platform.

[0049] Preferably, the method for using the clustering algorithm k-means comprises the following steps:

[0050] Step 1: Determine the number of categories to be clustered, and select m center points;

[0051] Step 2: For each sample point, find the center point closest to the sample point. The points closest to the same center point are one class.

[0052] Step 3: Determine the categories of the sample points before and after clustering. If the categories are the same, the algorithm terminates. If the categories are different, proceed to step 4.

[0053] Step 4: For each sample point in each category, calculate the center point of the sample point, use it as the new center point, and repeat step 2.

[0054] Preferably, the extended warranty service strategy includes different extended warranty periods, extended warranty scopes, prices and service methods.

[0055] Preferably, the strategy evaluation module is connected to a risk evaluation module via a network. During the implementation of the extended warranty strategy, the risk evaluation module performs real-time risk evaluation, identifies potential market risks and changes in user demand, and establishes a risk early warning mechanism. When problems arise during the implementation of the extended warranty strategy, an alarm message is issued in a timely manner.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] 1. The present invention is designed with a strategy optimization module to realize the optimal platform extended warranty strategy selection function of the e-commerce platform in the supply chain environment where manufacturers compete, improve the operating efficiency and market responsiveness of the e-commerce platform, and improve the scientificity and accuracy of the e-commerce platform in the process of formulating extended warranty strategies;

[0058] 2. The present invention realizes the market segmentation function of consumer demand by designing a consumer demand module, provides data support for formulating and optimizing extended warranty strategies, and improves the marketing efficiency and user conversion rate of e-commerce platforms in a supply chain environment where manufacturers compete;

[0059] 3. The present invention implements the extended warranty service strategy selection function of the e-commerce platform by designing an extended warranty service module, thereby improving user satisfaction and loyalty to the extended warranty service, improving the profitability of the e-commerce platform, and solving the problem of service homogeneity in traditional extended warranty services;

[0060] 4. The present invention realizes the monitoring function of the implementation effect of the extended warranty strategy of the e-commerce platform by designing a strategy evaluation module, solves the deviation and omission problems that may occur during the execution of the extended warranty strategy on the e-commerce platform, and ensures the effective implementation of the extended warranty strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the strategy optimization module of the present invention;

[0062] Figure 2 It is a schematic diagram of the consumption demand module of the present invention;

[0063] Figure 3 This is a schematic diagram of the extended warranty service module of the present invention;

[0064] Figure 4 is a schematic diagram of a strategy evaluation module of the present invention;

[0065] Figure 5 It is a schematic diagram of a data integration module of the present invention;

[0066] Figure 6 It is a schematic diagram of the work flow of the strategy evaluation module of the present invention;

[0067] Figure 7 It is a schematic diagram of the system working process of the present invention;

[0068] Figure 8 It is a schematic diagram of the profit function solving process of the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] See also Figure 1 , Figure 7 and Figure 8 , an embodiment provided by the present invention: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, comprising a strategy optimization module, wherein the strategy optimization module is used to optimize the formulation of a pricing strategy under an extended warranty strategy of the e-commerce platform;

[0071] The strategy optimization module includes: a strategy formulation unit, a function construction unit and a price formulation unit, wherein the strategy formulation unit is connected to the function construction unit via a network, and the function construction unit is connected to the price formulation unit via a network;

[0072] The strategy formulation unit formulates a warranty extension strategy in which the e-commerce platform does not provide platform warranty extension, the e-commerce platform provides platform warranty extension for a single manufacturer, and the e-commerce platform provides platform warranty extension for two manufacturers in a supply chain consisting of two competing manufacturers;

[0073] The function construction unit constructs a product demand function and an extended warranty utility function under each extended warranty strategy based on the market segmentation and cluster analysis results, constructs an extended warranty demand function of the manufacturer and the e-commerce platform under each extended warranty strategy, and determines the profit function of the manufacturer and the e-commerce platform under each extended warranty strategy according to the extended warranty demand function;

[0074] The strategy selection unit calculates the optimal solution of the profit function, determines the commission rate and platform extended warranty price charged by the e-commerce platform to the manufacturer under different extended warranty strategies, uses Matlab software to perform numerical simulation, compares the optimal profit range of the e-commerce platform under different strategies, and determines the optimal extended warranty strategy of the e-commerce platform in the supply chain environment where manufacturers compete;

[0075] Furthermore, in an online retail supply chain consisting of two competing manufacturers and an e-commerce platform, the strategy formulation unit formulates four possible platform extended warranty strategies; the function construction unit analyzes the demand of different user groups for products of different manufacturers based on the market segmentation and cluster analysis results, and analyzes the user's willingness to purchase product extended warranties, thereby analyzing the relationship between extended warranty demand and factors such as product price and extended warranty price, and obtains the product demand function according to the first manufacturer: The demand function of the second manufacturer's product is: in, and denote the product demand of the first manufacturer and the second manufacturer respectively, p i (i=a, b, representing the first manufacturer and the second manufacturer respectively) is the product retail price, ρ is the market share of the first manufacturer, (1-ρ) is the market share of the second manufacturer, τ1 and τ2 are the market expansion effects of the extended warranty of the first manufacturer and the second manufacturer respectively, α is the potential market size of the e-commerce platform, d is the price competition factor of the manufacturer, θ is the market expansion effect of the platform extended warranty, N is the case where the e-commerce platform does not provide it, A is the case where the e-commerce platform provides extended warranty to the first manufacturer, B is the case where the e-commerce platform provides extended warranty to the second manufacturer, and AB is the case where the e-commerce platform provides extended warranty to the first manufacturer and the second manufacturer;

[0076] Then, the product demand function, extended warranty utility function, extended warranty demand function and profit function of manufacturers and e-commerce platforms under each extended warranty strategy are constructed. The strategy selection unit solves the optimal solution of the profit function under each extended warranty strategy, determines the commission rate and platform extended warranty price charged by the e-commerce platform to the manufacturer under the supply chain environment of competing manufacturers, uses Matlab and other software for numerical simulation, simulates the platform profit under different extended warranty strategies, and calculates the optimal profit range of the e-commerce platform under each extended warranty strategy, thereby revealing the optimal profit range of the e-commerce platform within the space of manufacturer market share and potential market size. Finally, the optimal extended warranty strategy is selected, and the platform extended warranty price under the supply chain environment of competing manufacturers is determined, thereby improving the overall profit of the supply chain;

[0077] The optimal extended warranty strategy of the e-commerce platform in the supply chain environment of competitive manufacturers provides theoretical guidance for manufacturers among the supply chain members on product pricing and extended warranty pricing under competitive situations, improves the operating efficiency and user conversion rate of the e-commerce platform, thereby attracting more consumers to purchase the extended warranty services of the platform and manufacturers, enhances the market competitiveness of the supply chain members, and increases the overall profit of the supply chain.

[0078] See also Figure 2 and Figure 7 , an embodiment provided by the present invention: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, wherein the strategy optimization module is connected to a consumer demand module via a network, and the consumer demand module is used to segment consumer demand situations;

[0079] The consumption demand module includes: a data collection unit, a feature extraction unit and a cluster analysis unit, the data collection unit is connected to the feature extraction unit through a network, and the feature extraction unit is connected to the cluster analysis unit through a network;

[0080] The data collection unit collects the operation data of the e-commerce platform through the Internet, user feedback system and after-sales service system, collects the user's demand data on extended warranty of electronic products, and stores the data in the database;

[0081] The feature extraction unit receives data from a database, extracts features related to extended warranty pricing from the data, performs selection operations on the features of the data, removes redundant features from the data, retains a feature set related to extended warranty pricing, and performs standardization processing on the features;

[0082] The cluster analysis unit uses the clustering algorithm k-means to divide the data into different groups, analyze the characteristics of each group, identify user groups in different markets, and divide consumers into different market segments based on the characteristics of user groups;

[0083] Furthermore, the data collection unit collects various types of user data from the database of the e-commerce platform, the user feedback system, the after-sales service system and other channels, including basic user information, purchase history, extended warranty service purchase status, product usage feedback, etc., ensures the real-time and integrity of the data, and stores the collected data in the database;

[0084] The feature extraction unit receives data from the database, selects features related to extended warranty pricing, such as the potential market size of the e-commerce platform, the market expansion effect of platform extended warranty, and consumer acceptance of platform extended warranty, etc., analyzes the correlation between features, removes redundant features that have little impact on extended warranty pricing or are highly correlated with other features, and converts feature values ​​to the same scale;

[0085] The clustering analysis unit will receive the data processed by the feature extraction unit, input the data into the clustering algorithm k-means, execute the clustering process, and perform feature analysis on each group, including user behavior, purchasing habits, product preferences, acceptance of extended warranty services, etc., analyze the differences between groups and the commonalities within groups, and divide consumers into different market segments based on the clustering results and the characteristics of the user groups, so as to provide a data basis for the pricing and selection of extended warranty strategies of e-commerce platforms under the supply chain situation of manufacturer competition, so that the optimized extended warranty strategy can meet the needs of different user groups, thereby improving user satisfaction and loyalty.

[0086] See also Figure 3 and Figure 7 , an embodiment provided by the present invention: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, wherein the strategy optimization module is connected to an extended warranty service module via a network, the extended warranty service module is connected to a consumer demand module via a network, and the extended warranty service module provides different extended warranty service strategies according to market demand;

[0087] The extended warranty service module includes: a service strategy unit, a model tuning unit and a service selection unit. The service strategy unit is connected to the model tuning unit via a network, and the model tuning unit is connected to the service selection unit via a network.

[0088] The service strategy unit conducts in-depth analysis of users in each market segment, identifies users’ extended warranty service needs, and develops differentiated extended warranty service strategies;

[0089] The model tuning unit builds a prediction model for the extended warranty service strategy based on the data in the database, and adjusts and optimizes the extended warranty service strategy through the prediction model, adjusting the extended warranty period, scope and service method;

[0090] The service selection unit evaluates each extended warranty service strategy, including cost-benefit analysis, user acceptance prediction, and market response prediction. Based on the evaluation results, it selects an extended warranty service strategy that meets the needs of each market segment;

[0091] Furthermore, the service strategy unit receives the data from the cluster analysis of the consumer demand module, deeply analyzes the user behavior, purchasing habits and historical data of extended warranty services in each market segment, identifies the extended warranty service needs of users in each market segment, and formulates extended warranty service strategies for different market segments based on the user needs and characteristics of each market segment, including extended warranty period, coverage, service methods, etc., so as to meet the personalized needs of different user groups, enable the e-commerce platform to accurately reach the target user group, improve the marketing efficiency and user conversion rate of the platform supply chain, and consumers choose the extended warranty service strategy that suits them according to their personal preferences and needs, thereby improving consumers' shopping experience, increasing the sales of extended warranty services, and thus improving the overall profit of the supply chain;

[0092] The model tuning unit extracts data related to the extended warranty strategy from the database, uses the data to train the prediction model of the extended warranty service strategy, obtains the prediction model for each market segment, and adjusts different extended warranty service strategies through the prediction model to make the extended warranty service strategy more in line with market demand; the service selection unit conducts a comprehensive evaluation of the extended warranty service strategy in each market segment to ensure that the selected extended warranty service strategy meets the needs of each market segment, improves the overall profit of the supply chain, and improves the marketing efficiency and user conversion rate of the e-commerce platform.

[0093] See also Figure 4 , Figure 6 and Figure 7 , an embodiment provided by the present invention: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, wherein the strategy optimization module is connected to a strategy evaluation module via a network, and the strategy evaluation module is used to monitor and evaluate the implementation effect of the extended warranty strategy;

[0094] The strategy evaluation module includes: a strategy implementation unit, a monitoring and evaluation unit and a feedback and optimization unit. The strategy implementation unit is connected to the monitoring and evaluation unit through a network, and the monitoring and evaluation unit is connected to the feedback and optimization unit through a network.

[0095] The policy implementation unit deploys the extended warranty policy into the e-commerce platform system, accurately reflects the extended warranty policy in each link of front-end display, back-end processing, and user notification, and informs users and manufacturers about the details of the extended warranty policy;

[0096] The monitoring and evaluation unit collects real-time sales data, user feedback and complaints of extended warranty services on e-commerce platforms in a supply chain environment where manufacturers compete, and regularly evaluates the implementation effect of extended warranty strategies, including user satisfaction, sales volume and profit contribution;

[0097] The feedback and optimization unit regularly collects user feedback on extended warranty services through online user reviews and customer service feedback, organizes and analyzes the feedback content, and provides suggestions for optimizing extended warranty strategies;

[0098] Furthermore, the strategy implementation unit integrates the extended warranty strategy formulated and optimized in the early stage into the system of the e-commerce platform. The front-end user interface of the e-commerce platform displays the latest extended warranty options and information to users. The back-end system promptly handles the purchase and claim settlement of extended warranty services by users, and notifies users and manufacturers of changes in extended warranty strategies. In the platform supply chain environment where manufacturers compete, competing manufacturers adjust production plans and marketing strategies based on strategy information, and quickly respond to changes in market demand, thereby predicting the demand for products and spare parts, reducing the risk of excess inventory and out-of-stock, reducing operating costs, and improving the overall operational efficiency of the supply chain. After understanding the extended warranty strategies of competitors and user feedback, manufacturers adjust their own extended warranty strategies to make them have more competitive prices and better services, thereby improving market competitiveness and further improving the overall operational efficiency and profits of the supply chain.

[0099] The monitoring and evaluation unit collects various data related to the extended warranty service in real time, analyzes and regularly evaluates the data, and judges whether the implemented extended warranty strategy is correct by evaluating the trend of changes in indicators. This avoids the blindness and subjectivity of previous extended warranty strategy effect evaluations and provides objective and accurate evaluation results for e-commerce platforms.

[0100] The feedback and optimization unit solves the problem of delayed user feedback processing by collecting user feedback in real time and responding quickly, extracts users' main concerns and dissatisfaction points, and puts forward optimization suggestions for extended warranty strategies, thereby improving user satisfaction and loyalty. By organizing and analyzing user feedback, the e-commerce platform can effectively coordinate the relationship between manufacturers and consumers, promote information sharing and close cooperation among various links in the supply chain, and improve the overall efficiency and stability of the supply chain.

[0101] See also Figure 5 and Figure 7 , an embodiment provided by the present invention: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, wherein the consumer demand module is connected to a data integration module via a network, and the data integration module is used to convert data into a unified standard format;

[0102] The data integration module includes: a data standardization unit, a data encryption unit and a data storage unit, the data standardization unit is connected to the data encryption unit via a network, and the data encryption unit is connected to the data storage unit via a network;

[0103] The data standardization unit converts data from different channels into a unified standard format, removes duplicate, erroneous and incomplete data, integrates data according to business logic and requirements, and establishes a structured data set;

[0104] The data encryption unit uses encryption algorithms to encrypt the integrated data, establishes a key management mechanism, generates keys of different levels, distributes keys according to security requirements and access rights, and regularly updates keys;

[0105] The data storage unit performs sharding processing on the encrypted data, stores the sharded data in different storage nodes, and sets the user's access authority;

[0106] Furthermore, the data standardization unit unifies and integrates data, improves data processing efficiency, reduces the complexity of subsequent analysis, ensures data accuracy and consistency, and provides a reliable data basis for cluster analysis and extended warranty strategy formulation; the data encryption unit protects data integrity, protects user privacy, avoids unauthorized access or leakage of sensitive data, improves data security, and enhances the reputation of the e-commerce platform and user trust;

[0107] The data storage unit cuts large data sets into multiple smaller data blocks and stores them in different storage nodes, realizing distributed storage and redundant backup of data, improving the reliability and fault tolerance of data storage, and avoiding data loss due to failure of a storage node.

[0108] See also Figure 1 , Figure 3 and Figure 7 , an embodiment provided by the present invention: an extended warranty strategy optimization system based on cluster analysis of an e-commerce platform, comprising a strategy optimization module and an extended warranty service module; the strategy optimization module comprises: a strategy formulation unit, a function construction unit and a price formulation unit, the strategy formulation unit is connected to the function construction unit through a network, and the function construction unit is connected to the price formulation unit through a network;

[0109] The strategy formulation unit formulates the extended warranty strategies of the e-commerce platform not providing platform extended warranty, the e-commerce platform providing platform extended warranty for a single manufacturer, and the e-commerce platform providing platform extended warranty for two manufacturers in a supply chain consisting of two competing manufacturers; the function construction unit constructs the product demand function and extended warranty utility function under each extended warranty strategy based on the market segmentation and cluster analysis results, constructs the extended warranty demand function of the manufacturer and the e-commerce platform under each extended warranty strategy, and determines the profit function of the manufacturer and the e-commerce platform under each extended warranty strategy based on the extended warranty demand function; the strategy selection unit calculates the optimal solution of the profit function, determines the commission rate and platform extended warranty price charged by the e-commerce platform to the manufacturer under different extended warranty strategies, uses Matlab software for numerical simulation, compares the optimal profit range of the e-commerce platform under different strategies, and determines the optimal extended warranty strategy of the e-commerce platform in the supply chain environment with manufacturer competition;

[0110] The extended warranty service module includes: a service strategy unit, a model tuning unit and a service selection unit. The service strategy unit is connected to the model tuning unit through a network, and the model tuning unit is connected to the service selection unit through a network. The service strategy unit deeply analyzes the users of each market segment, identifies the extended warranty service needs of the users, and formulates differentiated extended warranty service strategies. The model tuning unit builds a prediction model for the extended warranty service strategy based on the data in the database, and adjusts and optimizes the extended warranty service strategy through the prediction model, and adjusts the extended warranty period, scope and service method. The service selection unit evaluates each extended warranty service strategy, including cost-benefit analysis, user acceptance prediction, and market reaction prediction, and selects an extended warranty service strategy that meets the needs of each market segment based on the evaluation results.

[0111] Furthermore, in the platform supply chain environment where manufacturers compete, the strategy optimization module formulates an extended warranty strategy through market analysis, including whether the e-commerce platform provides platform extended warranty and whether to provide extended warranty for a single manufacturer or two manufacturers, providing macro-guidance and direction for the extended warranty service module. On the basis of the strategy optimization module, the extended warranty service module further analyzes the user needs of each market segment and formulates differentiated extended warranty service strategies, including specific details such as extended warranty period, coverage, and service methods, and refines the extended warranty strategy. At the same time, manufacturers formulate and adjust their own extended warranty strategies based on the extended warranty strategies of the platform and competitors to make them more competitive in the market, so that supply chain members can jointly enhance their market competitiveness, improve user satisfaction, and improve the marketing efficiency and user conversion rate of the e-commerce platform, thereby increasing the overall profit of the supply chain.

[0112] Working principle: The market segmentation and cluster analysis results obtained by the consumer demand module provide important data support and decision-making basis for the strategy optimization module to build the profit function in the platform supply chain environment where manufacturers compete and obtain the optimal extended warranty strategy. Through cluster analysis and extended warranty strategy optimization, the market competitiveness of supply chain members can be improved;

[0113] The consumer demand module and the strategy evaluation module feed back the data analysis results to the extended warranty service module, so that the extended warranty service module can more accurately build and correct the prediction model. The extended warranty service module further refines the extended warranty strategy in the platform supply chain environment where manufacturers compete, adjusts the extended warranty service strategy through the prediction model, and improves the overall operational efficiency of the supply chain;

[0114] The strategy evaluation module collects data from the actual service process, evaluates the effectiveness of strategy implementation, and feeds the data back to the strategy optimization module through the consumer demand module to form a data closed loop. The risk assessment module performs risk assessment on the data collected by the strategy evaluation module. When it detects that the extended warranty strategy has lost its effectiveness, the risk assessment module will issue an early warning.

[0115] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An extended warranty strategy optimization system based on cluster analysis for an e-commerce platform, characterized by: It includes a strategy optimization module, which is used to optimize the formulation of pricing strategies under the extended warranty strategy of the e-commerce platform; The strategy optimization module includes: a strategy formulation unit, a function construction unit and a price formulation unit, wherein the strategy formulation unit is connected to the function construction unit via a network, and the function construction unit is connected to the price formulation unit via a network; The strategy formulation unit formulates a warranty extension strategy in which the e-commerce platform does not provide platform warranty extension, the e-commerce platform provides platform warranty extension for a single manufacturer, and the e-commerce platform provides platform warranty extension for two manufacturers in a supply chain consisting of two competing manufacturers; The function construction unit constructs a product demand function and an extended warranty utility function under each extended warranty strategy based on the market segmentation and cluster analysis results, constructs an extended warranty demand function of the manufacturer and the e-commerce platform under each extended warranty strategy, and determines the profit function of the manufacturer and the e-commerce platform under each extended warranty strategy according to the extended warranty demand function; The strategy selection unit calculates the optimal solution of the profit function, determines the commission rate and platform extended warranty price charged by the e-commerce platform to the manufacturer under different extended warranty strategies, uses Matlab software to perform numerical simulation, compares the optimal profit range of the e-commerce platform under different strategies, and determines the optimal extended warranty strategy of the e-commerce platform in a supply chain environment with manufacturer competition.

2. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 1, characterized in that: The strategy optimization module is connected to a consumer demand module via a network, and the consumer demand module is used to segment consumer demand situations; The consumption demand module includes: a data collection unit, a feature extraction unit and a cluster analysis unit, the data collection unit is connected to the feature extraction unit through a network, and the feature extraction unit is connected to the cluster analysis unit through a network; The data collection unit collects the operation data of the e-commerce platform through the Internet, user feedback system and after-sales service system, collects the user's demand data on extended warranty of electronic products, and stores the data in the database; The feature extraction unit receives data from a database, extracts features related to extended warranty pricing from the data, performs selection operations on the features of the data, removes redundant features from the data, retains a feature set related to extended warranty pricing, and performs standardization processing on the features; The cluster analysis unit uses the clustering algorithm k-means to divide the data into different groups, analyze the characteristics of each group, identify user groups in different markets, and divide consumers into different market segments based on the characteristics of user groups.

3. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 1, characterized in that: The strategy optimization module is connected to the extended warranty service module through the network, and the extended warranty service module is connected to the consumer demand module through the network. The extended warranty service module provides different extended warranty service strategies according to market demand; The extended warranty service module includes: a service strategy unit, a model tuning unit and a service selection unit. The service strategy unit is connected to the model tuning unit via a network, and the model tuning unit is connected to the service selection unit via a network. The service strategy unit conducts in-depth analysis of users in each market segment, identifies users’ extended warranty service needs, and develops differentiated extended warranty service strategies; The model tuning unit builds a prediction model for the extended warranty service strategy based on the data in the database, and adjusts and optimizes the extended warranty service strategy through the prediction model, adjusting the extended warranty period, scope and service method; The service selection unit evaluates each extended warranty service strategy, including cost-benefit analysis, user acceptance prediction, and market response prediction. Based on the evaluation results, it selects an extended warranty service strategy that meets the needs of each market segment.

4. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 1, characterized in that: The strategy optimization module is connected to a strategy evaluation module via a network, and the strategy evaluation module is used to monitor and evaluate the implementation effect of the extended warranty strategy; The strategy evaluation module includes: a strategy implementation unit, a monitoring and evaluation unit and a feedback and optimization unit. The strategy implementation unit is connected to the monitoring and evaluation unit through a network, and the monitoring and evaluation unit is connected to the feedback and optimization unit through a network. The policy implementation unit deploys the extended warranty policy into the e-commerce platform system, accurately reflects the extended warranty policy in each link of front-end display, back-end processing, and user notification, and informs users and manufacturers about the details of the extended warranty policy; The monitoring and evaluation unit collects real-time sales data, user feedback and complaints of extended warranty services on e-commerce platforms in a supply chain environment where manufacturers compete, and regularly evaluates the implementation effect of extended warranty strategies, including user satisfaction, sales volume and profit contribution; The Feedback and Optimization Unit regularly collects user feedback on extended warranty services through online user evaluations and customer service feedback, organizes and analyzes the feedback content, and provides suggestions for optimizing extended warranty strategies.

5. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 2, characterized in that: The consumer demand module is connected to a data integration module via a network, and the data integration module is used to convert data into a unified standard format; The data integration module includes: a data standardization unit, a data encryption unit and a data storage unit, the data standardization unit is connected to the data encryption unit via a network, and the data encryption unit is connected to the data storage unit via a network; The data standardization unit converts data from different channels into a unified standard format, removes duplicate, erroneous and incomplete data, integrates data according to business logic and requirements, and establishes a structured data set; The data encryption unit uses encryption algorithms to encrypt the integrated data, establishes a key management mechanism, generates keys of different levels, distributes keys according to security requirements and access rights, and regularly updates keys; The data storage unit performs sharding on the encrypted data, stores the sharded data in different storage nodes, and sets user access permissions.

6. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 1, characterized in that: The product demand function is: The first manufacturer's product demand function: The second manufacturer's product demand function: in, and denote the product demand of the first manufacturer and the second manufacturer respectively, and p i (i=a, b, representing the first manufacturer and the second manufacturer respectively) is the product retail price, ρ is the market share of the first manufacturer, (1-ρ) is the market share of the second manufacturer, τ1 and τ2 are the market expansion effects of the extended warranty of the first manufacturer and the second manufacturer respectively, α is the potential market size of the e-commerce platform, d is the price competition factor of the manufacturer, θ is the market expansion effect of the platform's extended warranty, N is the case where the e-commerce platform does not provide it, A is the case where the e-commerce platform provides extended warranty to the first manufacturer, B is the case where the e-commerce platform provides extended warranty to the second manufacturer, and AB is the case where the e-commerce platform provides extended warranty to the first manufacturer and the second manufacturer.

7. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 1, characterized in that: The extended warranty demand function includes the following situations: Strategy 1: E-commerce platforms do not provide platform extended warranty Extended warranty demand functions for purchasing only the product, purchasing the product and extended warranty service from the first manufacturer, and purchasing the product and extended warranty service from the second manufacturer; Strategy 2: E-commerce platforms provide platform extended warranty for first-tier manufacturers Extended warranty demand function for purchasing only the product, purchasing the first manufacturer's product and extended warranty service, purchasing the second manufacturer's product and extended warranty service, and purchasing the first manufacturer's product and the platform's extended warranty service; Strategy 3: E-commerce platforms provide platform extended warranty for first-tier manufacturers Extended warranty demand functions for purchasing only the product, purchasing the product and extended warranty service of the first manufacturer, purchasing the product and extended warranty service of the second manufacturer, and purchasing the product and extended warranty service of the second manufacturer and the platform; Strategy 4: The e-commerce platform provides platform extended warranty for two manufacturers The extended warranty demand function for purchasing only products, purchasing products and extended warranty services from the first manufacturer, purchasing products and extended warranty services from the second manufacturer, purchasing products and extended warranty services from the second manufacturer’s platform, and purchasing products and extended warranty services from the first manufacturer’s platform.

8. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 2, characterized in that: The method for using the clustering algorithm k-means includes the following steps: Step 1: Determine the number of categories to be clustered, and select m center points; Step 2: For each sample point, find the center point closest to the sample point. The points closest to the same center point are one class. Step 3: Determine the categories of the sample points before and after clustering. If the categories are the same, the algorithm terminates. If the categories are different, proceed to step 4. Step 4: For each sample point in each category, calculate the center point of the sample point, use it as the new center point, and repeat step 2.

9. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 3, characterized in that: The extended warranty service strategy includes different extended warranty periods, extended warranty scopes, prices and service methods.

10. The extended warranty strategy optimization system based on cluster analysis for an e-commerce platform according to claim 4, characterized in that: The strategy assessment module is connected to the risk assessment module via a network. During the implementation of the extended warranty strategy, the risk assessment module performs real-time risk assessment, identifies potential market risks and changes in user demand, and establishes a risk early warning mechanism. When problems arise during the implementation of the extended warranty strategy, an alarm message is issued in a timely manner.

Images