Smart retail marketing platform system

Abstract

The invention relates to a smart retail marketing platform system which comprises a conversion module, an iterative optimization module, a content module, a channel integrated management module, an interaction module, an event identification module, a right service module and a marketing module. According to the invention, the conversion module, the iterative optimization module, the content module, the channel integration management module, the interaction module, the event identification module, the right and interest service module and the marketing module are integrated, so that the operation efficiency is improved, the operation cost is reduced, the marketing benefit is improved, the channel is expanded, the customer management is normalized, and the labor cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of retail marketing technology, and in particular to a smart retail marketing platform system. Background Art

[0002] At present, the problem facing the physical retail industry is the high operating costs: in the early stages of omni-channel construction, retail companies often have to face high operating costs, especially the operating costs of physical channels and the remuneration costs of social channels. Summary of the invention

[0003] The purpose of the present invention is to solve the problems existing in the prior art and provide a smart retail marketing platform system, which improves operational efficiency, reduces operating costs, improves marketing benefits, broadens channels, regulates customer management, and reduces labor costs by integrating a conversion module, an iterative optimization module, a content module, a channel integration management module, an interaction module, an event recognition module, a rights and interests service module, and a marketing module.

[0004] The present invention provides a smart retail marketing platform system, including a conversion module, an iterative optimization module, a content module, a channel integration management module, an interaction module, an event recognition module, a rights and interests service module and a marketing module;

[0005] The conversion module is used to extract user behavior data from the raw data, conduct product sales forecasts and inventory information management, and then convert it into labels;

[0006] Iteration optimization module, used for product life cycle management and product configuration management, supports product iteration and optimization;

[0007] Content module, used to create, edit and optimize display pages;

[0008] Channel integration management module, used for integration and management of retail business channels;

[0009] Interaction module, used to handle the interaction between customers and the system;

[0010] Event recognition module, used to identify events in user behavior;

[0011] Equity service module, used to manage and configure supporting services and additional service content;

[0012] The marketing module is used to plan, execute and evaluate marketing activities to achieve sales growth and improve customer satisfaction.

[0013] The conversion module includes a user behavior analysis unit, a commodity sales forecasting unit and an inventory management unit. The user behavior analysis unit is used to analyze the user's purchase history, browsing and clicking behavior, and generate labels of preference, activity and loyalty; the commodity sales forecasting unit is used to analyze historical sales data, market trends and promotional activities, and predict future sales; the inventory management unit is used to analyze the calculated inventory, sales speed and replenishment cycle, and optimize the inventory management strategy.

[0014] The steps of iteration and optimization of the product are:

[0015] S1. Clarify business requirements: determine the type of data required;

[0016] S2, data collection and preprocessing: collect raw data and clean, transform and remove duplicates;

[0017] S3, data integration: input data, processing logic and output results, and convert them into executable code;

[0018] S4, testing and optimization: test the accuracy and efficiency of the output results, and optimize according to the test results;

[0019] S5. Deploy the tested and optimized results to the conversion module and configure and monitor them.

[0020] The method for calculating the activity level corresponding to each user includes:

[0021] According to the user's consumption amount classification and consumption frequency classification, the corresponding classification value is calculated, and the classification value includes the amount value and the frequency value;

[0022] CX i =(SX i +SY i )*(∑ n j＝1 Z ij )

[0023] Where, CX i is the activity value corresponding to the i-th user, SX i is the amount of money of the i-th user, SY i is the consumption frequency value of the i-th user, MZ ij is the consumption amount of the jth consumption by the ith user, n is the number of consumptions by the ith user, j∈[1,n],i∈[1,m].

[0024] The interaction module includes a customer active behavior track collection unit, a customer passive interaction collection unit and a customer behavior data query unit; the customer passive interaction collection unit is used to collect customer usage tracks, customer interaction logs, and customer communication content; the customer behavior data query unit is used to query, share and integrate customer information; the customer active behavior track collection unit is used to collect customer active behavior tracks, and the steps for forming customer active behavior tracks are:

[0025] S1. Log in to the server. The customer logs in via a computer or mobile phone application.

[0026] S2, raise an event, the customer logs in and raises a demand;

[0027] S3, feedback result: after the customer service handles the customer event, the customer service returns the processing result through the channel selected by the customer;

[0028] S4. Analysis and optimization: Based on customer feedback and interaction data, conduct data analysis and optimize service processes.

[0029] The event identification module includes a data stream processing unit, an event detection unit and a resource allocation optimization unit. The data stream processing unit is used to receive and process data streams from various channels in real time, the event detection unit is used to define and trigger events, and the resource allocation optimization unit is used to optimize the allocation of server resources and human resources.

[0030] The event trigger probability formula is:

[0031] P(y=1∣x)=1+e-(β0+β1x1+β2x2+…+βn xn)1

[0032] Among them, P(y=1|x) is the probability of event triggering,

[0033] e is the natural logarithm,

[0034] x1, x2,…, xn are the characteristic variables of user behavior data,

[0035] β0,β1,β2,…,βn are model parameters.

[0036] The rights and interests service module includes a member rights and interests unit for reading and analyzing member consumption amounts and member rights and interests bonuses, a points redemption unit for converting points into currency or commodities, a discount unit for analyzing the amount saved or increased consumption amount by members using coupons on the platform, a rights and interests participation unit for analyzing user participation during specific rights and interests activities, a rights and interests satisfaction unit for analyzing user satisfaction, and a rights and interests ROI unit for analyzing the equity input-output ratio.

[0037] The marketing module includes a data collection and analysis unit for collecting and analyzing data on sales revenue, order quantity, number of customers and average order value, an evaluation unit for analyzing the marketing input-output ratio, conversion rate, average order value increase rate, marketing cost ratio and customer repurchase rate, a dynamic adjustment unit for adjusting marketing strategies and budget allocations, and an optimization unit for optimizing marketing strategies and marketing activities.

[0038] The computer device comprises a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the steps of the method described above are implemented.

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

[0040] The conversion module can more accurately extract information from user behavior, conduct sales forecasting and inventory management, and make smarter business decisions. The iterative optimization module helps track every stage of the product from design to elimination, ensuring that the product continues to meet market demand. The content module allows the creation and optimization of personalized content to increase user engagement and satisfaction. The channel integration management module can integrate multiple sales channels to ensure a consistent brand experience and efficient operations. The interaction module can improve customer service and increase customer satisfaction through automated and personalized interactions. The event recognition module helps analyze user behavior and identify key events to optimize user experience and business processes. The equity service module can provide and manage value-added services, increase customer loyalty and improve customer life cycle value. The marketing module can more effectively plan and execute marketing activities, evaluate the effectiveness of activities through data analysis, and thus increase sales and customer satisfaction. The entire solution improves operational efficiency and reduces labor costs through technical integration. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is a schematic diagram of the structure of the system of the present invention. DETAILED DESCRIPTION

[0042] The present invention will be further described below in conjunction with embodiments:

[0043] Example 1

[0044] like Figure 1 As shown, a smart retail marketing platform system described in the present invention includes a conversion module, an iterative optimization module, a content module, a channel integration management module, an interaction module, an event recognition module, a rights and interests service module and a marketing module;

[0045] The conversion module is used to extract user behavior data from the raw data, conduct product sales forecasts and inventory information management, and then convert it into labels;

[0046] Iteration optimization module, used for product life cycle management and product configuration management, supports product iteration and optimization;

[0047] Content module, used to create, edit and optimize display pages;

[0048] The channel integration management module is used to integrate and manage retail business channels; the channel integration management module integrates self-service channels, employee channels and third-party channels to achieve full-channel coverage of retail business.

[0049] Interaction module, used to handle the interaction between customers and the system;

[0050] Event recognition module, used to identify events in user behavior;

[0051] Equity service module, used to manage and configure supporting services and additional service content;

[0052] The marketing module is used to plan, execute and evaluate marketing activities to achieve sales growth and improve customer satisfaction.

[0053] The conversion module includes a user behavior analysis unit, a product sales forecasting unit and an inventory management unit. The user behavior analysis unit is used to analyze the user's purchase history, browsing and clicking behavior, and generate labels of preference, activity and loyalty, so as to provide customers with more personalized services and product recommendations.

[0054] The calculation method of each user's corresponding activity includes

[0055] According to the user's consumption amount classification and consumption frequency classification, the corresponding classification value is calculated, and the classification value includes the amount value and the frequency value;

[0056] CX i =(SX i +SY i )*(∑ n j＝1 Z ij )

[0057] Where, CX i is the activity value corresponding to the i-th user, SX i is the amount of money of the i-th user, SY i is the consumption frequency value of the i-th user, MZ ij is the consumption amount of the jth consumption of the i-th user, n is the number of consumptions of the i-th user, j∈[1,n],i∈[1,m]. The calculation method of user preference and loyalty is the same as that of activity.

[0058] The commodity sales forecasting unit is used to analyze historical sales data, market trends and promotional activities, and predict future sales, thereby improving the foresight and accuracy of inventory management and sales strategies. The inventory management unit is used to analyze the calculated inventory volume, sales speed and replenishment cycle, optimize inventory management strategies, enable enterprises to reduce inventory backlogs, avoid out-of-stock situations, and improve inventory turnover. The conversion module reduces manual operations through automation and data analysis, improves the efficiency of operational processes, and helps enterprises make more data-driven decisions.

[0059] The steps for product iteration and optimization are:

[0060] S1. Clarify business requirements and determine the type of data required. By clarifying business requirements, you can focus on solving the most critical problems and improve the relevance and efficiency of the project.

[0061] S2. Data collection and preprocessing: collect raw data and clean, convert and deduplicate them; thus ensuring the accuracy and reliability of the data and providing a high-quality data foundation for subsequent analysis.

[0062] S3, data integration, input data, processing logic and output results, and convert them into executable code; the data integration step helps to standardize the data processing process, making data processing more systematic and automated. Converting the processing logic into executable code improves the readability and maintainability of the code.

[0063] S4. Testing and optimization: test the accuracy and efficiency of the output results, optimize according to the test results, and find and fix problems in time.

[0064] S5. Deploy the test and optimization results to the conversion module, and configure and monitor them. Post-deployment configuration and monitoring help track product performance in real time and respond quickly to possible problems.

[0065] Through continuous iteration and optimization, products can better meet customer needs and improve customer satisfaction. At the same time, they can quickly respond to market changes and customer needs to enhance the market competitiveness of products. The clear steps of the entire iteration and optimization process help improve project transparency and facilitate team members to understand and track.

[0066] Product life cycle management includes creativity, release, listing, delisting, and expiration. Product life cycle management covers every stage of the product. Through the creative stage, the product is created from scratch and forms a preliminary concept and plan. Subsequently, the product enters the release stage and officially debuts on the market to be tested by consumers. In the listing stage, the product is officially pushed to the sales channel and sales begin. With market feedback and product performance, the product may go through the delisting stage and exit the market, or reach the end of its life in the expiration stage.

[0067] Product configuration management includes basic products, combination products and promotional products. Basic products: As the basis of product configuration, basic products represent the core product lines and basic functions of the enterprise. These products are the cornerstone of the enterprise's competitiveness and the basis for subsequent product development and combination. Combination products: Based on the basic products, enterprises can combine different products according to market demand and consumer preferences to form combination products with specific functions and advantages. This flexible combination method helps enterprises respond quickly to market changes and launch new products that meet consumer needs. Promotional products: In order to increase sales and market share, enterprises can also design promotional products. These products usually have a higher cost-effectiveness or more attractive preferential conditions to attract consumers' attention and purchase.

[0068] The content module includes a component drag unit, a content configuration unit, a template unit, a navigation unit, an operation unit, an AI-assisted design unit, and a material management unit. The component drag unit is used by users to add the required components to the page by simply dragging and dropping. This method greatly improves the efficiency and flexibility of page production. The content configuration unit is used to configure the components in detail, including setting pictures, text content, font style, font color, font size, and animation effects, so that users can accurately control the display effect of the page to meet different design requirements. The template unit has page templates, including product information display page, activity display page, and marketing promotion page, which are used for customers to choose according to their needs, thereby improving the efficiency of page production and ensuring the professionalism and consistency of page design. The navigation unit is used to drag and drop the navigation bar. Users can freely set the style, position, and content of the navigation bar according to the page structure and user habits, thereby improving the user experience and the convenience of page navigation. The operation unit is used to display advertising and promotional information, allowing users to set the position, size, style, and content of the operation position as needed to achieve precision marketing and brand promotion. The AI-assisted design unit is used to help users expand text content and help users complete page design work more efficiently. The material management unit is used to uniformly manage and approve image materials and slogans, ensuring the accuracy and compliance of page content while improving the efficiency of team collaboration.

[0069] The interaction module includes a customer active behavior track collection unit, a customer passive interaction collection unit, and a customer behavior data query unit; the customer passive interaction collection unit is used to collect customer usage tracks, customer interaction logs, and customer communication content; the customer behavior data query unit is used to query, share, and integrate customer information; the customer active behavior track collection unit is used to collect customer active behavior tracks. Through the customer behavior data query unit and the customer active behavior track collection unit, the enterprise can have a deeper understanding of the customer's purchase preferences, activity, and loyalty, so as to provide customers with more personalized services and product recommendations. The customer passive interaction collection unit can collect the customer's usage tracks and communication content, which helps to improve the quality and efficiency of customer support, thereby improving the customer experience.

[0070] The steps to form a customer's active behavior trajectory are:

[0071] S1. Customer login: Customers log in via computer or mobile application;

[0072] S2. Raising an event: After logging in, customers can inquire about product information, complain about service quality, or make suggestions. These events will be recorded by the system and serve as the basis for subsequent processing;

[0073] S3. Feedback results: After handling the customer event, the customer service will return the processing results through the channel selected by the customer to ensure that the customer can understand the processing progress and results in a timely manner;

[0074] S4. Analysis and optimization: Based on customer feedback and interaction data, data analysis is performed to optimize service processes. Based on customer feedback and interaction data, service processes can be continuously optimized to improve service response speed and quality.

[0075] The event recognition module includes a data stream processing unit, an event detection unit, and a resource allocation optimization unit. The data stream processing unit is used to receive and process data streams from various channels in real time, thereby improving the speed and efficiency of data processing. The event detection unit is used to define and trigger events, so that the system can respond quickly to the events that occur. The resource allocation optimization unit is used to optimize the allocation of server resources and human resources, thereby improving the rationality and efficiency of resource use.

[0076] The event trigger probability formula is:

[0077] P(y=1∣x)=1+e-(β0+β1x1+β2x2+…+βnxn)1

[0078] Among them, P(y=1|x) is the probability of event triggering,

[0079] e is the natural logarithm,

[0080] x1, x2,…, xn are the characteristic variables of user behavior data,

[0081] β0,β1,β2,…,βn are model parameters.

[0082] The equity service module includes a member equity unit for reading and analyzing member consumption amounts and member equity bonuses, a point redemption unit for converting points into currency or goods, a discount unit for analyzing the amount saved or increased consumption amount by members using coupons on the platform, a rights participation unit for analyzing user participation during specific equity activities, a rights satisfaction unit for analyzing user satisfaction, and a rights ROI unit for analyzing the equity input-output ratio. Through the member equity unit and the rights satisfaction unit, enterprises can better understand the needs and satisfaction of members, thereby providing more personalized services and enhancing customer loyalty. The point redemption unit and the discount unit can encourage customers to exchange points for currency or goods, as well as use coupons. These measures can increase customer activity and stickiness. The equity participation unit can help enterprises analyze user participation during specific equity activities, thereby optimizing marketing activities and improving the effectiveness of activities. By analyzing the equity input-output ratio through the equity ROI unit, enterprises can allocate resources more reasonably and improve the efficiency of resource use. The overall implementation of the equity service module helps enterprises better meet customer needs and stand out in the fierce market competition.

[0083] The marketing module includes a data collection and analysis unit for collecting and analyzing data on sales revenue, number of orders, number of customers, and average order value; an evaluation unit for analyzing marketing input-output ratio, conversion rate, average order value increase rate, marketing cost ratio, and customer repurchase rate; a dynamic adjustment unit for adjusting marketing strategies and budget allocations; and an optimization unit for optimizing marketing strategies and marketing activities. Through the data collection and analysis unit, enterprises can obtain detailed data on sales, orders, and number of customers, providing solid data support for decision-making. The evaluation unit can analyze the marketing input-output ratio and conversion rate, help enterprises understand the effectiveness of marketing activities, and adjust strategies accordingly to improve efficiency. The dynamic adjustment unit allows enterprises to adjust marketing budgets and resource allocations based on real-time data to ensure that resources are used effectively and invest in the most valuable market opportunities.

[0084] The description of the direction and relative position relationship of the structure in the present invention, such as the description of front, back, left, right, up, and down, does not constitute a limitation of the present invention, but is only for the convenience of description.

Claims

1. A smart retail marketing platform system, characterized in that: It includes conversion module, iterative optimization module, content module, channel integration management module, interaction module, event identification module, equity service module and marketing module; The conversion module is used to extract user behavior data from the raw data, conduct product sales forecasts and inventory information management, and then convert it into labels; Iteration optimization module, used for product life cycle management and product configuration management, supports product iteration and optimization; Content module, used to create, edit and optimize display pages; Channel integration management module, used for integration and management of retail business channels; Interaction module, used to handle the interaction between customers and the system; Event recognition module, used to identify events in user behavior; Equity service module, used to manage and configure supporting services and additional service content; The marketing module is used to plan, execute and evaluate marketing activities to achieve sales growth and improve customer satisfaction.

2. The smart retail marketing platform system according to claim 1, characterized in that: The conversion module includes a user behavior analysis unit, a commodity sales forecasting unit, and an inventory management unit. The user behavior analysis unit is used to analyze the user's purchase history, browsing and clicking behavior, and generate labels for preference, activity, and loyalty; The commodity sales forecasting unit is used to analyze historical sales data, market trends and promotional activities to predict future sales; The inventory management unit is used to analyze and calculate inventory levels, sales speeds, and replenishment cycles to optimize inventory management strategies.

3. The smart retail marketing platform system according to claim 2, characterized in that: The calculation method of each user's corresponding activity includes According to the user's consumption amount classification and consumption frequency classification, the corresponding classification value is calculated, and the classification value includes the amount value and the frequency value; CX i =(SX i +AND i )*(∑n j =1MZ ij ) Where, CX i is the activity value corresponding to the i-th user, SX i is the amount of money of the i-th user, SY i is the consumption frequency value of the i-th user, MZ ij is the consumption amount of the jth consumption by the ith user, n is the number of consumptions by the ith user, j∈[1,n],i∈[1,m].

4. The smart retail marketing platform system according to claim 1, characterized in that: The steps for product iteration and optimization are: S1. Clarify business requirements: determine the type of data required; S2, data collection and preprocessing: collect raw data and clean, transform and remove duplicates; S3, data integration: input data, processing logic and output results, and convert them into executable code; S4, testing and optimization: test the accuracy and efficiency of the output results, and optimize according to the test results; S5. Deploy the tested and optimized results to the conversion module and configure and monitor them.

5. A smart retail marketing platform system according to any one of claims 1-4, characterized in that: The interaction module includes a customer active behavior track collection unit, a customer passive interaction collection unit and a customer behavior data query unit; the customer passive interaction collection unit is used to collect customer usage tracks, customer interaction logs and customer communication content; The customer behavior data query unit is used to query, share and integrate customer information; the customer active behavior track collection unit is used to collect customer active behavior tracks. The steps for forming customer active behavior tracks are: S1. Log in to the server. The customer logs in via a computer or mobile phone application. S2, raise an event, the customer logs in and raises a demand; S3, feedback result: after the customer service handles the customer event, the customer service returns the processing result through the channel selected by the customer; S4. Analysis and optimization: Based on customer feedback and interaction data, conduct data analysis and optimize service processes.

6. The smart retail marketing platform system according to claim 5, characterized in that: The event identification module includes a data stream processing unit, an event detection unit and a resource allocation optimization unit. The data stream processing unit is used to receive and process data streams from various channels in real time. The event detection unit is used to define and trigger events. The resource allocation optimization unit is used to optimize the allocation of server resources and human resources.

7. The smart retail marketing platform system according to claim 6, characterized in that: The event trigger probability formula is: P(y=1∣x)=1+e-(β0+β1 x1 +β2 x2+…+βnxn )1 Among them, P(y=1|x) is the probability of event triggering, e is the natural logarithm, x1, x2,…, xn are the characteristic variables of user behavior data, β0,β1,β2,…,βn are model parameters.

8. The smart retail marketing platform system according to claim 7, characterized in that: The rights and interests service module includes a member rights and interests unit for reading and analyzing member consumption amounts and member rights and interests bonuses, a points redemption unit for converting points into currency or goods, a discount unit for analyzing the amount saved or increased consumption amount by members using coupons on the platform, a rights and interests participation unit for analyzing user participation during specific rights and interests activities, a rights and interests satisfaction unit for analyzing user satisfaction, and a rights and interests ROI unit for analyzing the equity input-output ratio.

9. The smart retail marketing platform system according to claim 8, characterized in that: The marketing module includes a data collection and analysis unit for collecting and analyzing data on sales revenue, order quantity, number of customers and average order value; an evaluation unit for analyzing the marketing input-output ratio, conversion rate, average order value increase rate, marketing cost ratio and customer repurchase rate; a dynamic adjustment unit for adjusting marketing strategies and budget allocations; and an optimization unit for optimizing marketing strategies and marketing activities.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When a processor executes the computer program, the steps of the method according to any one of claims 1 to 9 are implemented.

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