Method and device for adjusting product information of sending mail, computer device and storage medium

Abstract

The application discloses a kind of sending product information adjustment method, device, computer equipment and storage medium, the method includes: obtaining the original sending data of target enterprise;Based on the original sending data of target enterprise and the existing sending price ordering table stored in system database, determine the original recommended price of target enterprise;Monitoring the online operation time of target enterprise based on original recommended price operation, judge whether online operation time reaches operation review period;If online operation time reaches operation review period, obtain the operation statistical data corresponding to target enterprise, determine target adjustment strategy according to operation statistical data and original recommended price;According to target adjustment strategy, determine the target recommended price and / or target product time limit of target enterprise.This method does not need to carry out standard interface development, saves technical resources, makes the adjustment of sending product information more timely and fast, and more in line with the actual operation of target enterprise.

Description

Technical Field

[0001] This invention relates to the field of logistics and express delivery, and in particular to a method, apparatus, computer equipment, and storage medium for adjusting product information when sending a package. Background Technology

[0002] In existing technologies, logistics and express delivery companies need to obtain or adjust parcel information, including pricing, through standard interface interfaces when providing parcel delivery services. This is especially true when using smart locker compartments, where matching the locker type of the target company is necessary to determine pricing or adjust delivery times, thus modifying the parcel information. Since this adjustment relies on standard interface interfaces, it requires not only the target company's manufacturer to develop the interface but also different logistics companies within the target company to develop their own interfaces for the platform. This method demands significant technical resources from both parties for development and integration, which is challenging for small or startup logistics and express delivery companies. Therefore, there is an urgent need for a cost-effective method for adjusting parcel information. Summary of the Invention

[0003] This invention provides a method, apparatus, computer device, and storage medium for adjusting shipment product information, in order to solve the problem of how to adjust shipment product information.

[0004] A method for adjusting product information for shipments, comprising:

[0005] Obtain the target company's original shipment data;

[0006] Based on the target company's original shipping data and the existing shipping price ranking table stored in the system database, the original recommended price of the target company is determined;

[0007] Monitor the online operation time of the target enterprise based on the original recommended price, and determine whether the online operation time has reached the operation review cycle;

[0008] If the online operation time reaches the operation review cycle, then obtain the operation statistics data corresponding to the target enterprise, and determine the target adjustment strategy based on the operation statistics data and the original recommended price;

[0009] Based on the target adjustment strategy, determine the target recommended price and / or target product timeliness for the target enterprise.

[0010] A device for adjusting product information for shipments, comprising:

[0011] The original shipment data acquisition module is used to acquire the original shipment data of the target company;

[0012] The original recommended price acquisition module is used to determine the original recommended price of the target company based on the target company's original shipment data and the existing shipment price sorting table stored in the system database;

[0013] The Operation Review Cycle Monitoring Module is used to monitor the online operation time of the target enterprise based on the original recommended price and determine whether the online operation time has reached the operation review cycle.

[0014] The target adjustment strategy determination module is used to obtain the corresponding operational statistics of the target enterprise if the online operation time reaches the operation review cycle, and determine the target adjustment strategy based on the operational statistics and the original recommendation price.

[0015] The target adjustment strategy execution module is used to determine the target recommended price and / or target product timeliness of the target enterprise according to the target adjustment strategy.

[0016] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for adjusting mailed product information.

[0017] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for adjusting shipment product information.

[0018] The aforementioned method, device, computer, and storage medium for adjusting parcel delivery product information directly determine the target company's original recommended price by querying the system database based on the original parcel delivery data. This eliminates the need for standard interface development, saving technical resources and making price determination more convenient and efficient. Furthermore, after the operational review cycle is completed, the target adjustment strategy is determined directly based on operational statistics and the original recommended price. Based on this strategy, the target recommended price and / or target product timeliness for the target company are determined, again without requiring standard interface development, saving development costs. This makes adjusting parcel delivery product information more timely and efficient, and ensures that the final adjusted parcel delivery product information, including the target recommended price and / or target product timeliness, better reflects the target company's actual operational situation. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of an application environment for a method for adjusting product information of a mail item according to an embodiment of the present invention;

[0021] Figure 2 This is a flowchart of a method for adjusting product information of a mail item according to an embodiment of the present invention;

[0022] Figure 3 This is another flowchart of the method for adjusting product information of a shipment in one embodiment of the present invention;

[0023] Figure 4 This is another flowchart of the method for adjusting product information of a shipment in one embodiment of the present invention;

[0024] Figure 5 This is a flowchart of a method for adjusting product information of a mail shipment according to another embodiment of the present invention;

[0025] Figure 6 This is another flowchart of the method for adjusting product information of a shipment in one embodiment of the present invention;

[0026] Figure 7 This is another flowchart of the method for adjusting product information of a shipment in one embodiment of the present invention;

[0027] Figure 8 This is another flowchart of the method for adjusting product information of a shipment in one embodiment of the present invention;

[0028] Figure 9 This is another flowchart of the method for adjusting product information of a shipment in one embodiment of the present invention;

[0029] Figure 10 This is a schematic diagram of a parcel product information adjustment device according to an embodiment of the present invention;

[0030] Figure 11 This is a schematic diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0031] 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, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0032] The method for adjusting shipment product information provided in this embodiment of the invention can be applied to, for example... Figure 1 The application environment is shown. Specifically, this method for adjusting parcel product information is applied in a parcel product information adjustment system, which includes, for example, […]. Figure 1 The diagram shows a client and server. The client and server communicate over a network to adjust the information of the shipped products. The client, also known as the user terminal, is the program that provides local services to the customer, corresponding to the server. The client can be installed on, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0033] In one embodiment, such as Figure 2 As shown, a method for adjusting shipment product information is provided, which is applied to... Figure 1 Taking the server in the example, the following steps are included:

[0034] S201: Obtain the target company's original shipment data;

[0035] S202: Determine the original recommended price for the target company based on the target company's original shipment data and the existing shipment price ranking table stored in the system database;

[0036] S203: Monitor the online operation time of the target enterprise based on the original recommended price, and determine whether the online operation time has reached the operation review cycle;

[0037] S204: If the online operation time reaches the operation review cycle, obtain the corresponding operation statistics of the target enterprise, and determine the target adjustment strategy based on the operation statistics and the original recommended price;

[0038] S205: Adjust the strategy according to the objectives and determine the target recommended price and / or the target product timeliness for the target company.

[0039] The target company refers to the logistics or express delivery company whose shipping product information needs to be adjusted. Shipping product information includes the shipping price and / or delivery time of the target company. Original shipping data refers to the indicator data required by the target company to determine the shipping price, including data on smart locker shipping and shipping data for non-smart locker methods. Smart locker shipping data for the target company includes compartment type, area type distance, and delivery time. Generally, different smart locker manufacturers produce different types of smart lockers for the target company, resulting in different original shipping data for compartment type, area type distance, and delivery time. Non-smart locker shipping data refers to shipping data for methods other than smart locker shipping within the target company, such as shipping data from express delivery stores or partner stations, and shipping data for online orders with courier door-to-door pickup. Non-smart locker shipping data includes the weight and volume of the shipped item, area type distance, and delivery time.

[0040] As an example, in step S201, the server obtains the original parcel delivery data corresponding to the target enterprise. In this example, the server obtains the indicator data used by logistics companies and express delivery companies to determine the parcel delivery price of the target enterprise, as the original parcel delivery data. Understandably, for example, when it is necessary to determine the original recommended price for smart locker parcel delivery of the target enterprise, since it is necessary to comprehensively consider the parcel delivery prices for different locker types, different regional distances, and different product delivery times corresponding to the target enterprise's smart locker, it is necessary to obtain smart locker parcel delivery data including locker type, regional distance, and product delivery time as the original parcel delivery data. For example, when it's necessary to determine the original recommended price for a target company's non-smart locker parcel delivery methods, such as the original recommended price for parcel delivery via courier stores or partner stations versus online ordering with courier door-to-door pickup, it's necessary to comprehensively consider the parcel delivery prices for different weights, volumes, distances, and delivery times. Therefore, it's required to obtain parcel delivery data for non-smart locker methods, including parcel weight, volume, distance, and delivery time, as the original delivery data. In this example, obtaining the target company's original delivery data makes it feasible to subsequently determine the corresponding original recommended price based on this data.

[0041] The original recommended price is the shipping price set by logistics and express delivery companies for the corresponding shipping business of the target company. The existing shipping price sorting table is a price sorting table of the original shipping data that affects the shipping price, pre-stored in the system database.

[0042] As an example, in step S202, the server determines the original recommended price for the target company based on its original parcel delivery data and the existing parcel delivery price ranking table stored in the system database. For instance, when it is necessary to determine the original recommended price for a target company's smart locker parcel delivery, the server obtains the original parcel delivery data corresponding to the target company's smart locker, i.e., the slot type, area type distance, and product timeliness required to determine the parcel delivery price of the target company's smart locker. Subsequently, it retrieves the pre-stored existing parcel delivery price ranking table from the system database, queries and filters the existing parcel delivery price ranking results corresponding to the target company's slot type, area type distance, and product timeliness in the existing parcel delivery price ranking table; and formulates the original recommended price for the target company's smart locker based on the existing parcel delivery price ranking results. Understandably, the types of smart lockers corresponding to the pre-obtained existing parcel delivery price ranking table may be different, i.e., the smart lockers corresponding to the existing parcel delivery price ranking table may come from different smart locker manufacturers. Therefore, it is necessary to filter the existing parcel delivery price ranking results corresponding to the target company from the existing parcel delivery price ranking table to facilitate the determination of the original recommended price for the target company's smart locker.

[0043] For example, when it is necessary to determine the original recommended price for non-smart locker delivery methods of a target company, such as the original recommended price for delivery through a courier store or partner station and the original recommended price for online ordering with courier pickup, the server obtains the original delivery data for the target company's non-smart locker delivery methods. This involves determining the weight, volume, regional distance, and delivery time of the items to be delivered, including both courier stores / partner stations and online ordering with courier pickup. Subsequently, the system retrieves a pre-stored existing delivery price ranking table from the system database, queries and filters the price ranking results for the target company's items based on weight, volume, regional distance, and delivery time. Based on the existing price ranking results, the server formulates the original recommended price for non-smart locker delivery methods of the target company, including both courier stores / partner stations and online ordering with courier pickup.

[0044] In this example, the server determines the original recommended price of the target company's shipping products based on the original shipping data corresponding to the target company and by querying the existing shipping price ranking table stored in the system database. This makes the determined original recommended price of the target company more consistent with the actual situation. This method can determine the original recommended price of the target company of logistics and express delivery companies by directly querying the system database without developing a standard interface, making it more convenient to obtain the original recommended price.

[0045] The online operation period refers to the time during which the target company conducts its parcel delivery business online. The operational review period refers to the time during which the target company maintains its original recommended price. During this operational review period, the target company maintains its original recommended price and conducts its parcel delivery business. After the operational review period ends, the original recommended price is adjusted based on the data from the target company's parcel delivery business during this period.

[0046] As an example, in step S203, the server monitors the target company's online operation time based on the original recommended price and determines whether the online operation time has reached the operation review cycle. In this example, the server constantly monitors the target company's online parcel delivery service time and determines whether the target company's online parcel delivery service time has reached the operation review cycle in order to obtain the target adjustment strategy. In this example, the server monitors the target company's online operation time and determines whether the online operation time has reached the operation review cycle, providing feasibility for subsequently obtaining the target adjustment strategy.

[0047] Operational statistics, in this context, refer to the statistical data on product prices and order quantities of the target company during the operational review period after the initial recommended price has been determined. Target adjustment strategies refer to the methods used by the target company after the operational review period to adjust the initial recommended price and / or product availability to ensure the target company operates in accordance with actual conditions and maintains normal operations.

[0048] As an example, in step S204, after determining that the target company's online operation time has reached the operation review period, the server obtains the corresponding operational statistics for the target company. Based on the operational statistics and the original recommended price, it determines the target adjustment strategy. In this example, after determining that the target company's online operation time has reached the operation review period, the server obtains the statistical data on the target company's product prices and order quantities within the operation review period. Based on the product prices and order quantities, it formulates an appropriate target adjustment strategy to subsequently adjust the target company's original recommended price and / or product availability, ensuring the target company remains in a normal operational state. In this example, after reaching the operation review period, determining the target adjustment strategy based on the target company's operational statistics and original recommended price within the operation review period allows for timely adjustments to the target company based on actual operational conditions. This eliminates the need for developing standard interfaces, making price adjustments more timely and convenient.

[0049] The target recommended price refers to the shipping price of the target company after adjustment according to the target adjustment strategy. The target product delivery time refers to the product delivery time of the target company after adjustment according to the target adjustment strategy.

[0050] As an example, in step S205, the server determines the target recommended price and / or target product timeliness of the target enterprise based on the target adjustment strategy. In this example, after determining the target adjustment strategy, the server determines the method for determining the target recommended price and / or target product timeliness based on the determined target adjustment strategy: if it is necessary to increase the original recommended price or decrease the product timeliness, the increased shipping price is used as the target recommended price, or the decreased product timeliness is used as the target product timeliness; if it is necessary to decrease the original recommended price or increase the product timeliness, the decreased shipping price is used as the target recommended price, or the increased product timeliness is used as the target product timeliness; if no adjustment is required, the original recommended price and product timeliness are maintained, that is, the original recommended price is used as the target recommended price, and the maintained product timeliness is used as the target product timeliness. In this example, the server determines the target recommended price and / or target product timeliness of the target enterprise based on the target adjustment strategy without the need for standard interface development, and can determine the target recommended price and / or target product timeliness in a timely manner.

[0051] In one embodiment, when the server determines that the online operation time has not reached the operation review cycle, it sets the original recommended price as the target recommended price and keeps the product timeliness unchanged. In this example, if the target company's online operation time has not reached the operation review cycle, that is, the target company's online operation time has not reached the price adjustment point, therefore, the original recommended price is still set as the target recommended price, and the product timeliness remains unchanged, and the target company's parcel delivery business continues. In this example, when the target company's online operation time has not reached the conditions for adjusting parcel delivery product information, the original recommended price and product timeliness are not changed, making the setting of the target recommended price more reasonable.

[0052] The method for adjusting parcel delivery product information provided in this embodiment directly determines the original recommended price of the target enterprise by querying the system database based on the original parcel delivery data. This eliminates the need for standard interface development, saving technical resources and making price determination more convenient and faster. Furthermore, after the operational review cycle is completed, a target adjustment strategy is determined directly based on operational statistics and the original recommended price. Based on the target adjustment strategy, the target recommended price and / or target product timeliness of the target enterprise are determined, again without the need for standard interface development, saving development costs. This makes the adjustment of parcel delivery product information more timely and efficient, and ensures that the final adjusted parcel delivery product information, including the target recommended price and / or target product timeliness, better reflects the actual operational situation of the target enterprise.

[0053] In one embodiment, such as Figure 3 As shown, step S202, which involves determining the original recommended price for the target company based on its original shipping data and the existing shipping price ranking table stored in the system database, includes:

[0054] S301: Based on the smart locker parcel delivery data of the target enterprise and the price sorting table of locker type, price sorting table of regional type, and price sorting table of product timeliness stored in the system database, obtain the ranking results of locker type, ranking results of regional type, and ranking results of product timeliness respectively.

[0055] S302: Process the data results of the grid type ranking to determine the pricing benchmark for grid type;

[0056] S303: Process the data results of the regional type distance ranking to determine the regional type distance pricing benchmark;

[0057] S304: Process the product timeliness ranking results to determine the product timeliness pricing benchmark;

[0058] S305: Determine product pricing rules and industry ranking range based on pricing benchmarks for grid type, regional type distance pricing benchmarks, and product time-sensitive pricing benchmarks;

[0059] S306: Determine the original recommended price based on product pricing rules and industry ranking range.

[0060] In this example, the target company's original parcel delivery data includes the target company's smart locker parcel delivery data. Understandably, this example is used to determine the original recommended price for the smart locker corresponding to the target company.

[0061] In this example, the existing parcel delivery price ranking tables include a smart locker parcel delivery price ranking table by compartment type, a regional type distance price ranking table, and a product timeliness price ranking table. The compartment type price ranking table is formed by querying the parcel delivery prices for existing companies' smart locker compartment types based on compartment type and / or mapping the parcel weight and volume of existing companies' non-smart locker delivery methods, and then ranking the resulting prices for various compartment types. The regional type distance price ranking table is formed by querying the parcel delivery prices for existing companies' regional type distances based on regional type distance and then ranking them. The product timeliness price ranking table is formed by querying the parcel delivery prices for existing companies' corresponding product timeliness and then ranking them.

[0062] In this example, the server uses the above-mentioned grid type price ranking table, regional type distance price ranking table, and product timeliness price ranking table as the existing shipping price sorting table.

[0063] The ranking results for different smart cabinet types are as follows: Compartment type ranking: This ranking is based on the compartment type specified by the target company, retrieved from an existing price ranking table of smart cabinets by compartment type, and the corresponding price for the target company's smart cabinet. Regional distance ranking: This ranking is based on the regional distance specified by the target company, retrieved from an existing price ranking table of smart cabinets by regional distance, and the corresponding price for the product's timeliness.

[0064] As an example, in step S301, the server, based on the original parcel delivery data of the smart lockers corresponding to the target enterprise and the price sorting tables for locker types, distances, and product delivery times stored in the system database, obtains the ranking results for locker type, distance, and product delivery time, respectively. In this example, the server, based on the original parcel delivery data of the target enterprise, such as locker type, distance, and product delivery time, queries the pre-stored price sorting tables for locker type, distance, and product delivery time in the system database, filters them to obtain the price sorting tables for locker type, distance, and product delivery time corresponding to the target enterprise's smart lockers, and uses these as the ranking results for locker type, distance, and product delivery time, respectively. This example obtains the ranking results for locker type, distance, and product delivery time corresponding to the target enterprise's smart lockers, providing feasibility for subsequently obtaining the corresponding pricing benchmarks.

[0065] As an example, in step S302, the server processes the ranking results of the compartment types to determine the pricing benchmark for each compartment type. In this example, after obtaining the ranking results of the compartment types corresponding to the target company's smart cabinets, the server can process the ranking results to obtain the pricing benchmark for each compartment type of the target company's smart cabinets. For example, data processing methods such as the average or median price of the same compartment type in the ranking results can be selected to obtain the pricing benchmark for each compartment type of the target company's smart cabinets.

[0066] As an example, in step S303, the server processes the regional type distance ranking results to determine the regional type distance pricing benchmark. In this example, after obtaining the regional type distance ranking results corresponding to the target company's smart cabinets, the server can process the regional type distance ranking results to obtain the regional type distance pricing benchmark corresponding to the target company's smart cabinets. For example, data processing methods such as the average or median price of the same regional type distance in the regional type distance ranking results can be selected to obtain the regional type distance pricing benchmark for the smart cabinets corresponding to each regional type distance.

[0067] As an example, in step S304, the server processes the product timeliness ranking results to determine the product timeliness pricing benchmark. In this example, after obtaining the product timeliness ranking results for the target company, the server can process the product timeliness ranking results to obtain the product timeliness pricing benchmark for the smart cabinets corresponding to the target company. For example, data processing methods such as the average or median price of the same product timeliness in the product timeliness ranking results can be selected to obtain the product timeliness pricing benchmark for the smart cabinets corresponding to each product timeliness.

[0068] As an example, in step S305, after obtaining the pricing benchmarks for locker type, regional type distance, and product timeliness, the server determines the product pricing rules and industry ranking range based on these benchmarks. In this example, the server queries the ranking ranges corresponding to the locker type pricing benchmark, regional type distance pricing benchmark, and product timeliness pricing benchmark, respectively, to obtain the industry ranking range of the target company's smart locker parcel delivery pricing benchmark. The server then matches the target company's corresponding locker type, regional type distance, and product timeliness with the locker type pricing benchmark, regional type distance pricing benchmark, and product timeliness pricing benchmark, respectively, to obtain the target company's product pricing rules for smart locker parcel delivery. In this example, the product pricing rules and industry ranking range are determined based on the locker type pricing benchmark, regional type distance pricing benchmark, and product timeliness pricing benchmark, ensuring that the subsequently determined original recommended price aligns with the target company's actual smart locker parcel delivery pricing.

[0069] As an example, in step S306, the server determines the original recommended price based on the product pricing rules and the industry ranking range. In this example, the server can obtain the target company's smart locker's product pricing rules and the industry ranking under those rules, and then obtain the original recommended price, which includes the product pricing rules and the industry ranking under those rules. In this example, the obtained original recommended price is based on existing parcel delivery data from existing companies in the logistics field, which is consistent with reality.

[0070] The parcel delivery product information adjustment method provided in this embodiment involves the server obtaining the ranking results of the smart lockers of the target enterprise based on the original parcel delivery data corresponding to the smart lockers of the target enterprise, the ranking results of the smart locker type by region, and the ranking results of the product timeliness. Based on the ranking results of the smart lockers of the target enterprise, the server formulates a corresponding price benchmark, and then obtains the original recommended price of the smart lockers of the target enterprise. This makes the obtained original recommended price more reasonable and more in line with the actual situation, and provides feasibility for subsequent adjustment of the original recommended price to obtain the target recommended price.

[0071] In one embodiment, such as Figure 4 As shown, before step S202, that is, before obtaining the original shipment data of the target company, the process also includes:

[0072] S401: Obtain existing shipment data for existing companies;

[0073] S402: Transform and map existing parcel data to obtain the corresponding parcel type, area type distance, and product timeliness;

[0074] S403: Based on the grid type, area type distance, and product timeliness corresponding to all existing shipment data, obtain the existing shipment price sorting table, which includes the grid type price sorting table, area type distance price sorting table, and product timeliness price sorting table.

[0075] S404: Store the existing shipping price sorting table in the system database.

[0076] This example is used to determine the existing parcel delivery price ranking table corresponding to the smart locker of the target enterprise.

[0077] In this example, "existing enterprises" refers to logistics and express delivery companies that have already launched parcel delivery services; "existing parcel delivery data" refers to the parcel delivery data of existing enterprises, including indicators such as parcel delivery area type, distance between area types, weight of the parcel, type of product being delivered, volume of the parcel, and delivery timeliness. This indicator data can be parcel delivery data from existing enterprises' smart lockers or parcel delivery data from existing enterprises' non-smart locker delivery methods. The area type is used to distinguish whether the parcel can be delivered to the corresponding area, including two types: deliverable and undeliverable.

[0078] As an example, in step S401, the server obtains existing parcel delivery data corresponding to existing enterprises. Understandably, the server obtains indicator data of existing enterprises, including parcel delivery area type, area type distance, parcel weight, parcel product type, parcel volume, and parcel delivery timeliness, etc., which are used to subsequently obtain the price ranking table for locker type, price ranking table for area type distance, and price ranking table for product delivery timeliness, as a reference standard for determining the original recommended price of the smart locker for the target enterprise.

[0079] Among these, "Compartment Type" refers to the size of the compartments used by existing and target companies when using smart lockers for parcel delivery. "Area Type Distance" refers to the defined delivery distance for parcels when using smart lockers, such as 200km. "Product Delivery Time" refers to the defined timeframe for delivering the parcel to its destination, such as 1-day delivery or 3-day delivery.

[0080] As an example, in step S402, the server transforms and maps existing parcel delivery data to obtain the corresponding locker type, area type distance, and product timeliness. Understandably, existing parcel delivery data includes indicators such as parcel area type, area type distance, parcel item weight, parcel product type, parcel item volume, and parcel product timeliness. The parcel item weight, parcel product type, and parcel item volume determine the locker type used by the target company when sending parcels. Therefore, the parcel item weight, parcel product type, and parcel item volume are mapped to locker type, serving as one of the indicators for the target company to obtain the original recommended price. In this example, the server obtains the locker type, area type distance, and product timeliness based on the transformation and mapping of existing parcel delivery data, facilitating the subsequent determination of the corresponding price ranking table based on these factors.

[0081] As an example, in step S403, the server obtains an existing parcel delivery price ranking table based on the locker type, regional distance, and product timeliness corresponding to all existing parcel delivery data. In this example, the server obtains the locker type, regional distance, and product timeliness corresponding to the smart lockers of existing enterprises, and calculates the price requirements corresponding to the locker type, regional distance, and product timeliness, forming corresponding locker type price ranking tables, regional distance price ranking tables, and product timeliness price ranking tables; and uses these three tables as the existing parcel delivery price ranking table. In this example, obtaining the existing parcel delivery price ranking table makes it feasible to subsequently obtain the original recommended price for the target enterprise to use the smart locker for parcel delivery.

[0082] As an example, in step S404, the server stores the existing parcel delivery price ranking table in the system database. In this example, after obtaining the existing parcel delivery price ranking table corresponding to the smart locker type, area type distance, and product timeliness for each enterprise, the server stores the existing parcel delivery price ranking table in the system database. This facilitates subsequent queries of the existing parcel delivery price ranking table to determine the original recommended price for the target enterprise. In this example, storing the existing parcel delivery price ranking table in the system database makes subsequent queries of the existing parcel delivery price ranking table feasible, and it eliminates the need for standard interface development to obtain the original recommended price for the target enterprise to use the smart locker for parcel delivery, making it faster and more convenient.

[0083] The parcel delivery product information adjustment method provided in this embodiment stores the existing parcel delivery price ranking table in the system database, making it feasible to query the existing parcel delivery price ranking table in the future. Moreover, it can obtain the original recommended price of the target company's smart locker based on the existing parcel delivery price ranking table without the need for standard interface development, which is faster and more convenient.

[0084] In another embodiment, such as Figure 5 As shown, step S202, which involves determining the original recommended price for the target company based on its original shipping data and the existing shipping price ranking table stored in the system database, also includes:

[0085] S501: Based on the non-smart locker parcel delivery data of the target enterprise and the parcel item weight price sorting table, parcel item volume price sorting table, regional type distance price sorting table and product timeliness price sorting table stored in the system database, obtain the parcel item weight ranking result, parcel item volume ranking result, regional type distance ranking result and product timeliness ranking result respectively.

[0086] S502: Process the data of the ranking results of the weight of the shipped items to determine the pricing benchmark for the weight of the shipped items;

[0087] S503: Process the data of the ranking results of the volume of the shipped items to determine the pricing benchmark for the volume of the shipped items;

[0088] S504: Process the data results of the regional type distance ranking to determine the regional type distance pricing benchmark;

[0089] S505: Process the product timeliness ranking results to determine the product timeliness pricing benchmark;

[0090] S506: Determine product pricing rules and industry ranking range based on the pricing benchmarks for the weight of the shipped items, the pricing benchmarks for the distance between different regions, and the pricing benchmarks for product delivery time.

[0091] S507: Determine the original recommended price based on product pricing rules and industry ranking range.

[0092] In this example, the target company's original parcel delivery data includes parcel delivery data for non-smart locker methods. Understandably, this example is used to determine the original recommended price for parcel delivery using non-smart locker methods for the target company. Non-smart locker methods include delivery via courier stores or partner stations and delivery via online ordering and courier pickup.

[0093] In this example, the existing shipping price sorting tables include: a shipping item weight price sorting table, a shipping item volume price sorting table, a region type distance price sorting table, and a product timeliness price sorting table. Specifically, the shipping item weight price sorting table is a price sorting table obtained by sorting the shipping prices of existing companies based on the shipping product weight. The shipping item volume price sorting table is a price sorting table obtained by sorting the shipping prices of existing companies based on the shipping product volume. The region type distance price sorting table is a price sorting table obtained by querying the shipping prices of existing companies based on the region type distance. The product timeliness price sorting table is a price sorting table obtained by querying the shipping prices of existing companies based on the corresponding product timeliness.

[0094] In this example, the server uses the above-mentioned ranking tables for shipping item weight, shipping item volume, regional type distance, and product timeliness as existing shipping price sorting tables.

[0095] In this example, the ranking results for package weight refer to the price ranking results for the target company's non-smart locker shipping method based on the weight of the packages sent using the target company's chosen non-smart locker shipping method, obtained by querying an existing table of price rankings for package weight. The ranking results for package volume refer to the price ranking results for the target company's non-smart locker shipping method based on the volume of the packages sent using the target company's chosen non-smart locker shipping method, obtained by querying an existing table of price rankings for price based on ...

[0096] As an example, in step S501, the server, based on the target company's non-smart locker parcel delivery data and the parcel weight price ranking table, parcel volume price ranking table, regional type distance price ranking table, and product timeliness price ranking table stored in the system database, obtains the parcel weight ranking result, parcel volume ranking result, regional type distance ranking result, and product timeliness ranking result, respectively. In this example, the server, based on the target company's parcel weight, parcel volume, regional type distance, and product timeliness, queries the pre-stored parcel weight price ranking table, parcel volume price ranking table, regional type distance price ranking table, and product timeliness price ranking table in the system database, respectively, to obtain the parcel weight ranking result, parcel volume ranking result, regional type distance ranking result, and product timeliness ranking result corresponding to the target company's non-smart locker parcel delivery method. In this example, obtaining the parcel weight ranking result, parcel volume ranking result, regional type distance ranking result, and product timeliness ranking result corresponding to the target company's non-smart locker parcel delivery method provides feasibility for subsequently obtaining the corresponding pricing benchmark.

[0097] As an example, in step S502, the server processes the data of the ranking results of the shipped items by weight to determine the pricing benchmark for the shipped items by weight. In this example, after obtaining the ranking results of the shipped items by weight corresponding to the non-smart locker shipping methods of the target company, the server can process the data of the shipping item weight ranking results to obtain the pricing benchmark for the shipped items by weight corresponding to the non-smart locker shipping methods of the target company. For example, data processing methods such as the average or median of the weight price of the same type of item in the shipping item weight ranking results can be selected to obtain the pricing benchmark for the shipping item weight corresponding to each type of shipped item for the non-smart locker shipping methods of the target company.

[0098] As an example, in step S503, the server processes the ranking results of the shipment volume to determine the pricing benchmark for shipment volume. In this example, after obtaining the ranking results of the shipment volume corresponding to the non-smart locker shipment method of the target company, the server can process the ranking results to obtain the pricing benchmark for shipment volume corresponding to the non-smart locker shipment method of the target company. For example, data processing methods such as the average or median price of the same type of item in the shipment volume ranking results can be selected to obtain the pricing benchmark for shipment volume for each type of shipment volume corresponding to the non-smart locker shipment method of the target company.

[0099] As an example, in step S504, the server processes the regional type distance ranking results to determine the regional type distance pricing benchmark. In this example, after obtaining the regional type distance ranking results corresponding to the target company's non-smart locker parcel delivery methods, the server can process the regional type distance ranking results to obtain the regional type distance pricing benchmark corresponding to the target company's non-smart locker parcel delivery methods. For example, data processing methods such as the average or median price of the same regional type distance in the regional type distance ranking results can be selected to obtain the regional type distance pricing benchmark for each regional type distance corresponding to the non-smart locker parcel delivery method.

[0100] As an example, in step S505, the server processes the product timeliness ranking results to determine the product timeliness pricing benchmark. In this example, after obtaining the product timeliness ranking results for non-smart locker delivery methods within the target company, the server can process the product timeliness ranking results to obtain the product timeliness pricing benchmark for the target company's non-smart locker delivery methods. For example, data processing methods such as the average or median of the timeliness price for the same product in the product timeliness ranking results can be selected to obtain the product timeliness pricing benchmark for each product timeliness corresponding to the non-smart locker delivery method.

[0101] As an example, in step S506, after obtaining the pricing benchmarks for the weight, volume, compartment type, regional distance, and delivery time of the parcel, the server determines the product pricing rules and industry ranking range based on these benchmarks. In this example, the server queries the ranking ranges corresponding to the pricing benchmarks for the weight, volume, regional distance, and delivery time of the parcel, respectively, to obtain the industry ranking range for the target company's non-smart locker parcel delivery method. The server then matches the target company's corresponding parcel weight, volume, regional distance, and delivery time with the pricing benchmarks for the weight, volume, regional distance, and delivery time of the parcel, respectively, to obtain the target company's product pricing rules for the non-smart locker parcel delivery method. In this example, the product pricing rules and industry ranking range are determined based on the pricing benchmarks for the weight of the shipped items, the pricing benchmarks for the volume of the shipped items, the pricing benchmarks for the distance of the region type, and the pricing benchmarks for the product timeliness. This ensures that the subsequently determined original recommended price is consistent with the actual pricing of the target company's non-smart locker shipping method.

[0102] As an example, in step S507, the server determines the original recommended price based on the product pricing rules and the industry ranking range. In this example, the server can obtain the product pricing rules for the target company's non-smart locker parcel delivery method and the industry ranking under those rules, and then obtain the original recommended price, which includes the product pricing rules and the industry ranking under those rules. In this example, the obtained original recommended price is based on existing parcel delivery data from existing companies in the logistics field, which is consistent with reality.

[0103] The parcel delivery product information adjustment method provided in this embodiment involves the server obtaining the ranking results of parcel weight, parcel volume, regional type distance, and product timeliness for the non-smart locker parcel delivery method of the target enterprise based on the original parcel delivery data of the target enterprise. Based on the ranking results of the target enterprise, a corresponding price benchmark is formulated, thereby obtaining the original recommended price for the non-smart locker parcel delivery method of the target enterprise. This makes the obtained original recommended price more reasonable and more in line with the actual situation, providing feasibility for subsequent adjustment of the original recommended price to obtain the target recommended price.

[0104] In one embodiment, such as Figure 6 As shown, step S204, which involves determining the target adjustment strategy based on operational statistics and the original recommended price, includes:

[0105] S601: Based on operational statistics, obtain product price rankings and order quantity rankings;

[0106] S602: Determine the target adjustment strategy based on product price ranking and order quantity ranking.

[0107] Among these, product price ranking refers to the ranking of the target company's original recommended price among all existing companies. Order volume ranking refers to the ranking of the target company's order volume among all existing companies during the operational review period.

[0108] As an example, in step S601, the server obtains the target company's product price ranking and order quantity ranking based on operational statistics. In this example, the server queries the system database based on the target company's original recommended data and order quantity during the operational review period, obtaining the ranking of the target company's original recommended price among all existing companies, thus obtaining the product price ranking; and the ranking of the target company's order quantity during the operational review period among all existing companies, thus obtaining the order quantity ranking.

[0109] As an example, in step S602, the server determines the target adjustment strategy based on product price ranking and order quantity ranking. In this example, the server determines the adjustment strategy for the original recommended price, deciding whether to adopt a price increase adjustment strategy, a price decrease adjustment strategy, or a price protection adjustment strategy as the target adjustment strategy. In this example, obtaining the target adjustment strategy makes it feasible to subsequently obtain the target recommended price and / or the timeliness of the target product.

[0110] The method for adjusting shipping product information provided in this embodiment allows the server to determine the target adjustment strategy based on operational statistics from the operational review cycle. This eliminates the need to develop standard interfaces, saves technical resources, and makes price adjustments more timely and convenient.

[0111] In one embodiment, such as Figure 7 As shown, step S602, which involves determining the target adjustment strategy based on product price ranking and order quantity ranking, includes:

[0112] S701: Obtain the ranking difference between product price ranking and order quantity ranking;

[0113] S702: If the ranking difference is greater than the first preset threshold, the target adjustment strategy is determined to be a price reduction adjustment strategy;

[0114] S703: If the ranking difference is not less than the second preset threshold and not greater than the first preset threshold, then the target adjustment strategy is determined to be the price protection adjustment strategy.

[0115] S704: If the ranking difference is less than the second preset threshold, the target adjustment strategy is determined to be a price increase adjustment strategy.

[0116] The first preset threshold and the second preset threshold are used to determine the final target adjustment strategy, and can be set to corresponding constants according to the actual situation.

[0117] As an example, in step S701, the server performs a difference calculation on the product price ranking and the order quantity ranking to obtain the difference between them. This difference reflects the level of the original recommended price, facilitating subsequent adjustments to the original recommended price and determining the target recommended price.

[0118] The first preset threshold is greater than zero, which is used to determine whether the product price ranking is higher than the order quantity ranking.

[0119] As an example, in step S702, if the server determines that the ranking difference is greater than the first preset threshold, then the product price ranking is much higher than the order quantity ranking, which means that the original recommended price is too high, and the price reduction adjustment strategy will be used as the target adjustment strategy.

[0120] The first and second preset thresholds are used to evaluate the thresholds for different adjustment strategies corresponding to the difference between product price ranking and order quantity ranking. As an example, the first preset threshold is greater than the second preset threshold. For instance, the first preset threshold can be a threshold greater than zero, while the second preset threshold can be a threshold less than zero. Their absolute values ​​can be the same or different.

[0121] As an example, in step S703, if the server determines that the ranking difference is not less than the second preset threshold and not greater than the first preset threshold, then the product price ranking and the order quantity ranking are equal, indicating that the original recommended price is reasonable, and the price protection adjustment strategy is determined as the target adjustment strategy.

[0122] As an example, in step S704, if the server determines that the ranking difference is less than the second preset threshold, then the product price ranking is much lower than the order quantity ranking, indicating that the original recommended price is too low, and the price increase adjustment strategy is determined as the target adjustment strategy.

[0123] The method for adjusting shipping product information provided in this embodiment determines the relationship between product price ranking and order quantity ranking based on the ranking difference between product price ranking and order quantity ranking, reflects the level of the original recommended price, determines the target adjustment strategy, and facilitates subsequent adjustment of shipping product information according to the target adjustment strategy to determine the target recommended price and / or target product timeliness.

[0124] In one embodiment, such as Figure 8 As shown, step S205, which involves determining the target recommended price and / or target product timeliness for the target company based on the target adjustment strategy, includes:

[0125] S801: Based on operational statistics, obtain the recommended price range corresponding to the operational statistics.

[0126] S802: If the target adjustment strategy is a price reduction adjustment strategy, then the original recommended price will be reduced according to the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, or the timeliness of the target product for the target company will be improved.

[0127] S803: If the target adjustment strategy is a price maintenance adjustment strategy, then the original recommended price will be determined as the target recommended price corresponding to the target company, and the timeliness of the target product corresponding to the target company will be maintained;

[0128] S804: If the target adjustment strategy is a price increase adjustment strategy, then the original recommended price will be increased based on the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, or the timeliness of the target product for the target company will be reduced.

[0129] The recommended price range refers to the constrained price range when adjusting the original recommended price according to the target adjustment strategy, which is used to constrain the adjustment range of the original recommended price.

[0130] As an example, in step S801, the server obtains the recommended price range corresponding to the operational statistics data. In this example, the operational statistics data includes the target company's product prices and order quantities during the operational review period. The server determines the recommended price range based on the product prices and order quantities.

[0131] As an example, in step S802, if the server determines that the target adjustment strategy is a price reduction adjustment strategy, it reduces the original recommended price based on the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, or improves the delivery time of the target product for the target company. In this example, if it is a price reduction adjustment strategy, the original recommended price is reduced within the recommended price range to obtain the target recommended price for the target company, or the delivery time of the target product for the target company is improved. Understandably, if the target adjustment strategy is a price reduction adjustment strategy, the product delivery time is improved accordingly, and the improved product delivery time is used as the target product delivery time for the target company. Product delivery time reflects the speed of delivery of the shipped product; the higher the product delivery time, the higher the original recommended price. Therefore, when a price reduction adjustment strategy is used, it indicates that the original recommended price is too high. Improving product delivery time allows customers to receive shipping services with a higher original recommended price, and by improving the quality of shipping services for customers, the price reduction adjustment strategy is achieved. In this embodiment, price reduction adjustments are made based on the recommended price range to make the target recommended price more consistent with the actual situation.

[0132] As an example, in step S803, if the server determines that the target adjustment strategy is a price protection adjustment strategy, then the original recommended price is used as the target recommended price, and the existing product validity period is used as the target product validity period. Understandably, if the server determines that the target adjustment strategy is a price protection adjustment strategy, it means that the currently set original recommended price is reasonable; therefore, the original recommended price is used as the target recommended price, and the existing product validity period is used as the target product validity period.

[0133] As an example, in step S804, if the server determines that the target adjustment strategy is a price increase adjustment strategy, it increases the original recommended price based on the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, or reduces the delivery time of the target product for the target company. In this example, if it is a price increase adjustment strategy, the original recommended price is increased within the recommended price range to obtain the target recommended price for the target company, or the delivery time of the target product for the target company is reduced. Understandably, if the target adjustment strategy is a price increase adjustment strategy, the product delivery time is reduced accordingly, and the reduced product delivery time is used as the target product delivery time for the target company. Product delivery time reflects the speed of delivery of the shipped product; the lower the product delivery time, the lower the original recommended price. Therefore, when a price increase adjustment strategy is used, it indicates that the original recommended price is too low. The price increase adjustment strategy can be achieved by reducing the product delivery time to provide customers with a lower delivery service at the original recommended price, thereby reducing the quality of delivery service for customers. In this embodiment, the price adjustment is based on the recommended price range to make the target recommended price more consistent with the actual situation.

[0134] The parcel delivery product information adjustment method provided in this embodiment involves the server adjusting the parcel delivery product information of the target enterprise, including the target recommended price and / or the target product timeliness, within the recommended price range according to the target adjustment strategy, thereby obtaining the target recommended price and / or the target product timeliness, so that the final obtained target recommended price and / or target product timeliness are more in line with the actual situation.

[0135] In one embodiment, step S802, i.e., if the target adjustment strategy is a price reduction adjustment strategy, involves reducing the original recommended price based on the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, including:

[0136] S8021: If the target adjustment strategy is a price reduction adjustment strategy, the target recommended price shall not be lower than the minimum value of the recommended price range.

[0137] As an example, in step S8021, if the server determines that the target adjustment strategy is a price reduction adjustment strategy, then the target recommended price will not be lower than the minimum value of the recommended price range. Understandably, if a price reduction adjustment strategy is implemented, a price reduction needs to be made within the recommended price range, and the target recommended price after the price reduction cannot be lower than the recommended price range. In this example, specifying that the target recommended price cannot be lower than the minimum value of the recommended price range ensures that the final target recommended price is reasonable.

[0138] In one embodiment, step S804, i.e., if the target adjustment strategy is a price increase adjustment strategy, involves increasing the original recommended price based on the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, including:

[0139] S8041: If the target adjustment strategy is a price increase adjustment strategy, then the target recommended price shall not be higher than the maximum value of the recommended price range.

[0140] As an example, in step S8041, if the server determines that the target adjustment strategy is a price increase adjustment strategy, then the target recommended price will not exceed the maximum value of the recommended price range. Understandably, if a price increase adjustment strategy is implemented, the price needs to be increased within the recommended price range, and the target recommended price after the price increase cannot exceed the recommended price range. In this example, specifying that the target recommended price cannot exceed the maximum value of the recommended price range ensures that the final target recommended price is reasonable.

[0141] In one embodiment, such as Figure 9 As shown, step S801, which involves obtaining the recommended price range corresponding to the operational statistics based on operational statistics, includes:

[0142] S901: Based on operational statistics, obtain product price rankings and order quantity rankings;

[0143] S902: Obtain the competitiveness ranking of target companies based on product price ranking and order quantity ranking;

[0144] S903: Based on the target company's competitiveness ranking, obtain the recommended price range corresponding to the operational statistics.

[0145] As an example, in step S901, the server obtains the product price ranking and order quantity ranking based on operational statistics. In this example, the server queries the system database based on the target company's original recommended data and order quantity during the operational review period to obtain the ranking of the target company's original recommended price among all existing companies, thus obtaining the product price ranking; and the ranking of the target company's order quantity among all existing companies during the operational review period, thus obtaining the order quantity ranking. In this example, obtaining the product price ranking and order quantity ranking facilitates the subsequent determination of the target company's competitiveness ranking based on these rankings.

[0146] Among them, the target company's competitiveness ranking refers to the target company's overall ranking among all existing companies, reflecting the target company's future competitive level among existing companies.

[0147] As an example, in step S902, the server obtains the target company's competitiveness ranking based on product price ranking and order quantity ranking. In this example, the server uses the method of summing the product price ranking and order quantity ranking and then taking the average to obtain the target company's competitiveness ranking. In this example, the server obtains the target company's competitiveness ranking based on both product price ranking and order quantity ranking, making the obtained competitiveness ranking more consistent with the actual operation of the target company.

[0148] As an example, in step S903, the server determines the price range of the shipping products where the target company's competitiveness ranking falls, and uses this price range as the recommended price range. In this example, using the price range of the shipping products where the target company's competitiveness ranking falls as the recommended price range facilitates subsequent adjustments to the original recommended price within this recommended price range.

[0149] The method for adjusting shipping product information provided in this embodiment involves the server determining the competitive ranking of the target company based on operational statistics, and then determining a recommended price range based on the competitive ranking of the target company. This ensures that the obtained recommended price range is more consistent with the actual operational situation of the target company during the operational review period, providing feasibility for subsequent implementation of target adjustment strategies based on the recommended price range.

[0150] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0151] In one embodiment, a device for adjusting parcel product information is provided, which corresponds one-to-one with the parcel product information adjustment method described in the above embodiments. For example... Figure 10 As shown, the parcel delivery product information adjustment device includes a raw parcel delivery data acquisition module 1001, a raw recommended price acquisition module 1002, an operational review cycle monitoring module 1003, a target adjustment strategy determination module 1004, and a target adjustment strategy execution module 1005. Detailed descriptions of each functional module are as follows:

[0152] The original shipment data acquisition module 1001 is used to acquire the original shipment data of the target company.

[0153] The original recommended price acquisition module 1002 is used to determine the original recommended price of the target company based on the target company's original shipment data and the existing shipment price sorting table stored in the system database;

[0154] The Operation Review Cycle Monitoring Module 1003 is used to monitor the online operation time of the target enterprise based on the original recommended price and determine whether the online operation time has reached the operation review cycle.

[0155] The target adjustment strategy determination module 1004 is used to obtain the corresponding operational statistics of the target enterprise if the online operation time reaches the operation review cycle, and determine the target adjustment strategy based on the operational statistics and the original recommended price.

[0156] The target adjustment strategy execution module 1005 is used to determine the target recommended price and / or the target product timeliness of the target enterprise based on the target adjustment strategy.

[0157] In one embodiment, the original recommended price acquisition module 1002 includes:

[0158] The first ranking result acquisition submodule, based on the smart locker parcel delivery data of the target enterprise and the price sorting table of locker type, the price sorting table of regional type distance, and the price sorting table of product timeliness stored in the system database, acquires the ranking results of locker type, the ranking results of regional type distance, and the ranking results of product timeliness, respectively.

[0159] The grid type pricing benchmark determination submodule is used to process the grid type ranking results and determine the grid type pricing benchmark.

[0160] The first regional type distance pricing benchmark determination submodule is used to process the regional type distance ranking results and determine the regional type distance pricing benchmark.

[0161] The first product time-of-delivery pricing benchmark determination submodule is used to process the product time-of-delivery ranking results and determine the product time-of-delivery pricing benchmark.

[0162] The first product pricing rules and industry ranking range determination submodule is used to determine product pricing rules and industry ranking range based on grid type pricing benchmark, regional type distance pricing benchmark, and product time-of-use pricing benchmark;

[0163] The first original recommended price determination submodule is used to determine the original recommended price based on the product pricing rules and industry ranking range.

[0164] The target company's original parcel delivery data includes the target company's smart locker parcel delivery data; the existing parcel delivery price ranking tables include a locker type price ranking table, a region type distance price ranking table, and a product timeliness price ranking table.

[0165] In another embodiment, the mailing product information adjustment device further includes:

[0166] The existing shipment data acquisition module is used to acquire existing shipment data for existing enterprises.

[0167] The conversion and mapping module is used to convert and map existing shipment data to obtain the corresponding parcel type, area type distance, and product timeliness.

[0168] The module for obtaining the existing parcel shipping price sorting table is used to obtain the existing parcel shipping price sorting table based on the grid type, area type distance, and product timeliness corresponding to all existing parcel shipping data.

[0169] An existing shipping price sorting table storage module is used to store the existing shipping price sorting table in the system database.

[0170] The existing shipping price ranking tables include a grid type price ranking table, a regional type distance price ranking table, and a product time-sensitivity price ranking table.

[0171] In another embodiment, the original recommended price acquisition module 1002 further includes:

[0172] The second ranking result acquisition submodule, based on the non-smart locker parcel delivery data of the target enterprise and the parcel item weight price sorting table, parcel item volume price sorting table, regional type distance price sorting table and product timeliness price sorting table stored in the system database, respectively acquires the parcel item weight ranking result, parcel item volume ranking result, regional type distance ranking result and product timeliness ranking result;

[0173] The "Determine Pricing Benchmark by Weight of Shipped Items" submodule is used to process the data of the ranking results of the weight of shipped items and determine the pricing benchmark by weight of shipped items.

[0174] The "Determine Pricing Benchmark by Volume of Shipped Items" submodule is used to process the data of the ranking results of the volume of shipped items and determine the pricing benchmark by volume of shipped items.

[0175] The second regional type distance pricing benchmark determination submodule is used to process the regional type distance ranking results and determine the regional type distance pricing benchmark.

[0176] The second product time-of-delivery pricing benchmark determination submodule is used to process the product time-of-delivery ranking results and determine the product time-of-delivery pricing benchmark.

[0177] The second product pricing rules and industry ranking range determination submodule is used to determine product pricing rules and industry ranking range based on the pricing benchmark of the weight of the shipped item, the pricing benchmark of the distance between the region type and the region type, and the pricing benchmark of the product timeliness.

[0178] The second original recommended price determination submodule is used to determine the original recommended price based on the product pricing rules and industry ranking range.

[0179] The target company's original parcel delivery data includes parcel delivery data for non-smart locker methods; the existing parcel delivery price ranking tables include a price ranking table based on parcel weight, parcel volume, regional type distance, and product delivery time.

[0180] In one embodiment, the target adjustment strategy determination module 1004 includes:

[0181] The ranking acquisition submodule is used to obtain product price ranking and order quantity ranking based on operational statistics.

[0182] The target adjustment strategy determination submodule is used to determine the target adjustment strategy based on product price ranking and order quantity ranking.

[0183] In one embodiment, the target adjustment strategy determination submodule includes:

[0184] The ranking difference acquisition unit is used to obtain the ranking difference between product price ranking and order quantity ranking;

[0185] The first target adjustment strategy determination unit is used to determine the target adjustment strategy as a price reduction adjustment strategy if the ranking difference is greater than the first preset threshold.

[0186] The second target adjustment strategy determination unit is used to determine the target adjustment strategy as the price protection adjustment strategy if the ranking difference is not less than the second preset threshold and not greater than the first preset threshold.

[0187] The third target adjustment strategy determination unit is used to determine the target adjustment strategy as a price increase adjustment strategy if the ranking difference is less than the second preset threshold.

[0188] The first preset threshold is greater than the second preset threshold.

[0189] In one embodiment, the target adjustment strategy execution module 1005 includes:

[0190] The recommended price range acquisition submodule is used to obtain the recommended price range corresponding to the operational statistics based on the operational statistics data.

[0191] The first target adjustment strategy execution submodule is used to reduce the original recommended price based on the recommended price range corresponding to the operational statistics if the target adjustment strategy is a price reduction strategy, thereby obtaining the target recommended price for the target company or improving the timeliness of the target product for the target company.

[0192] The second target adjustment strategy execution submodule is used to determine the original recommended price as the target recommended price corresponding to the target enterprise and maintain the timeliness of the target product corresponding to the target enterprise if the target adjustment strategy is a price protection adjustment strategy.

[0193] The third target adjustment strategy execution submodule is used to increase the original recommended price based on the recommended price range corresponding to the operational statistics if the target adjustment strategy is a price increase strategy, thereby obtaining the target recommended price for the target company, or reducing the timeliness of the target product for the target company.

[0194] In one embodiment, the recommended price range acquisition submodule includes:

[0195] The ranking acquisition unit is used to obtain product price rankings and order quantity rankings based on operational statistics.

[0196] The competitiveness ranking acquisition unit is used to obtain the competitiveness ranking of target companies based on product price and order quantity.

[0197] The recommended price range acquisition unit is used to obtain the recommended price range corresponding to the operational statistics based on the target company's competitiveness ranking.

[0198] Specific limitations regarding the device for adjusting shipment product information can be found in the limitations of the method for adjusting shipment product information above, and will not be repeated here. Each module in the aforementioned device for adjusting shipment product information can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0199] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 11 As shown. The computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data used in the execution of a method for adjusting mail product information. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for adjusting mail product information.

[0200] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the mail product information adjustment method described in the above embodiments, for example... Figure 2As shown in S201-S205, or Figures 3 to 9 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the mail delivery product information adjustment device, for example... Figure 10 The functions of the original shipment data acquisition module 1001, the original recommended price acquisition module 1002, the operation review cycle monitoring module 1003, the target adjustment strategy determination module 1004, and the target adjustment strategy execution module 1005 shown are not described in detail here to avoid repetition.

[0201] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program implements the mail product information adjustment method described in the above embodiment, for example... Figure 2 As shown in S201-S205, or Figures 3 to 9 As shown, to avoid repetition, it will not be described again here. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in this embodiment of the mail delivery product information adjustment device, for example... Figure 10 The functions of the original shipment data acquisition module 1001, the original recommended price acquisition module 1002, the operation review cycle monitoring module 1003, the target adjustment strategy determination module 1004, and the target adjustment strategy execution module 1005 shown are not described again here to avoid repetition. The computer-readable storage medium may be non-volatile or volatile.

[0202] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0203] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0204] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for adjusting product information for shipped items, characterized in that, include: Obtain the target company's original shipment data; Based on the target company's original shipping data and the existing shipping price ranking table stored in the system database, the original recommended price of the target company is determined; Monitor the online operation time of the target enterprise based on the original recommended price, and determine whether the online operation time has reached the operation review cycle; If the online operation time reaches the operation review cycle, then obtain the operation statistics data corresponding to the target enterprise, and obtain the product price ranking and order quantity ranking based on the operation statistics data; Obtain the ranking difference between the product price ranking and the order quantity ranking; If the ranking difference is greater than the first preset threshold, then the target adjustment strategy is determined to be a price reduction adjustment strategy; If the ranking difference is not less than the second preset threshold and not greater than the first preset threshold, then the target adjustment strategy is determined to be a price maintenance adjustment strategy. If the ranking difference is less than the second preset threshold, then the target adjustment strategy is determined to be a price increase adjustment strategy; wherein, the first preset threshold is greater than the second preset threshold; Based on the target adjustment strategy, the target recommended price and / or target product timeliness of the target enterprise are determined, including: if it is necessary to increase the original recommended price or decrease the product timeliness, the increased shipping price is used as the target recommended price, or the decreased product timeliness is used as the target product timeliness; if it is necessary to decrease the original recommended price or increase the product timeliness, the decreased shipping price is used as the target recommended price, or the increased product timeliness is used as the target product timeliness; if no adjustment is required, the original recommended price and product timeliness are maintained, the original recommended price is used as the target recommended price, and the maintained product timeliness is used as the target product timeliness.

2. The method for adjusting shipment product information as described in claim 1, characterized in that, The target company's original parcel delivery data includes the target company's smart locker parcel delivery data; The existing parcel delivery price sorting table includes a grid type price sorting table, a region type distance price sorting table, and a product timeliness price sorting table. The determination of the target company's original recommended price based on the target company's original shipping data and the existing shipping price ranking table stored in the system database includes: Based on the smart locker parcel delivery data of the target enterprise and the price sorting tables of locker type, regional type distance price sorting tables, and product timeliness price sorting tables stored in the system database, the ranking results of locker type, regional type distance ranking results, and product timeliness ranking results are obtained respectively. The ranking results of the grid types are processed to determine the pricing benchmark for the grid types; Data processing is performed on the distance ranking results of the region types to determine the pricing benchmark for distance of the region types; The product timeliness ranking results are processed to determine the product timeliness pricing benchmark; Based on the pricing benchmark for the grid type, the pricing benchmark for the regional type, and the pricing benchmark for the product timeliness, determine the product pricing rules and industry ranking range; The original recommended price is determined based on the product pricing rules and the industry ranking range.

3. The method for adjusting shipment product information as described in claim 2, characterized in that, Before obtaining the target company's original mailing data, the process also includes: Obtain existing shipment data for existing companies; The existing parcel data is transformed and mapped to obtain the corresponding parcel type, area type distance, and product timeliness. Based on the compartment type, area type distance, and product timeliness corresponding to all the existing parcel shipping data, obtain the existing parcel shipping price sorting table, which includes a compartment type price sorting table, an area type distance price sorting table, and a product timeliness price sorting table. The existing shipping price sorting table is stored in the system database.

4. The method for adjusting shipment product information as described in claim 1, characterized in that, The target company's original parcel delivery data includes parcel delivery data from non-smart locker delivery methods. The existing shipping price ranking tables include a shipping item weight price ranking table, a shipping item volume price ranking table, a region type distance price ranking table, and a product timeliness price ranking table. The determination of the target company's original recommended price based on the target company's original shipping data and the existing shipping price ranking table stored in the system database includes: Based on the non-smart locker parcel delivery data of the target enterprise and the parcel item weight price sorting table, parcel item volume price sorting table, regional type distance price sorting table and product timeliness price sorting table stored in the system database, the parcel item weight ranking result, parcel item volume ranking result, regional type distance ranking result and product timeliness ranking result are obtained respectively. The data from the ranking results of the shipped items by weight is processed to determine the pricing benchmark for the shipped items by weight; The data from the ranking results of the shipped items by volume is processed to determine the pricing benchmark for shipped items by volume; Data processing is performed on the distance ranking results of the region types to determine the pricing benchmark for distance of the region types; The product timeliness ranking results are processed to determine the product timeliness pricing benchmark; Based on the pricing benchmarks for the weight of the shipped items, the pricing benchmarks for the volume of the shipped items, the pricing benchmarks for the distance of the region type, and the pricing benchmarks for the product's delivery time, the product pricing rules and industry ranking range are determined. The original recommended price is determined based on the product pricing rules and the industry ranking range.

5. The method for adjusting shipment product information as described in claim 1, characterized in that, The step of determining the target recommended price and / or target product timeliness of the target enterprise based on the target adjustment strategy includes: Based on the operational statistics, obtain the recommended price range corresponding to the operational statistics. If the target adjustment strategy is a price reduction adjustment strategy, then the original recommended price is reduced according to the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target enterprise, or the timeliness of the target product for the target enterprise is improved. If the target adjustment strategy is a price protection adjustment strategy, then the original recommended price is determined as the target recommended price corresponding to the target enterprise, and the timeliness of the target product corresponding to the target enterprise is maintained; If the target adjustment strategy is a price increase strategy, then the original recommended price is increased based on the recommended price range corresponding to the operational statistics data to obtain the target recommended price for the target company, or the timeliness of the target product for the target company is reduced.

6. The method for adjusting shipment product information as described in claim 5, characterized in that, The step of obtaining the recommended price range corresponding to the operational statistics data includes: Based on the aforementioned operational statistics, obtain product price rankings and order quantity rankings; Based on the product price ranking and the order quantity ranking, obtain the target company's competitiveness ranking; Based on the competitiveness ranking of the target company, obtain the recommended price range corresponding to the operational statistics.

7. A device for adjusting shipment product information, used to implement the shipment product information adjustment method according to any one of claims 1 to 6, characterized in that, The device includes: The original shipment data acquisition module is used to acquire the original shipment data of the target company; The original recommended price acquisition module is used to determine the original recommended price of the target company based on the target company's original shipment data and the existing shipment price sorting table stored in the system database; The Operation Review Cycle Monitoring Module is used to monitor the online operation time of the target enterprise based on the original recommended price and determine whether the online operation time has reached the operation review cycle. The target adjustment strategy determination module is used to obtain the corresponding operational statistics of the target enterprise if the online operation time reaches the operation review cycle, and determine the target adjustment strategy based on the operational statistics and the original recommendation price. The target adjustment strategy execution module is used to determine the target recommended price and / or target product timeliness of the target enterprise according to the target adjustment strategy.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the mail product information adjustment method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the mail product information adjustment method as described in any one of claims 1 to 6.

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