Electronic commerce integrated order management system

Abstract

The invention provides an e-commerce integrated order management system, and relates to the technical field of e-commerce, and the system comprises an order processing module which is used for receiving, splitting, merging and updating order states, automatically optimizing order circulation, improving the order processing efficiency, guaranteeing the real-time synchronization of the order states, and reducing the processing delay. In the invention, the data analysis module analyzes user behavior data (such as browsing, purchasing and returning) and market sales data in real time and predicts future commodity demands and sales trends by using the prediction model, and the system can automatically provide a real-time report for an operation team based on the data, so that the user experience is improved. The module helps to adjust the inventory replenishment cycle, sales promotion activities and commodity shelving plans, and has the core advantages that market changes are identified through big data analysis, response measures are automatically generated, the inventory management precision is improved, and the inventory overstock and stockout conditions are reduced.

Description

Technical Field

[0001] This invention relates to the field of e-commerce technology, and more specifically, to an integrated e-commerce order management system. Background Technology

[0002] E-commerce is the trading of goods or services via the internet. It enables consumers and merchants to transact across time and space. E-commerce is not limited to buying and selling goods; it also includes online payment, logistics and delivery, customer service, and information exchange. With the development of internet technology, e-commerce has become an important part of the global economy, providing a convenient, efficient, and low-cost trading method. Modern e-commerce platforms greatly enhance user experience and promote market globalization and digital transformation of businesses through personalized recommendations, real-time inventory management, flexible payment options, and optimized logistics and delivery systems.

[0003] Traditional inventory management systems largely rely on static data, making it difficult to accurately reflect actual demand. Sales forecasts also lack real-time analysis, resulting in significant discrepancies between forecasts and actual demand. Furthermore, existing systems are inefficient in order processing and logistics, failing to effectively consolidate orders, increasing delivery costs and impacting customer experience. Payment and settlement processes are cumbersome, and refund processing is inefficient. Finally, many systems lack data-driven decision support functions, leading to delays or errors in operational decisions.

[0004] Therefore, we have made improvements to this and proposed an integrated e-commerce order management system. Summary of the Invention

[0005] The purpose of this invention is to provide an integrated e-commerce order management system, which solves the problem that in the prior art, once products are listed, there is a lack of continuous dynamic monitoring, which leads to the reliance on manual statistics and intervention for changes in sales, inventory turnover rate and market demand. This is not only cumbersome but also prone to errors. This manual management method cannot respond to market changes in a timely manner, resulting in problems such as inventory backlog or stockouts.

[0006] The application is as follows:

[0007] An integrated e-commerce order management system, comprising:

[0008] The order processing module is used to receive, split, merge, and update order status, automatically optimize order flow, improve order processing efficiency, ensure real-time synchronization of order status, and reduce processing delays.

[0009] The inventory management module is used to monitor inventory levels in real time and automatically adjust replenishment strategies based on historical sales data and market fluctuation trends to reduce stockouts or overstocking and improve inventory utilization.

[0010] The product lifecycle management module is used to monitor the entire process of products from listing, selling to delisting, and automatically generate product update or promotional strategies based on product sales, inventory turnover rate, market demand, etc.

[0011] The payment and settlement module supports multiple payment methods and provides an automatic refund mechanism to simplify the payment process and improve the user payment experience.

[0012] The logistics optimization module automatically optimizes delivery routes based on order volume, delivery requirements, and warehouse location, reducing cross-regional logistics costs, improving transportation efficiency, and supporting the combined delivery of batch orders.

[0013] The data analytics module is used to analyze user behavior, generate data reports, and predict future product demand, helping the operations department optimize the supply chain and marketing strategies.

[0014] As a preferred technical solution of this application, the product lifecycle management module dynamically adjusts the product strategy through the following formula, wherein Formula 1 is the formula for calculating inventory turnover rate:

[0015]

[0016] Among them, S t I represents the number of goods sold within time period t. t The formula represents the ending inventory quantity for time period t, where n is the number of time periods considered. This formula takes into account the relationship between sales volume and inventory quantity for each time period, reflects the sales efficiency of the product, and helps merchants dynamically adjust their inventory management strategies based on actual sales conditions.

[0017] And based on changes in market demand, use Formula 2 for demand forecasting:

[0018] D t+1 =α·D t +(1-α)·D t-1 +β·(S t -I t )

[0019] Among them, D t D represents the actual demand at time t. t+1 This represents the predicted demand at time t+1, where α is the smoothing coefficient (0 < α < 1), β is the adjustment coefficient, and S t For sales volume, I t By combining historical demand data, sales volume, and inventory status, demand forecasting models can more accurately predict future demand changes, assisting merchants in making more precise product updates, promotions, and inventory management.

[0020] As a preferred technical solution of this application, the order processing module includes:

[0021] Order consolidation and logistics optimization: The system can automatically consolidate multiple orders from the same user, reducing logistics dispersion and improving delivery efficiency;

[0022] Real-time order status synchronization: Supports real-time synchronization and updates of order status, ensuring that customers can always obtain order processing progress information and providing transparent order status tracking.

[0023] As a preferred technical solution of this application, the inventory management module includes:

[0024] Dynamic inventory adjustment: The system combines historical sales data, market fluctuation trends and supply chain conditions to dynamically adjust the inventory replenishment cycle, avoid stockouts, excessive stockpiling or capital occupation, and ensure inventory liquidity and product availability.

[0025] Supply chain optimization: Integrate with supplier systems to enable automatic replenishment, ensuring sufficient supply of goods, avoiding delays caused by manual operation, and providing inventory early warning function to prevent the risk of supply chain disruption in advance.

[0026] As a preferred technical solution of this application, the payment settlement module includes:

[0027] Intelligent payment method selection: The system supports multiple payment methods and can automatically select the optimal payment method based on the order amount, payment platform, and user payment preferences.

[0028] Automatic Refund Mechanism: Provides an automatic refund mechanism to simplify and speed up the refund process and improve the payment experience.

[0029] As a preferred technical solution of this application, the data analysis module includes:

[0030] User behavior analysis: Based on user browsing, purchasing, and return behavior data, generate detailed reports to help analyze user behavior;

[0031] Market demand forecasting: By combining external market data, we can predict future demand for goods and help the operations team to accurately optimize the product supply chain and reduce inventory backlog and stockouts.

[0032] As a preferred technical solution of this application, the product lifecycle management module includes:

[0033] Sales fluctuations and promotional triggers: Automatically trigger promotional or clearance strategies based on product sales trends to ensure product market competitiveness;

[0034] Product flow optimization: Improve product flow efficiency through automated processes to ensure product sales continuity.

[0035] As a preferred technical solution of this application, the logistics optimization module includes:

[0036] Consolidated delivery of bulk orders: The system supports consolidated delivery of bulk orders and selects the most suitable warehouse for distribution based on the user's location;

[0037] Cross-regional delivery optimization: By optimizing delivery routes, the time and cost of cross-regional delivery are reduced, while logistics efficiency is improved.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0039] In the scheme of this application:

[0040] This invention provides an integrated e-commerce order management system that significantly improves inventory management efficiency, sales forecast accuracy, and user experience through various technologies such as a product lifecycle management module and a data analysis module. Specifically, after a product is listed, the product lifecycle management module continuously monitors its sales data and inventory status, automatically calculates inventory turnover rate, and combines it with market demand data to generate optimized replenishment strategies. The system automatically adjusts inventory and promotional plans to avoid overstocking or stockouts due to surging demand. This module ensures optimal sales performance of products throughout their entire lifecycle through real-time data feedback and enhances their market competitiveness through precise promotional strategies. The data analysis module performs real-time analysis of user behavior data (such as browsing, purchasing, and returns) and market sales data, using predictive models to predict future product demand and sales trends. Based on this data, the system can automatically provide real-time reports to the operations team, helping to adjust inventory replenishment cycles, promotional activities, and product listing plans. The core advantage of this module lies in identifying market changes through big data analysis, automatically generating response measures, improving the accuracy of inventory management, and reducing inventory backlogs and stockouts. Attached Figure Description

[0041] Figure 1 This application provides a schematic diagram of the overall process of an integrated e-commerce order management system.

[0042] Figure 2 A flowchart illustrating the product lifecycle module and data analysis module of an integrated e-commerce order management system provided in this application;

[0043] Figure 3 A schematic diagram of the module flow of an integrated e-commerce order management system provided in this application. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0045] Therefore, the following detailed description of embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely illustrates some embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0046] It should be noted that, unless otherwise specified, the embodiments and features and technical solutions in the present invention can be combined with each other.

[0047] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0048] In the description of this invention, it should be noted that the terms "upper," "lower," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use, or the orientation or positional relationship commonly understood by those skilled in the art. These terms are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. In addition, the terms "first," "second," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0049] Please see Figures 1 to 3 This invention provides a technical solution: an integrated e-commerce order management system, comprising:

[0050] The order processing module is used to receive, split, merge, and update order status, automatically optimize order flow, improve order processing efficiency, ensure real-time synchronization of order status, and reduce processing delays.

[0051] The inventory management module is used to monitor inventory levels in real time and automatically adjust replenishment strategies based on historical sales data and market fluctuation trends to reduce stockouts or overstocking and improve inventory utilization.

[0052] The product lifecycle management module is used to monitor the entire process of products from listing, selling to delisting, and automatically generate product update or promotional strategies based on product sales, inventory turnover rate, market demand, etc.

[0053] The payment and settlement module supports multiple payment methods and provides an automatic refund mechanism to simplify the payment process and improve the user payment experience.

[0054] The logistics optimization module automatically optimizes delivery routes based on order volume, delivery requirements, and warehouse location, reducing cross-regional logistics costs, improving transportation efficiency, and supporting the combined delivery of batch orders.

[0055] The data analytics module is used to analyze user behavior, generate data reports, and predict future product demand, helping the operations department optimize the supply chain and marketing strategies.

[0056] like Figure 2 As shown, in a preferred embodiment, based on the above method, the product lifecycle management module further dynamically adjusts the product strategy using the following formula, where Formula 1 is the inventory turnover rate calculation formula:

[0057]

[0058] Among them, S t I represents the number of goods sold within time period t. t The formula represents the ending inventory quantity for time period t, where n is the number of time periods considered. This formula takes into account the relationship between sales volume and inventory quantity for each time period, reflects the sales efficiency of the product, and helps merchants dynamically adjust their inventory management strategies based on actual sales conditions.

[0059] And based on changes in market demand, the demand forecasting formula is as follows:

[0060] D t+1 =α·D t +(1-α)·D t-1 +β·(S t -I t )

[0061] Among them, D t D represents the actual demand at time t. t+1 This represents the predicted demand at time t+1, where α is the smoothing coefficient (0 < α < 1), β is the adjustment coefficient, and S t For sales volume, I tFor inventory levels, by combining historical demand data, sales volume, and inventory status, the demand forecasting model can more accurately predict future demand changes, assisting merchants in making more precise product updates, promotions, and inventory management. The formula calculates inventory turnover rate based on the sales volume and ending inventory of products within a certain period. Inventory turnover rate reflects the sales efficiency and inventory utilization of products. By quantitatively analyzing the relationship between sales volume and inventory, merchants can dynamically adjust their inventory management strategies based on actual sales. For example, if the inventory turnover rate of a certain product is low, the system can prompt the merchant to adjust the replenishment strategy or launch promotional activities to avoid inventory backlog.

[0062] like Figure 3 As shown, in a preferred embodiment, based on the above method, the order processing module further includes:

[0063] Order consolidation and logistics optimization: The system can automatically consolidate multiple orders from the same user, reducing logistics dispersion and improving delivery efficiency;

[0064] Real-time order status synchronization: Supports real-time synchronization and updates of order status, ensuring that customers can always obtain order processing progress information, providing transparent order status tracking, reducing logistics dispersion, optimizing delivery efficiency, and lowering transportation costs by automatically merging multiple orders from the same user. At the same time, the system supports real-time synchronization of order status, ensuring that customers can view order progress at any time, providing transparent tracking information, improving customer experience and order processing efficiency.

[0065] like Figure 3 As shown, in a preferred embodiment, based on the above method, the inventory management module further includes:

[0066] Dynamic inventory adjustment: The system combines historical sales data, market fluctuation trends and supply chain conditions to dynamically adjust the inventory replenishment cycle, avoid stockouts, excessive stockpiling or capital occupation, and ensure inventory liquidity and product availability.

[0067] Supply Chain Optimization: By integrating with supplier systems, automatic replenishment ensures sufficient supply of goods, avoids delays caused by manual operations, and provides inventory alerts to proactively prevent supply chain disruptions. Inventory operations are optimized through two core functions: First, dynamic inventory adjustment combines historical sales data, market fluctuations, and supply chain conditions to adjust replenishment cycles in real time, ensuring neither excess nor shortage of inventory, avoiding capital tied up and inventory buildup, and maintaining inventory liquidity and product availability. Second, the supply chain optimization function, through integration with supplier systems, enables automatic replenishment, ensuring timely inventory replenishment and avoiding supply shortages caused by delays due to manual operations. Simultaneously, the system provides inventory alerts to identify potential supply chain risks in advance, thereby reducing stockouts and ensuring operational stability.

[0068] like Figure 3 As shown, in a preferred embodiment, based on the above method, the payment settlement module further includes:

[0069] Intelligent payment method selection: The system supports multiple payment methods and can automatically select the optimal payment method based on the order amount, payment platform, and user payment preferences.

[0070] Automatic Refund Mechanism: This mechanism simplifies and accelerates the refund process, enhancing the payment experience. It optimizes the payment experience through two main functions: intelligent payment method selection, which supports multiple payment methods and automatically selects the most suitable one based on order amount, payment platform, and user preferences, thus improving convenience and efficiency; and the automatic refund mechanism, which simplifies the refund process by quickly and automatically processing refund requests, reducing manual intervention, accelerating refund speed, and improving customer satisfaction and payment experience.

[0071] like Figure 3 As shown, in a preferred embodiment, based on the above method, the data analysis module further includes:

[0072] User behavior analysis: Based on user browsing, purchasing, and return behavior data, generate detailed reports to help analyze user behavior;

[0073] Market Demand Forecasting: By combining external market data, this feature forecasts future product demand, helping operations teams to precisely optimize the product supply chain, reduce inventory backlog and stockouts. It supports operational optimization through two functions: User Behavior Analysis, which collects and analyzes user browsing, purchasing, and return behavior data to generate detailed reports, helps merchants gain a deeper understanding of user preferences and consumption trends, providing data support for accurate market decisions; and Market Demand Forecasting, which combines external market data to analyze future product demand trends, helping operations teams adjust supply chain strategies, reduce inventory backlog and stockouts, thereby improving inventory management efficiency and sales effectiveness.

[0074] like Figure 3 As shown, in a preferred embodiment, based on the above method, the product lifecycle management module further includes:

[0075] Sales fluctuations and promotional triggers: Automatically trigger promotional or clearance strategies based on product sales trends to ensure product market competitiveness;

[0076] Product Flow Optimization: By automating processes, product flow efficiency is improved, ensuring continuous sales. Two functions optimize product management and sales: the sales volume change and promotion triggering function automatically triggers promotions or clearance strategies based on product sales trends, ensuring product competitiveness in the market and avoiding sales stagnation; and product flow optimization improves product flow efficiency through automated processes, ensuring continuous sales, avoiding inventory backlog or sales interruptions, and maintaining product market activity.

[0077] like Figure 3 As shown, in a preferred embodiment, based on the above method, the logistics optimization module further includes:

[0078] Consolidated delivery of bulk orders: The system supports consolidated delivery of bulk orders and selects the most suitable warehouse for distribution based on the user's location;

[0079] Cross-regional delivery optimization: By optimizing delivery routes, the time and cost of cross-regional delivery are reduced, while logistics efficiency is improved. Two functions enhance delivery efficiency: the batch order consolidation delivery function allows multiple orders from the same user to be merged, optimizing the delivery process, and selecting the most suitable warehouse based on the user's location for distribution, reducing delivery time and cost; the cross-regional delivery optimization function intelligently optimizes delivery routes, reducing the time and cost of cross-regional delivery, thereby improving overall logistics efficiency and ensuring fast and low-cost delivery services.

[0080] Specifically, when this integrated e-commerce order management system is in operation: the product lifecycle management module monitors changes in product sales and inventory turnover, dynamically adjusts product strategies, and automatically triggers promotions or clearance activities based on changes in product sales trends to ensure that products remain competitive in the market. At the same time, it optimizes product flow through automated processes, improves the continuity of product sales, avoids inventory backlog or sales stagnation, ensures that products are always in the best sales condition, and ultimately improves operational efficiency and market responsiveness.

[0081] After receiving an order, the order processing module first receives the order and splits it according to the needs. Then, the system automatically merges multiple orders from the same user into one delivery order, reducing logistics dispersion and improving delivery efficiency. The system updates the order status in real time to ensure that customers can get the order processing progress at any time and provides transparent order status tracking, improving user experience and order processing efficiency.

[0082] The inventory management module monitors inventory levels in real time, combines historical sales data and market fluctuation trends to dynamically adjust replenishment cycles, ensure inventory liquidity, and avoid stockouts or overstocking. The system connects with supplier systems to achieve automatic replenishment, ensuring sufficient inventory and avoiding stockouts caused by delays in manual operations. It also provides an inventory early warning function to prevent supply chain risks in advance and ensure operational stability.

[0083] The payment and settlement module supports multiple payment methods. The system will automatically select the most suitable payment method based on the order amount, payment platform, and user payment preferences to improve payment convenience and efficiency. At the same time, it provides an automatic refund mechanism to simplify the refund process, speed up the refund process, ensure a smooth payment experience, and reduce user waiting time.

[0084] The logistics optimization module consolidates and delivers orders in batches. The system processes multiple orders together, selects the most suitable warehouse based on the user's geographical location for distribution, optimizes delivery routes, and reduces time and costs. At the same time, the system optimizes cross-regional delivery to ensure the efficiency of cross-regional delivery, further improving logistics efficiency and reducing operating costs.

[0085] The data analytics module generates detailed user behavior reports by analyzing user behavior data (browsing, purchasing, returns, etc.), helping merchants gain a deeper understanding of user consumption trends and preferences, and supporting optimized decision-making. Combined with external market data, the system predicts future product demand trends, helping operations teams accurately adjust product supply chain strategies, reduce inventory backlogs and stockouts, and ensure stable product sales.

[0086] The above embodiments are only used to illustrate the present invention and are not intended to limit the technical solutions described herein. Although the present invention has been described in detail with reference to the above embodiments, the present invention is not limited to the specific embodiments described above. Therefore, any modifications or equivalent substitutions to the present invention, as well as all technical solutions and improvements that do not depart from the spirit and scope of the invention, are covered within the scope of the claims of the present invention.

Claims

1. An integrated e-commerce order management system, characterized in that, include: The order processing module is used to receive, split, merge, and update order status, automatically optimize order flow, improve order processing efficiency, ensure real-time synchronization of order status, and reduce processing delays. The inventory management module is used to monitor inventory levels in real time and automatically adjust replenishment strategies based on historical sales data and market fluctuation trends to reduce stockouts or overstocking and improve inventory utilization. The product lifecycle management module is used to monitor the entire process of products from listing, selling to delisting, and automatically generate product update or promotional strategies based on product sales, inventory turnover rate, market demand, etc. The payment and settlement module supports multiple payment methods and provides an automatic refund mechanism to simplify the payment process and improve the user payment experience. The logistics optimization module automatically optimizes delivery routes based on order volume, delivery requirements, and warehouse location, reducing cross-regional logistics costs, improving transportation efficiency, and supporting the combined delivery of batch orders. The data analytics module is used to analyze user behavior, generate data reports, and predict future product demand, helping the operations department optimize the supply chain and marketing strategies.

2. The integrated e-commerce order management system according to claim 1, characterized in that, The product lifecycle management module dynamically adjusts product strategies using the following formula, where Formula 1 is the inventory turnover rate calculation formula: Among them, S t I represents the number of goods sold within time period t. t The formula represents the ending inventory quantity for time period t, where n is the number of time periods considered. This formula takes into account the relationship between sales volume and inventory quantity for each time period, reflects the sales efficiency of the product, and helps merchants dynamically adjust their inventory management strategies based on actual sales conditions. And based on changes in market demand, use Formula 2 for demand forecasting: D t+1 =α·D t +(1-a)·D t-1 +β·(S t -I t ) Among them, D t D represents the actual demand at time t. t+1 This represents the predicted demand at time t+1, where α is the smoothing coefficient (0 < α < 1), β is the adjustment coefficient, and S t For sales volume, I t By combining historical demand data, sales volume, and inventory status, demand forecasting models can more accurately predict future demand changes, assisting merchants in making more precise product updates, promotions, and inventory management.

3. The integrated e-commerce order management system according to claim 1, characterized in that, The order processing module includes: Order consolidation and logistics optimization: The system can automatically consolidate multiple orders from the same user, reducing logistics dispersion and improving delivery efficiency; Real-time order status synchronization: Supports real-time synchronization and updates of order status, ensuring that customers can always obtain order processing progress information and providing transparent order status tracking.

4. The integrated e-commerce order management system according to claim 1, characterized in that, The inventory management module includes: Dynamic inventory adjustment: The system combines historical sales data, market fluctuation trends and supply chain conditions to dynamically adjust the inventory replenishment cycle, avoid stockouts, excessive stockpiling or capital occupation, and ensure inventory liquidity and product availability. Supply chain optimization: Integrate with supplier systems to enable automatic replenishment, ensuring sufficient supply of goods, avoiding delays caused by manual operation, and providing inventory early warning function to prevent the risk of supply chain disruption in advance.

5. The integrated e-commerce order management system according to claim 1, characterized in that, The payment and settlement module includes: Intelligent payment method selection: The system supports multiple payment methods and can automatically select the optimal payment method based on the order amount, payment platform, and user payment preferences. Automatic Refund Mechanism: Provides an automatic refund mechanism to simplify and speed up the refund process and improve the payment experience.

6. The integrated e-commerce order management system according to claim 1, characterized in that, The data analysis module includes: User behavior analysis: Based on user browsing, purchasing, and return behavior data, generate detailed reports to help analyze user behavior; Market demand forecasting: By combining external market data, we can predict future demand for goods and help the operations team to accurately optimize the product supply chain and reduce inventory backlog and stockouts.

7. The integrated e-commerce order management system according to claim 1, characterized in that, The product lifecycle management module includes: Sales fluctuations and promotional triggers: Automatically trigger promotional or clearance strategies based on product sales trends to ensure product market competitiveness; Product flow optimization: Improve product flow efficiency through automated processes to ensure product sales continuity.

8. The integrated e-commerce order management system according to claim 1, characterized in that, The logistics optimization module includes: Consolidated delivery of bulk orders: The system supports consolidated delivery of bulk orders and selects the most suitable warehouse for distribution based on the user's location; Cross-regional delivery optimization: By optimizing delivery routes, the time and cost of cross-regional delivery are reduced, while logistics efficiency is improved.

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