An order management method, system, medium and product based on ToC cycle

Abstract

The present application relates to the technical field of order management, and in particular to an order management method, system, medium, and product based on a ToC cycle, wherein the method comprises determining predicted consumer product information based on order intention information, and determining a display order list based on the predicted consumer product information; creating a target payment order based on target order information, wherein the target order information is the consumer product information selected by the consumer; conducting a financial audit on the target payment order, and updating the store purchase order information based on the target order information after receiving a financial audit pass instruction; obtaining inventory information, performing goods sorting processing on the target order information according to the inventory information, and updating the store purchase and shipment information based on the goods sorting processing result; and performing a sign-off processing based on the target order when a sign-off instruction is received, and determining to update the store purchase sign-off information based on the sign-off processing. The present application facilitates improving the accuracy of order management, thereby improving the consumer's shopping experience.

Description

Technical Field

[0001] The present application relates to the technical field of order management, and in particular to an order management method, system, medium and product based on a ToC cycle. Background Art

[0002] E-commerce has broken the time and space limitations of traditional shopping. Consumers can shop through the Internet anytime and anywhere without having to go to physical stores in person, which greatly saves time and energy and is highly convenient. In addition, e-commerce platforms can also provide consumers with a wider range of product choices. E-commerce platforms can bring together merchants and products from all over the world, and the variety and quantity of products far exceed those of traditional physical stores. Through e-commerce platforms, different brands and prices of the same type of products can be easily compared, thereby helping consumers to choose the most favorite products.

[0003] However, as online shopping becomes more and more popular, e-commerce platforms need to process more and more orders every day. If orders are not managed properly, problems such as logistics delays and increased difficulty in inventory management may occur, which may reduce consumers' shopping experience. Summary of the Invention

[0004] In order to improve the accuracy of order management and thus enhance consumers' shopping experience, this application provides an order management method, system, medium and product based on the ToC cycle.

[0005] In a first aspect, the present application provides an order management method based on a ToC cycle, which adopts the following technical solutions:

[0006] An order management method based on ToC cycle, comprising:

[0007] Acquiring order intention information of a consumer, determining predicted consumption product information based on the order intention information, and determining a display order list based on the predicted consumption product information for the consumer to select an order;

[0008] Obtaining target order information fed back by the consumer, and creating a target payment order based on the target order information, wherein the target order information is information about the consumer product selected by the consumer;

[0009] Performing a financial review on the target payment order, and upon receiving a financial review approval instruction, updating the store purchase order information based on the target order information;

[0010] Acquire inventory information, perform product sorting on the target order information according to the inventory information, and update store purchase and shipment information based on the product sorting result;

[0011] When a receipt instruction is received, a receipt process is performed based on the target order, and the store purchase receipt information is updated based on the receipt process.

[0012] By adopting the above technical solution, the order intention information uploaded by the consumer is used to analyze and predict the consumer's products of interest, and a display order list is generated based on the analysis and prediction results, so as to improve the consumer's satisfaction in the procurement process while ensuring the match between inventory and consumer demand, reducing excessive inventory or out-of-stock situations, thereby improving the accuracy of inventory management. In addition, by conducting a financial audit after the payment order is determined, it is convenient to improve the standardization of the consumer's payment process, and the target order information is divided and processed according to the inventory information to ensure that the target order information can be reasonably allocated according to the existing inventory situation, thereby improving the accuracy and efficiency of the order execution process. Finally, by tracking the receipt status in real time, the store purchase receipt information is updated in time to timely understand the order progress. By coordinating the early stages of procurement, payment, shipment and receipt, it is convenient to improve the accuracy of the order management process, thereby improving the consumer's shopping experience.

[0013] In one possible implementation, determining predicted consumer product information based on the order intention information includes:

[0014] When the consumer is a repeat purchaser, obtaining the consumer's historical shopping information, wherein the historical shopping information is the consumer's shopping record information in the past stages;

[0015] Identifying product feature information corresponding to each shopping record in the historical shopping information, where the product feature information includes product price, brand, and demand type;

[0016] Determining the characteristic information of the product of interest to the consumer based on the product characteristic information corresponding to each shopping record information;

[0017] Based on the order intention information and the feature information of the product of interest, the predicted consumption product information corresponding to the consumer is determined.

[0018] By adopting the above technical solution, by analyzing the historical shopping information of repeat consumers, it is easy to accurately identify consumers' shopping tendencies, and based on the analysis results, it is easy to provide consumers with more personalized product recommendations, thereby improving consumers' shopping satisfaction. By predicting the consumer's displayed order list, it is also easy for merchants to optimize product inventory management, so that the inventory situation meets consumers' shopping needs while improving inventory accumulation.

[0019] In a possible implementation, after determining the predicted consumption product information corresponding to the consumer based on the order intention information and the feature information of the product of interest, the method further includes:

[0020] identifying predicted characteristic information corresponding to the predicted consumer product information, and determining an interest score for each of the predicted consumer products based on the product of interest characteristic information and the predicted characteristic information;

[0021] determining a historical purchase amount of each predicted consumer product based on the historical shopping information, and determining a first predicted purchase amount of each predicted consumer product based on the historical purchase amount and the corresponding interest score of each predicted consumer product;

[0022] identifying a second predicted purchase quantity for each predicted consumer product from the order intention information;

[0023] Based on the first predicted purchase quantity, the second predicted purchase quantity and the preset retention quantity of each predicted consumer product, the inventory requirement of each predicted consumer product is determined, and the inventory demand of each predicted consumer product is fed back.

[0024] By adopting the above technical solution, the characteristics of each predicted consumer product are analyzed, and the interest score of each predicted consumer product is determined in combination with the consumer's interest feature information, which facilitates the analysis of the consumer's purchasing power, thereby facilitating the prediction accuracy. After determining the consumer's purchasing power for each predicted consumer product in combination with the order intention information, inventory demand information is generated in a timely manner to improve inventory management accuracy, thereby avoiding inventory shortages or excess inventory.

[0025] In one possible implementation, the method further includes:

[0026] When the consumer has browsing behavior characteristics, the number of clicks related to each predicted consumption product is determined based on the browsing information corresponding to the browsing characteristics. The number of clicks on the predicted consumption product is the number of times the consumer clicks on the related product in the browsing information. The related products corresponding to different predicted consumption products can be determined based on the product association mapping relationship.

[0027] Determine the click score of each predicted consumption product corresponding to the relevant click volume based on the mapping relationship between the relevant click volume and the click score of each predicted consumption product;

[0028] Determine the display ranking of each predicted consumer product based on its interest score and click score;

[0029] A display order list is determined based on the predicted consumer product information and the display ranking of each predicted consumer product.

[0030] By adopting the above technical solution, the browsing information of consumers is analyzed to determine the relevant click volume of consumers on predicted consumer products, which is convenient for analyzing consumers' shopping preferences and improving the accuracy of product recommendations. In addition, the final display ranking is determined by the click score and the interest score. By preferentially pushing predicted consumer products with higher click scores and interest scores to consumers, it is convenient to increase consumers' purchase rate of predicted consumer products.

[0031] In a possible implementation, when the store purchase and shipment information includes multiple shipment orders, it further includes:

[0032] Obtaining shipping information for each shipping order, wherein the shipping information includes shipping inventory point, shipping quantity, shipping destination, and shipping method;

[0033] Determining the size of the progress display bar corresponding to each shipment amount based on a mapping relationship between the shipment amount and the size in each shipment information, wherein the size mapping relationship is a correspondence between the shipment amount and the size of the progress display bar;

[0034] Determine the shipping route corresponding to each shipping information based on the shipping inventory point and shipping destination in each shipping information, identify the shipping distance corresponding to each shipping route, and determine the update rate of the progress display bar corresponding to each shipping information based on each shipping distance and corresponding shipping method. The update rate of the progress display bar corresponds to the predicted shipping rate obtained based on the shipping distance and shipping method.

[0035] Determine a progress bar for the shipping order corresponding to each shipping information based on the progress bar display size and progress bar update rate corresponding to each shipping information;

[0036] Integrate the progress display bars corresponding to all shipping orders to form a multi-order acceptance table, and feedback the multi-order acceptance table.

[0037] By adopting the above technical solution, the shipping inventory point, shipping volume, shipping destination and shipping method of each shipping order are analyzed, and then based on the progress bar size and progress bar update rate corresponding to each shipping order, the progress display bar corresponding to each shipping order is determined. The progress display bar is determined in a personalized way to facilitate the improvement of the adaptability of the progress display bar to the actual shipping process of each shipping order. In addition, by providing feedback on all progress display bars, real-time supervision of the shipping process is facilitated. By improving the transparency of the shipping process, it is convenient to enhance the consumer shopping experience while promoting the collaboration between procurement and shipping work, thereby facilitating the improvement of the overall efficiency of the order management process.

[0038] In one possible implementation, the method further includes:

[0039] Identifying whether a shipping route includes a preset shipping feature, and determining the shipping route including the preset shipping feature as a shipping route of interest;

[0040] Identifying at least one preset shipping feature included in the shipping route of interest, and segmenting the shipping route of interest based on the at least one preset shipping feature to obtain at least two segmented shipping routes;

[0041] Perform route coding for each split shipping route to obtain the route code corresponding to each split shipping route;

[0042] When the route code is the first code, determining an update rate of a segmentation progress bar corresponding to the segmentation shipping route according to the segmentation route distance and shipping method of the segmentation shipping route corresponding to the route code;

[0043] When the route code is the second code, the update rate of the split progress bar corresponding to the split shipping route is determined based on the split route distance, shipping method and updated predicted shipping rate of the split shipping route corresponding to the route code. The updated predicted shipping rate is obtained by updating the actual shipping rate of the previous split shipping route corresponding to the route code.

[0044] By adopting the above technical solution, when the shipping route contains preset shipping characteristics, the corresponding split progress bar update rate is determined according to the actual situation of each split shipping route, rather than using a consistent method to update the progress bar update rate of the split shipping routes in different situations. This facilitates improving the accuracy of determining the progress bar update rate corresponding to each split route, thereby facilitating improving the accuracy of determining the shipping information corresponding to the multi-order acceptance form.

[0045] In a second aspect, the present application provides a management system that adopts the following technical solutions:

[0046] A management system, comprising:

[0047] at least one processor;

[0048] Memory;

[0049] At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute the above-mentioned order management method based on ToC cycle.

[0050] In a third aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0051] A computer-readable storage medium includes: a computer program stored therein that can be loaded by a processor and execute the above-mentioned order management method based on the ToC cycle.

[0052] In a fourth aspect, the present application provides a computer program product that adopts the following technical solution:

[0053] A computer program product includes a computer program, wherein when the computer program is executed by a processor, the computer program implements the above-mentioned order management method based on the ToC cycle.

[0054] In summary, this application includes at least one of the following beneficial technical effects:

[0055] Through the order intention information uploaded by consumers, we analyze and predict the products that consumers are interested in, and generate a display order list based on the analysis and prediction results, so as to improve consumer satisfaction in the purchasing process while ensuring the match between inventory and consumer demand, reducing excessive inventory or out-of-stock situations, thereby improving inventory management accuracy. In addition, by conducting financial audits after the payment order is determined, it is convenient to improve the standardization of consumers in the payment process, and to divide the target order information according to inventory information to ensure that the target order information can be reasonably allocated according to the existing inventory situation, thereby improving the accuracy and efficiency of the order execution process. Finally, by tracking the receipt status in real time, the store purchase receipt information is updated in time to keep abreast of the order progress. By coordinating the early stages of procurement, payment, shipment and receipt, it is convenient to improve the accuracy of the order management process, thereby improving the consumer shopping experience.

[0056] By analyzing the shipping inventory point, shipping volume, shipping destination and shipping method of each shipping order, and then determining the progress display bar corresponding to each shipping order based on the progress bar size and progress bar update rate corresponding to each shipping order, the progress display bar is determined through personalized customization to facilitate the adaptability of the progress display bar to the actual shipping process of each shipping order. In addition, by providing feedback on all progress display bars, real-time supervision of the shipping process is facilitated. By improving the transparency of the shipping process, it is convenient to enhance the consumer shopping experience while promoting the collaboration between procurement and shipping work, thereby facilitating the improvement of the overall efficiency of the order management process. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flowchart of an order management method based on a ToC cycle in an embodiment of the present application;

[0058] Figure 2 This is a flow chart of determining a multi-order acceptance table in an embodiment of the present application;

[0059] Figure 3 This is a schematic diagram of a multi-order acceptance form in an embodiment of the present application;

[0060] Figure 4 It is a structural diagram of a management system in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following is combined with Figure 1-4 This application is described in further detail.

[0062] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0063] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0064] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0065] Specifically, an embodiment of the present application provides an order management method based on a ToC cycle, which is executed by a management system, which can be a server or a terminal device. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in the embodiment of the present application.

[0066] refer to Figure 1, Figure 1 : is a flow chart of an order management method based on a ToC cycle in an embodiment of the present application, the method includes steps S110 to S150, wherein:

[0067] Step S110: Acquire the consumer's order intention information, determine the predicted consumption product information based on the order intention information, and determine a display order list based on the predicted consumption product information for the consumer to make an order selection.

[0068] Specifically, the order intention information can be uploaded by the consumer to the management system through the terminal device. The order intention information can be descriptive text content or specific information about the intended product. The specific form is not specifically limited in the embodiments of this application. Product feature recognition of the order intention information facilitates the determination of the intended products contained in the order intention information. By integrating the intended products, a display order list is determined, so that consumers can select the products they want to purchase from the displayed order list, thereby improving consumer satisfaction.

[0069] Determining the predicted consumer product information based on the order intention information may specifically include:

[0070] When the consumer is a repeat buyer, obtain the consumer's historical shopping information, which is the consumer's shopping record information in the historical stage; identify the product feature information corresponding to each shopping record information in the historical shopping information, which includes product price, brand, and demand type; based on the product feature information corresponding to each shopping record information, determine the consumer's product feature information of interest; based on the order intention information and the product feature information of interest, determine the consumer's corresponding predicted consumption product information.

[0071] Specifically, consumer types include repeat buyers and regular buyers. Repeat buyers are those who have purchased products in the past, i.e., regular customers. Whether a consumer is a repeat buyer can be determined by checking whether they have historical purchase history at the corresponding store. Each store records corresponding historical purchase history, and by reviewing and analyzing this historical purchase history, it is possible to identify the purchase history of any repeat buyer in the past. The historical shopping information includes at least one shopping record information. The number of shopping record information is not specifically limited in the embodiment of the present application. Each shopping record information corresponds to a historically purchased product. By performing feature recognition on each piece of historical shopping record information, it is convenient to determine the product price, brand, and demand type in each piece of historical shopping record information. Different product prices, brands, and demand types correspond to different product feature information. For example, by analyzing the product prices in the historical shopping records, it is convenient to determine the consumer's price sensitivity, brand loyalty, and demand type during the shopping process. When determining the consumer's price sensitivity based on the historical shopping record information, the sales volume of the same product at different price levels can be compared to analyze the impact of price changes on the consumer's order volume. If the consumer's order volume for the same product does not change significantly at different price levels, that is, the order volume difference between the order volumes at different price levels is within a preset difference range, it can be determined that the consumer's price sensitivity during the shopping process is low. The specific method for determining the consumer's price sensitivity based on the historical shopping information is not specifically limited in the embodiment of the present application.

[0072] When determining a consumer's brand loyalty based on historical shopping information, the historical shopping information can be used to analyze the number of times a consumer purchased a specific brand within a certain period. The higher the frequency of repeat purchases, the higher the consumer's brand loyalty. The corresponding loyalty can be determined based on the loyalty mapping relationship and repeat purchase frequency, where the loyalty mapping relationship represents the correspondence between repeat purchase frequency and loyalty. When determining a consumer's need type based on historical shopping information, the product categories of the historically purchased products in the historical shopping information can be used to determine the corresponding need areas based on the product categories, thereby determining the consumer's corresponding need type, which includes functional needs and emotional needs. The use scenarios corresponding to the historically purchased products in the historical shopping information can be analyzed to determine whether they primarily satisfied work, study, or specific task needs to determine whether the consumer's need type is a functional need. The product types corresponding to the historically purchased products in the historical shopping information can be analyzed to determine whether they are products associated with emotional value, such as artwork, collectibles, personalized gifts, accessories, etc. to determine whether the consumer's need type is an emotional need. Need types include, but are not limited to, functional needs and emotional needs, and the specific content can be set by relevant technical personnel based on actual circumstances.

[0073] After determining the product feature information corresponding to each historical shopping information, the number of occurrences of each product feature information is counted, and the multiple product feature information are ranked in descending order based on the number of occurrences. The product feature information that ranks higher than a preset ranking is determined as the product feature information of interest to the consumer. The preset ranking can be third or fourth, and the specific preset ranking is not specifically limited in the embodiments of this application.

[0074] After determining the corresponding intended products based on the order intent, the intended products can be optimized based on the consumer's interest characteristics to obtain predicted consumption product information. The optimization process can include deletion and addition. Specifically, products that do not meet the consumer's interest characteristics can be deleted from the intended products. In addition, the consumer's interest characteristics can be used to predict the consumption of products of interest, and new products based on the interest products can be added to the intended products. By analyzing the historical shopping information of repeat consumers, it is easier to accurately identify consumers' shopping tendencies and provide consumers with more personalized product recommendations based on the analysis results.

[0075] Step S120: Obtain target order information fed back by the consumer, and create a target payment order based on the target order information, where the target order information is information about the consumer product selected by the consumer.

[0076] Specifically, the displayed order list includes multiple predicted consumer products. Consumers can make selections from the displayed order list according to their own needs. After receiving the consumer's selection results, the corresponding target order information can be automatically generated. The target order information includes the selected consumer products, quantity and unit price. The corresponding target payment order can be automatically determined through the target order information. After the target payment order is generated, the target payment order can be fed back to the consumer's terminal device, and the consumer can choose any payment method to pay.

[0077] Step S130: Perform a financial review on the target payment order, and after receiving a financial review pass instruction, update the store purchase order information based on the target order information.

[0078] Specifically, after the consumer completes the payment, the shipping operation will not be performed directly according to the target order information. Instead, the target payment order needs to be fed back to the financial review end. During the financial review period, the target order information is in an inactive state, and the consumer can cancel the order on his own. When the financial review pass instruction is received, it indicates that the target order information has been activated and the shipping operation can be started. At this time, the store purchase order information is updated in time according to the target order information, that is, the store inventory information is updated according to the target order information, and then the store purchase order information is updated based on the store inventory information to avoid inventory shortages in the store.

[0079] Step S140: Acquire inventory information, perform goods sorting processing on the target order information according to the inventory information, and update the store purchase and shipping information based on the goods sorting processing result.

[0080] Specifically, the inventory information includes all products in the store and the inventory quantity corresponding to each product. When the target order information is sorted according to the inventory information, a preset sorting strategy can be used for sorting. The preset sorting strategy can be first-in-first-out, that is, giving priority to the earliest products in the warehouse to reduce inventory backlogs and expiration risks; sorting by batch, that is, sorting according to the batch information of the product to ensure that the products of the same batch are shipped together for easy traceability and management; sorting by location, that is, sorting according to the location of the product in the warehouse, optimizing the picking path and improving the picking efficiency. The specific content of the preset sorting strategy is not specifically limited in the embodiment of this application and can be set by relevant technical personnel. After picking according to the preset sorting strategy, the picked products are packaged, labeled, prepared for shipment, and other steps in sequence. Update the store's procurement and shipping information, that is, feed back the shipping information corresponding to the target order information to the store end, so that the store can track each target order information.

[0081] Step S150: When a receipt instruction is received, a receipt process is performed based on the target order, and the store purchase receipt information is updated based on the receipt process.

[0082] Specifically, the receipt instruction can be confirmed by the consumer and then sent to the management system. The management system confirms the store purchase receipt information based on the receipt instruction. The receipt instruction includes but is not limited to the receipt date, that is, the date when the target order is delivered; the signatory, that is, the consumer; the purchase order number, that is, the purchase order number related to the target order, which is used to track and manage the product procurement process, etc. It will be sorted and generated in advance based on the target order information before the shipping operation, and the consumer only needs to confirm it after receiving the goods.

[0083] For the embodiment of the present application, the order intention information uploaded by the consumer is used to analyze and predict the consumer's products of interest, and a display order list is generated based on the analysis and prediction results, so as to improve the consumer's satisfaction in the procurement process while ensuring the match between inventory and consumer demand, reducing excessive inventory or out-of-stock situations, thereby facilitating the improvement of inventory management accuracy. In addition, by conducting a financial audit after determining the payment order, it is convenient to improve the standardization of the consumer's payment process, and the target order information is divided and processed through inventory information to ensure that the target order information can be reasonably allocated according to the existing inventory situation, thereby facilitating the improvement of the accuracy and efficiency of the order execution process. Finally, by real-time tracking of the receipt status, the store purchase receipt information is updated in a timely manner to facilitate timely understanding of the order progress. By collaboratively processing in the early stage of procurement, payment, shipment and receipt, it is convenient to improve the accuracy of the order management process, thereby facilitating the improvement of the consumer's shopping experience.

[0084] Furthermore, to improve inventory management accuracy, after determining the predicted consumption product information corresponding to the consumer based on the order intention information and the characteristic information of the product of interest, the following is also included:

[0085] Identify the prediction feature information corresponding to the prediction consumer product information, and determine the interest score of each prediction consumer product in the prediction consumer products based on the feature information of the product of interest and the prediction feature information; determine the historical purchase quantity of each prediction consumer product based on the historical shopping information, and determine the first prediction purchase quantity of each prediction product based on the historical purchase quantity and the corresponding interest score of each prediction consumer product; identify the second prediction purchase quantity of each prediction consumer product from the order intention information; determine the inventory requirement of each prediction consumer product based on the first prediction purchase quantity, the second prediction purchase quantity and the preset retention quantity of each prediction consumer product, and feedback the inventory demand of each prediction consumer product.

[0086] Specifically, the predicted consumer product information includes multiple predicted consumer products, and each predicted consumer product corresponds to different predicted feature information. The predicted feature information includes but is not limited to product price, brand, and demand type. The predicted feature information of each predicted consumer product is matched with the feature information of the product of interest to obtain a feature matching value. The higher the feature matching value, the higher the interest score of the corresponding predicted consumer product. There is a corresponding relationship between the feature matching value and the interest score. The specific content of the corresponding relationship is not specifically limited in the embodiment of this application, and is determined by relevant staff based on historical shopping data and uploaded to the management system.

[0087] It is possible to determine whether the consumer has purchased the predicted consumer product during the historical shopping stage by determining whether the historical shopping information contains historical shopping records of the predicted consumer product. If so, the historical purchase quantity of the corresponding predicted consumer product is determined from the historical shopping records. If not, the historical purchase quantity of the predicted consumer product is determined to be 0. When determining the corresponding first predicted purchase quantity based on the historical purchase quantity and the corresponding interest score, the adjusted purchase quantity corresponding to the interest score can be first determined based on the adjusted purchase quantity mapping relationship, and then the historical purchase quantity is adjusted based on the determined adjusted purchase quantity to obtain the first predicted purchase quantity. The adjusted purchase quantity mapping relationship is the corresponding relationship between the interest score and the adjusted purchase, which is determined by relevant staff based on historical experimental data and uploaded to the management system. The specific content is not specifically limited in the embodiments of this application, as long as the adjusted purchase quantity corresponding to any interest score can be identified.

[0088] The second predicted purchase quantity of each predicted consumer product can be identified from the order intention information through feature recognition. If the order intention information does not include a predicted consumer product, the second predicted purchase quantity of the predicted consumer product is 0. By adding a preset retention quantity, it is convenient to avoid inventory shortages. The preset retention quantity can be 20 or 50 pieces. The specific quantity is not specifically limited in the embodiments of this application. By superimposing the first predicted purchase quantity, the second predicted purchase quantity, and the preset retention quantity of each predicted consumer product, the inventory requirement of each predicted consumer product is finally determined. By calculating the inventory requirement, it is convenient to avoid inventory shortages or excess inventory while ensuring the purchasing needs of consumers.

[0089] Furthermore, in order to increase the consumer purchase rate of the predicted consumer product, the method provided in the embodiment of the present application further includes:

[0090] When consumers have browsing behavior characteristics, the relevant click volume of each predicted consumer product is determined based on the browsing information corresponding to the browsing characteristics. The click volume of the predicted consumer product is the number of times the consumer clicks on the related product in the browsing information. The related products corresponding to different predicted consumer products can be determined based on the product association mapping relationship.

[0091] Specifically, the browsing behavior characteristics of consumers can be accessing or browsing web pages, searching for products within the web pages, and the corresponding browsing information is each web page visited or browsed, as well as the search content. By analyzing the browsing information of consumers, it is convenient to understand the shopping needs of consumers. For example, if a consumer enters a keyword in the search box, the keyword can be used to reflect the shopping needs of the consumer. Based on the browsing information, the relevant click content and relevant click volume of the consumer for any predicted consumption product can be determined. The relevant click volume corresponding to different predicted consumption products may be different. When the consumer does not click on the relevant click content of a predicted consumption product, the relevant click volume corresponding to the predicted consumption product is 0. Relevant staff can determine the association relationship between each predicted product and other products based on historical consumption records and historical survey data. For example, if there is an association relationship between predicted product a and product b, when it is detected that the consumer clicks or searches for product b, the relevant click volume of predicted consumption product a can be determined based on the consumer's click volume on product b. The specific content of the product association mapping relationship is not specifically limited in the embodiment of this application, as long as the relevant products of any predicted consumption product can be determined.

[0092] Based on the mapping relationship between the relevant click volume and click score of each predicted consumption product, the click score of each predicted consumption product corresponding to the relevant click volume is determined.

[0093] Specifically, the higher the predicted relevant click volume of the consumer product, the higher the corresponding click score. The click-score mapping relationship includes click scores corresponding to different relevant click volumes. The specific content of the mapping relationship is not specifically limited in the embodiments of this application.

[0094] The display ranking of each predicted consumer product is determined according to the interest score and click score of each predicted consumer product; and a display order list is determined based on the predicted consumer product information and the display ranking of each predicted consumer product.

[0095] Specifically, the interest score and click score of each predicted consumer product are summed up to obtain the total score of each predicted consumer product, and then the display ranking corresponding to each total score is determined based on the ranking mapping relationship. The higher the total score, the closer the corresponding display ranking. The specific content of the correspondence between the total score and the display ranking of the ranking mapping relationship is not specifically limited in the embodiment of this application and can be adjusted or modified according to actual needs. After determining the display ranking corresponding to each predicted consumer product, all predicted consumer products are sorted according to the display ranking corresponding to each predicted consumer product, and finally a sorted display order list is obtained. By giving priority to pushing predicted consumer products with higher click scores and interest scores to consumers, it is convenient to increase consumers' purchase rate of predicted consumer products.

[0096] Furthermore, in order to promote the collaborative work between procurement and shipping, when the store procurement and shipping information contains multiple shipping orders, the method provided in the embodiment of the present application further includes steps S1-S1-S5, such as Figure 2 As shown, where:

[0097] Step S1: Obtain the shipping information in each shipping order. The shipping information includes the shipping inventory point, shipping quantity, shipping destination, and shipping method.

[0098] Step S2: Determine the progress display bar size corresponding to each shipping quantity based on the shipping quantity and size mapping relationship in each shipping information. The size mapping relationship is the corresponding relationship between the shipping quantity and the progress display bar size.

[0099] Specifically, the shipping method is the order shipping method, and different shipping methods correspond to different transportation rates. For example, the shipping method can be express a, express b, express c, etc. Since different shipping methods correspond to different service levels and charges, the transportation rates corresponding to different shipping methods will also be different. When the shipping order is determined, the corresponding shipping information will be automatically generated. After the shipping information is automatically generated, it can be adjusted according to actual needs by submitting a modification application. In order to distinguish and display different shipping orders, the corresponding progress display bar size can be determined according to the shipping volume corresponding to each shipping order. The larger the shipping volume, the larger the corresponding progress display bar size. The progress display bar size includes the display bar length and the display bar width. In order to facilitate the unified management of multiple shipping orders, the display bar length or the display bar width of the progress display bar sizes corresponding to different shipping orders are kept consistent. For example, when the display bar length is guaranteed to be consistent, the larger the shipping volume, the wider the corresponding display bar width. The progress display bar size corresponding to any shipping volume can be determined based on the size mapping relationship. The specific content is not specifically limited in the embodiment of this application.

[0100] Step S3: Determine the shipping route corresponding to each shipping information based on the shipping inventory point and shipping destination in each shipping information, identify the shipping distance corresponding to each shipping route, and determine the progress display bar update rate corresponding to each shipping information based on each shipping distance and the corresponding shipping method. The progress display bar update rate corresponds to the predicted shipping rate obtained based on the shipping distance and shipping method.

[0101] Specifically, the route between the shipping inventory point and the shipping destination is the shipping route. Different shipping orders correspond to different shipping routes. Based on the shipping route, the corresponding shipping distance can be determined. According to the shipping method, the predicted shipping rate can be determined. According to the shipping distance and the predicted shipping rate, it is convenient to determine the shipping time. Finally, the progress display bar update rate is determined based on the progress bar length and the shipping time of the corresponding progress display bar. That is, it is only necessary to ensure that the progress cursor in the progress display bar reaches the end of the progress display bar within the shipping time.

[0102] Step S4: Based on the progress bar display size and progress bar update rate corresponding to each shipping information, determine the progress bar display for the shipping order corresponding to each shipping information.

[0103] Specifically, after determining the corresponding progress display size and progress bar update rate for each shipping information, the basic progress bar is determined according to the progress display size. The basic progress bar contains a progress cursor, and then the progress cursor is driven to move according to the progress bar update rate to obtain the progress display bar of the corresponding shipping order. The progress display bar of the shipping order makes it easy to intuitively view the actual shipping status of the corresponding shipping order.

[0104] Step S5: Integrate the progress display bars corresponding to all shipping orders to form a multi-order acceptance table, and feedback the multi-order acceptance table.

[0105] Specifically, since the progress display bars corresponding to different shipping orders have the same progress bar width or the same progress bar length, the progress display bars corresponding to all shipping orders can be integrated, such as Figure 3 As shown, Figure 3 The system includes three progress bars corresponding to shipping orders. By providing feedback on all progress bars, the shipping process can be monitored in real time. By increasing transparency in the shipping process, it can enhance the consumer shopping experience while promoting collaboration between procurement and shipping, thereby improving the overall efficiency of the order management process.

[0106] Furthermore, in order to improve the accuracy of determining whether shipping information corresponds to multiple order acceptance forms, the method provided in the embodiment of the present application further includes:

[0107] It is identified whether the shipping route includes a preset shipping feature, and the shipping route including the preset shipping feature is determined as a shipping route of interest.

[0108] Specifically, the preset shipping feature can be a transfer station feature. When a preset shipping feature exists in a shipping route, the corresponding predicted shipping rate may be affected when arriving at or leaving the preset shipping feature. Therefore, when a shipping route contains a preset shipping feature, it is necessary to pay attention to the shipping route. The shipping route of interest may contain one preset shipping feature, or it may contain two or more preset shipping features. The number of preset shipping features is not specifically limited in the embodiments of this application.

[0109] At least one preset shipping feature included in the shipping route of interest is identified, and the shipping route of interest is segmented based on the at least one preset shipping feature to obtain at least two segmented shipping routes.

[0110] Specifically, for any shipping route of interest, the shipping route of interest is segmented based on at least one preset shipping characteristic. Specifically, a segmentation line is determined based on each preset shipping characteristic, and the shipping route of interest is segmented based on each segmentation line. Based on this approach, at least two segmented shipping routes are obtained for each shipping route of interest.

[0111] Perform route coding for each split shipping route to obtain a route code corresponding to each split shipping route.

[0112] Specifically, for any shipping route of interest, route codes are assigned to at least two split shipping routes corresponding to the shipping route of interest based on the shipping direction, that is, based on the transportation direction. Each split shipping route has a different route code. The route code can be a symbol or a number, for example, a positive integer starting from 1. By coding each split shipping route, management of the different split shipping routes is facilitated.

[0113] When the route code is the first code, the update rate of the segmentation progress bar corresponding to the segmentation shipping route is determined according to the segmentation route distance and the shipping method of the segmentation shipping route corresponding to the route code.

[0114] Specifically, when the route code is a number, you can first determine whether the i corresponding to the route code is equal to 1. If the route code is 1, the first split shipping route in the shipping route can be determined to have the first code. When determining the update rate of the split progress bar corresponding to the split shipping route with the first code, you can refer to the above-mentioned embodiment based on each shipping distance and the corresponding shipping method to determine the update rate of the progress display bar corresponding to each shipping information, which will not be elaborated here.

[0115] When the route code is the second code, the update rate of the split progress bar corresponding to the split shipping route is determined based on the split route distance, shipping method and updated predicted shipping rate of the split shipping route corresponding to the route code. The updated predicted shipping rate is obtained by updating the actual shipping rate of the previous split shipping route corresponding to the route code.

[0116] Specifically, when the route code is i and i≠1, it can be determined that the route code is the second code. In this case, it can be determined that the split shipping route corresponding to the route code includes at least two split shipping routes, and that the split shipping route is located after the first split shipping route. The actual rate of the previous split shipping route is recorded in real time, and the predicted shipping rate is updated based on the recorded result. The update method can be to increase or decrease the corresponding rate. The specific rate value of increase or decrease is not specifically limited in this embodiment of the application. It is sufficient to adjust and update the predicted shipping rate based on the actual shipping rate of the previous split shipping route.

[0117] The actual shipping rate for the previous segmented shipping route can be determined by calculating the route length corresponding to the previous segmented shipping route and the actual arrival time corresponding to the preset shipping characteristics. After adjusting and updating the predicted shipping rate based on the actual shipping rate for the previous segmented shipping route, the method for determining the update rate of the segmented progress bar for the segmented shipping route corresponding to the first-coded route code can be referred to in the above embodiment, and will not be further described here.

[0118] By determining the corresponding split progress bar update rate based on the actual situation of each split shipping route, rather than using a consistent method to update the progress bar update rate for split shipping routes in different situations, it is easy to improve the accuracy of determining the progress bar update rate corresponding to each split route, thereby facilitating the improvement of the accuracy of determining the shipping information corresponding to the multi-order acceptance form.

[0119] The present application provides a management system, such as Figure 4 Show, Figure 4 The management system 400 shown includes a processor 401 and a memory 403. The processor 401 and the memory 403 are connected, for example, via a bus 402. Optionally, the management system 400 may further include a transceiver 404. It should be noted that in actual applications, the number of transceivers 404 is not limited to one, and the structure of the management system 400 does not constitute a limitation on the embodiments of the present application.

[0120] Processor 401 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, or a combination of a DSP and a microprocessor.

[0121] Bus 402 may include a path for transmitting information between the above components. Bus 402 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 402 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The fact that only one line is used does not mean that there is only one bus or one type of bus.

[0122] The memory 403 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0123] The memory 403 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 401. The processor 401 is used to execute the application code stored in the memory 403 to implement the content shown in the above method embodiment.

[0124] The management system includes, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers are also possible. Figure 4 The management system shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0125] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0126] An embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method in any of the above embodiments is implemented.

[0127] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0128] The above description is only part of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. An order management method based on ToC cycle, characterized in that: include: Acquiring order intention information of a consumer, determining predicted consumption product information based on the order intention information, and determining a display order list based on the predicted consumption product information for the consumer to select an order; Obtaining target order information fed back by the consumer, and creating a target payment order based on the target order information, wherein the target order information is information about the consumer product selected by the consumer; Performing a financial review on the target payment order, and upon receiving a financial review approval instruction, updating the store purchase order information based on the target order information; Acquire inventory information, perform product sorting on the target order information according to the inventory information, and update store purchase and shipment information based on the product sorting result; Upon receiving a receipt instruction, performing a receipt process based on the target order, and determining to update the store purchase receipt information based on the receipt process; The step of determining the predicted consumer product information based on the order intention information includes: When the consumer is a repeat purchaser, obtaining the consumer's historical shopping information, wherein the historical shopping information is the consumer's shopping record information in the past stages; Identifying product feature information corresponding to each shopping record in the historical shopping information, where the product feature information includes product price, brand, and demand type; Determining the characteristic information of the product of interest to the consumer based on the product characteristic information corresponding to each shopping record information; Determining predicted consumption product information corresponding to the consumer based on the order intention information and the characteristic information of the product of interest; After determining the predicted consumption product information corresponding to the consumer based on the order intention information and the feature information of the product of interest, the method further includes: identifying predicted characteristic information corresponding to the predicted consumer product information, and determining an interest score for each of the predicted consumer products based on the product of interest characteristic information and the predicted characteristic information; determining a historical purchase amount of each predicted consumer product based on the historical shopping information, and determining a first predicted purchase amount of each predicted consumer product based on the historical purchase amount and the corresponding interest score of each predicted consumer product; identifying a second predicted purchase quantity for each predicted consumer product from the order intention information; Determine the inventory requirement for each predicted consumer product based on the first predicted purchase quantity, the second predicted purchase quantity, and the preset retention quantity of each predicted consumer product, and provide feedback on the inventory requirement for each predicted consumer product; When the store purchase and delivery information includes multiple delivery orders, it also includes: Obtaining shipping information for each shipping order, wherein the shipping information includes shipping inventory point, shipping quantity, shipping destination, and shipping method; Determining the size of the progress display bar corresponding to each shipment amount based on a mapping relationship between the shipment amount and the size in each shipment information, wherein the size mapping relationship is a correspondence between the shipment amount and the size of the progress display bar; Determine the shipping route corresponding to each shipping information based on the shipping inventory point and shipping destination in each shipping information, identify the shipping distance corresponding to each shipping route, and determine the update rate of the progress display bar corresponding to each shipping information based on each shipping distance and corresponding shipping method. The update rate of the progress display bar corresponds to the predicted shipping rate obtained based on the shipping distance and shipping method. Determine a progress bar for the shipping order corresponding to each shipping information based on the progress bar display size and progress bar update rate corresponding to each shipping information; Integrate the progress display bars corresponding to all shipping orders to form a multi-order acceptance table, and provide feedback on the multi-order acceptance table; Among them, also include: Identifying whether a shipping route includes a preset shipping feature, and determining the shipping route including the preset shipping feature as a shipping route of interest; Identifying at least one preset shipping feature included in the shipping route of interest, and segmenting the shipping route of interest based on the at least one preset shipping feature to obtain at least two segmented shipping routes; Perform route coding for each split shipping route to obtain the route code corresponding to each split shipping route; When the route code is the first code, determining an update rate of a segmentation progress bar corresponding to the segmentation shipping route according to the segmentation route distance and shipping method of the segmentation shipping route corresponding to the route code; When the route code is the second code, the update rate of the split progress bar corresponding to the split shipping route is determined based on the split route distance, shipping method and updated predicted shipping rate of the split shipping route corresponding to the route code. The updated predicted shipping rate is obtained by updating the actual shipping rate of the previous split shipping route corresponding to the route code.

2. The order management method based on ToC cycle according to claim 1, characterized in that: Also includes: When the consumer has browsing behavior characteristics, the number of clicks related to each predicted consumption product is determined based on the browsing information corresponding to the browsing characteristics. The number of clicks on the predicted consumption product is the number of times the consumer clicks on the related product in the browsing information. The related products corresponding to different predicted consumption products can be determined based on the product association mapping relationship. Determine the click score of each predicted consumption product corresponding to the relevant click volume based on the mapping relationship between the relevant click volume and the click score of each predicted consumption product; Determine the display ranking of each predicted consumer product based on its interest score and click score; A display order list is determined based on the predicted consumer product information and the display ranking of each predicted consumer product.

3. A management system, characterized in that: The management system includes: at least one processor; Memory; At least one application, wherein the at least one application is stored in a memory and configured to be executed by at least one processor, and the at least one application is configured to: execute an order management method based on a ToC cycle according to any one of claims 1-2.

4. A computer-readable storage medium, characterized in that include: The computer program is stored and can be loaded by a processor to execute an order management method based on a ToC cycle as claimed in any one of claims 1 to 2.

5. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the steps of an order management method based on a ToC cycle according to any one of claims 1 to 2.

Images