Directional promotion system for value-added service products

Abstract

The invention discloses a directional promotion system for value-added service products. The directional promotion system comprises a data acquisition module, a data analysis module, a service product library, a feature output module, a matching module, a pushing module and a user feedback module. The data acquisition module is used for collecting power consumption data of a user, and the power consumption data comprises but is not limited to power consumption, power consumption time, power consumption frequency and electric appliance types; the data analysis module is used for processing and analyzing the collected data, identifying power utilization habits and power characteristics of users and forming customer attribute categories; according to the method, basic power supply service and value-added service products are deeply fused, upstream and downstream industrial chains are integrated in a cross-boundary manner, a diversified service product package is created, meanwhile, data analysis is performed and specific customer attribute categories are output by integrating data such as power utilization habits and power characteristics of users, accurate directional pushing is realized, and the user experience is improved. The power grid sales capability is improved, and user use requirements are met.

Description

Technical Field

[0001] The invention relates to the technical field of power supply and data analysis, and in particular to a system for directional promotion of value-added service products. Background Art

[0002] In the traditional power service model, basic power supply services and value-added service products are often independent of each other and fail to achieve deep integration. Although this method can meet basic power supply needs, it is insufficient in cross-border integration of upstream and downstream industrial chains and creating diversified service product packages. At the same time, traditional methods are not sufficient in integrating and analyzing user electricity consumption data, resulting in the inability to accurately and targetedly push information based on user habits and power characteristics, which in turn affects the sales capabilities and user satisfaction of power grid companies. Summary of the invention

[0003] The purpose of the present invention is to provide a system for targeted promotion of value-added service products to solve the problems raised in the above background technology.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a system for targeted promotion of value-added service products, the targeted promotion system comprising a data collection module, a data analysis module, a service product library, a feature output module, a matching module, a push module, and a user feedback module;

[0005] The data collection module is used to collect the user's electricity consumption data, which includes but is not limited to electricity consumption, electricity consumption time, electricity consumption frequency, and appliance type;

[0006] The data analysis module is used to process and analyze the collected data, identify the user's electricity usage habits and electricity characteristics, and form customer attribute categories;

[0007] The feature output module is used to output customer features according to the data analysis results;

[0008] The matching module is used to match comprehensive electricity consumption attributes and service product characteristics to achieve precise and targeted push;

[0009] The push module is used to push the matching service product packages to the user through the channel preferred by the user;

[0010] The user feedback module is used to collect user feedback on the push service, so as to optimize the matching algorithm and service quality.

[0011] Preferably, the specific method of using the data collection module in the value-added service product directional promotion system includes the following steps:

[0012] S1: Install intelligent monitoring equipment in the user's electricity meter or distribution box, including a smart meter or a current sensor with data transmission function, so that the device can monitor and record the user's electricity consumption data in real time;

[0013] S2: Configure intelligent monitoring devices to send data to the cloud platform via wireless networks, using encryption technology to protect privacy and security during data transmission;

[0014] S3: The intelligent monitoring device automatically records the power consumption data at the set time interval;

[0015] S4: Before transmission to the cloud platform, the intelligent monitoring device performs preliminary processing on the data, including noise filtering and outlier detection, to reduce the amount of data transmission and improve the accuracy of subsequent analysis;

[0016] S5: The collected data is sent to the cloud platform through the established data communication link. On the server side, the data is stored in the database, waiting for further processing and analysis.

[0017] Preferably, the specific method of using the data analysis module in the value-added service product targeted promotion system includes the following steps:

[0018] S11: Analyze the user's electricity consumption cycle and identify the peak and valley periods; infer the type of electrical appliances and load size used by the user through the fluctuation patterns of current and voltage; calculate the user's overall energy consumption and energy consumption in each period to evaluate energy efficiency;

[0019] S12: Use a hierarchical clustering algorithm to group users’ electricity usage behaviors and find user groups with similar electricity usage patterns;

[0020] S13: assigning labels to each user based on the results of the electricity usage behavior analysis, and classifying the users into different categories based on their electricity usage habits and preferences;

[0021] S14: Use historical electricity consumption data to build a prediction model to predict users' future electricity consumption trends and needs, and optimize the model through parameter adjustment methods to improve the accuracy of the prediction;

[0022] S15: Display the analysis results in the form of charts to facilitate understanding and communication, generate detailed analysis reports, summarize the key points of users' electricity consumption behavior and recommend strategies.

[0023] Preferably, the electricity consumption cycle includes a daily electricity consumption pattern and a weekly electricity consumption pattern; user allocation tags include peak electricity users, nighttime electricity users, and high energy consumption users; user types include economical, environmentally friendly, and convenient.

[0024] Preferably, the service product library includes information on a variety of value-added service products, including peak-valley electricity price discounts, energy-saving consulting services, and smart home integration solutions.

[0025] Preferably, the specific method of using the matching module in the value-added service product directional promotion system includes the following steps:

[0026] S21: receiving the customer's electricity consumption attribute characteristic data from the characteristic output module;

[0027] S22: Organize the available value-added service product catalog and extract the key features of each service product;

[0028] S23: Select a rule-based matching algorithm based on customer characteristics and service product features, and use historical data to train the matching algorithm to improve matching accuracy;

[0029] S24: Input the customer's electricity usage attribute characteristics and service product characteristics into the matching algorithm. The algorithm calculates the matching degree between the customer and each service product. The matching degree takes into account factors including electricity usage habits, preferences, and product characteristics. The service products are ranked according to the matching degree, and the best matching product or product combination is selected.

[0030] S25: Evaluate the potential value of the matching results so that the recommended products meet the needs of users.

[0031] Preferably, the value-added service product catalog includes product features, target user groups, costs, and benefits; key characteristics of service products include energy-saving performance, usage period optimization, and cost-effectiveness ratio.

[0032] Preferably, the specific method of using the push module in the value-added service product directional promotion system includes the following steps:

[0033] S31: Customizing push content based on the matching results, the push content includes details, advantages, and price information of the service product package;

[0034] S32: analyzing the user's preferred information receiving channels, which include email, SMS, mobile app notifications, and social media, and selecting a corresponding push channel based on the user's preference and the coverage efficiency of the channel;

[0035] S33: Determine the best time to push messages, taking into account user activity time and habits to increase open and response rates, and set push frequency to avoid overly disturbing users while maintaining user attention;

[0036] S34: Personalize the content and expression of push information based on the user's specific electricity usage attributes and preferences. Test the effects of push content and form in a small range and make adjustments based on feedback;

[0037] S35: Send push information to users through the selected channels, and monitor the key indicators of push delivery rate, opening rate, and click rate in real time.

[0038] Preferably, the user feedback module includes a satisfaction unit and a usage unit.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention provides a system for targeted promotion of value-added service products. The system can deeply integrate basic power supply services and value-added service products, cross-border integrate upstream and downstream industrial chains, and create diversified service product packages. At the same time, by integrating data such as users' electricity usage habits and electricity characteristics, data analysis is performed and specific customer attribute categories are output, so as to achieve precise targeted push, improve the sales capacity of the power grid, and meet users' usage needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The system block diagram of the invention is used for the directional promotion system of value-added service products.

[0042] Figure 2 It is a flow chart of the data acquisition module of the present invention.

[0043] Figure 3 Flow chart of the data analysis module of the present invention.

[0044] Figure 4 It is a flow chart of the matching module of the present invention.

[0045] Figure 5 This is a flow chart of the push module of the present invention. DETAILED DESCRIPTION

[0046] 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.

[0047] See also Figures 1 to 5 , the present invention provides a technical solution: a system for directional promotion of value-added service products, the directional promotion system includes a data collection module, a data analysis module, a service product library, a feature output module, a matching module, a push module, and a user feedback module;

[0048] The data collection module is used to collect the user's electricity consumption data, which includes but is not limited to electricity consumption, electricity consumption time, electricity consumption frequency, and appliance type;

[0049] The data analysis module is used to process and analyze the collected data, identify the user's electricity usage habits and electricity characteristics, and form customer attribute categories;

[0050] The service product library includes information on various value-added service products, including peak and valley electricity price discounts, energy-saving consulting services, and smart home integration solutions;

[0051] The feature output module is used to output customer features based on data analysis results;

[0052] The matching module is used to match comprehensive electricity consumption attributes and service product characteristics to achieve precise and targeted push;

[0053] The push module is used to push the matching service product packages to users through the channels preferred by users;

[0054] The user feedback module is used to collect user feedback on the push service, which is used to optimize the matching algorithm and service quality. The user feedback module includes a satisfaction unit and a usage unit.

[0055] The specific method of using the data collection module in the value-added service product targeted promotion system includes the following steps:

[0056] S1: Install intelligent monitoring equipment in the user's electricity meter or distribution box, including a smart meter or a current sensor with data transmission function, so that the device can monitor and record the user's electricity consumption data in real time;

[0057] S2: Configure intelligent monitoring devices to send data to the cloud platform via wireless networks, using encryption technology to protect privacy and security during data transmission;

[0058] S3: The intelligent monitoring device automatically records the power consumption data at the set time interval;

[0059] S4: Before transmission to the cloud platform, the intelligent monitoring device performs preliminary processing on the data, including noise filtering and outlier detection, to reduce the amount of data transmission and improve the accuracy of subsequent analysis;

[0060] S5: The collected data is sent to the cloud platform through the established data communication link. On the server side, the data is stored in the database, waiting for further processing and analysis.

[0061] The data collection module can effectively collect users' electricity usage habits and electricity characteristic data, providing support for subsequent data analysis and targeted promotion of value-added service products.

[0062] The specific method of using the data analysis module in the value-added service product targeted promotion system includes the following steps:

[0063] S11: Analyze the user's electricity consumption cycle, which includes daily and weekly electricity consumption patterns, and identify peak and valley electricity consumption periods; infer the type of electrical appliances and load size used by the user through the fluctuation patterns of current and voltage; calculate the user's overall energy consumption and energy consumption in each period to evaluate energy efficiency;

[0064] S12: Use a hierarchical clustering algorithm to group users’ electricity usage behaviors and find user groups with similar electricity usage patterns;

[0065] S13: assigning labels to each user based on the results of the power consumption behavior analysis. The user-assigned labels include peak power users, night power users, and high energy consumption users. The users are divided into different categories, including economical, environmentally friendly, and convenient, based on their power consumption habits and preferences;

[0066] S14: Use historical electricity consumption data to build a prediction model to predict users' future electricity consumption trends and needs, and optimize the model through parameter adjustment methods to improve the accuracy of the prediction;

[0067] S15: Display the analysis results in the form of charts to facilitate understanding and communication, generate detailed analysis reports, summarize the key points of users' electricity consumption behavior and recommend strategies.

[0068] The data analysis module can deeply understand users' electricity consumption behavior, form accurate customer attribute categories, and provide data support for the subsequent targeted promotion of value-added service products.

[0069] The specific method of using the matching module in the value-added service product directional promotion system includes the following steps:

[0070] S21: receiving the customer's electricity consumption attribute characteristic data from the characteristic output module;

[0071] S22: Organize the available value-added service product catalog, which includes product features, target user groups, costs, and benefits, and extract the key features of each service product, which includes energy-saving performance, usage period optimization, and cost-effectiveness ratio;

[0072] S23: Select a rule-based matching algorithm based on customer characteristics and service product features, and use historical data to train the matching algorithm to improve matching accuracy;

[0073] S24: Input the customer's electricity usage attribute characteristics and service product characteristics into the matching algorithm. The algorithm calculates the matching degree between the customer and each service product. The matching degree takes into account factors including electricity usage habits, preferences, and product characteristics. The service products are ranked according to the matching degree, and the best matching product or product combination is selected.

[0074] S25: Evaluate the potential value of the matching results so that the recommended products meet the needs of users.

[0075] The matching module can effectively match the user's electricity usage attributes with the characteristics of service products, achieve precise and targeted push, and improve user satisfaction and the overall efficiency of the system.

[0076] The specific method of using the push module for the value-added service product targeted promotion system includes the following steps:

[0077] S31: Customizing push content based on the matching results, the push content includes details, advantages, and price information of the service product package;

[0078] S32: analyzing the user's preferred information receiving channels, which include email, SMS, mobile app notifications, and social media, and selecting a corresponding push channel based on the user's preference and the coverage efficiency of the channel;

[0079] S33: Determine the best time to push messages, taking into account user activity time and habits to increase open and response rates, and set push frequency to avoid overly disturbing users while maintaining user attention;

[0080] S34: Personalize the content and expression of push information based on the user's specific electricity usage attributes and preferences. Test the effects of push content and form in a small range and make adjustments based on feedback;

[0081] S35: Send push information to users through the selected channels, and monitor the key indicators of push delivery rate, opening rate, and click rate in real time.

[0082] The push module can effectively push matching service product packages to users through channels preferred by users, thereby increasing users' acceptance and interaction rate of pushed content, thereby achieving effective promotion of value-added service products.

[0083] In summary, the present invention provides a system for targeted promotion of value-added service products. The system can deeply integrate basic power supply services and value-added service products, cross-border integrate upstream and downstream industrial chains, and create diversified service product packages. At the same time, by integrating data such as users' electricity usage habits and electricity characteristics, data analysis is performed and specific customer attribute categories are output, so as to achieve precise targeted push, improve the sales capabilities of the power grid, and meet user needs.

[0084] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system for targeted promotion of value-added service products, characterized in that: The targeted promotion system includes a data collection module, a data analysis module, a service product library, a feature output module, a matching module, a push module, and a user feedback module; The data collection module is used to collect the user's electricity consumption data, which includes but is not limited to electricity consumption, electricity consumption time, electricity consumption frequency, and appliance type; The data analysis module is used to process and analyze the collected data, identify the user's electricity usage habits and electricity characteristics, and form customer attribute categories; The feature output module is used to output customer features according to the data analysis results; The matching module is used to match comprehensive electricity consumption attributes and service product characteristics to achieve precise and targeted push; The push module is used to push the matching service product packages to the user through the channel preferred by the user; The user feedback module is used to collect user feedback on the push service, so as to optimize the matching algorithm and service quality.

2. A system for targeted promotion of value-added service products according to claim 1, characterized in that: The specific method of using the data collection module in the value-added service product directional promotion system includes the following steps: S1: Install intelligent monitoring equipment in the user's electricity meter or distribution box, including a smart meter or a current sensor with data transmission function, so that the device can monitor and record the user's electricity consumption data in real time; S2: Configure intelligent monitoring devices to send data to the cloud platform via wireless networks, using encryption technology to protect privacy and security during data transmission; S3: The intelligent monitoring device automatically records the power consumption data at the set time interval; S4: Before transmission to the cloud platform, the intelligent monitoring device performs preliminary processing on the data, including noise filtering and outlier detection, to reduce the amount of data transmission and improve the accuracy of subsequent analysis; S5: The collected data is sent to the cloud platform through the established data communication link. On the server side, the data is stored in the database, waiting for further processing and analysis.

3. A system for targeted promotion of value-added service products according to claim 1, characterized in that: The specific method of using the data analysis module in the value-added service product directional promotion system includes the following steps: S11: Analyze the user's electricity consumption cycle and identify the peak and valley periods; infer the type of electrical appliances and load size used by the user through the fluctuation patterns of current and voltage; calculate the user's overall energy consumption and energy consumption in each period to evaluate energy efficiency; S12: Use a hierarchical clustering algorithm to group users’ electricity usage behaviors and find user groups with similar electricity usage patterns; S13: assigning labels to each user based on the results of the electricity usage behavior analysis, and classifying the users into different categories based on their electricity usage habits and preferences; S14: Use historical electricity consumption data to build a prediction model to predict users' future electricity consumption trends and needs, and optimize the model through parameter adjustment methods to improve the accuracy of the prediction; S15: Display the analysis results in the form of charts to facilitate understanding and communication, generate detailed analysis reports, summarize the key points of users' electricity consumption behavior and recommend strategies.

4. A system for targeted promotion of value-added service products according to claim 3, characterized in that: The electricity consumption cycle includes a daily electricity consumption mode and a weekly electricity consumption mode; user allocation tags include peak electricity users, nighttime electricity users, and high energy consumption users; user types include economical, environmentally friendly, and convenient.

5. A system for targeted promotion of value-added service products according to claim 1, characterized in that: The service product library includes information on various value-added service products, including peak and valley electricity price discounts, energy-saving consulting services, and smart home integration solutions.

6. A system for targeted promotion of value-added service products according to claim 1, characterized in that: The specific method of using the matching module in the value-added service product directional promotion system includes the following steps: S21: receiving the customer's electricity consumption attribute characteristic data from the characteristic output module; S22: Organize the available value-added service product catalog and extract the key features of each service product; S23: Select a rule-based matching algorithm based on customer characteristics and service product features, and use historical data to train the matching algorithm to improve matching accuracy; S24: Input the customer's electricity usage attribute characteristics and service product characteristics into the matching algorithm. The algorithm calculates the matching degree between the customer and each service product. The matching degree takes into account factors including electricity usage habits, preferences, and product characteristics. The service products are ranked according to the matching degree, and the best matching product or product combination is selected. S25: Evaluate the potential value of the matching results so that the recommended products meet the needs of users.

7. A system for targeted promotion of value-added service products according to claim 6, characterized in that: The value-added service product catalog includes product features, target user groups, costs, and benefits; the key characteristics of the service products include energy-saving performance, usage period optimization, and cost-effectiveness ratio.

8. A system for targeted promotion of value-added service products according to claim 1, characterized in that: The specific method of using the push module in the value-added service product directional promotion system includes the following steps: S31: Customizing push content based on the matching results, the push content includes details, advantages, and price information of the service product package; S32: analyzing the user's preferred information receiving channels, which include email, SMS, mobile app notifications, and social media, and selecting a corresponding push channel based on the user's preference and the coverage efficiency of the channel; S33: Determine the best time to push messages, taking into account user activity time and habits to increase open and response rates, and set push frequency to avoid overly disturbing users while maintaining user attention; S34: Personalize the content and expression of push information based on the user's specific electricity usage attributes and preferences. Test the effects of push content and form in a small range and make adjustments based on feedback; S35: Send push information to users through the selected channels, and monitor the key indicators of push delivery rate, opening rate, and click rate in real time.

9. A system for targeted promotion of value-added service products according to claim 1, characterized in that: The user feedback module includes a satisfaction unit and a usage unit.

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