A method and system for unified management of cross-platform sales data

Abstract

The application discloses a kind of unified management method and system of cross-platform sales data, comprising: collecting the original sales data of each channel, the original sales data is converted into uniform sales fact record, constructs channel capacity model, allocates a group of capacity labels for each channel, dynamically loads corresponding channel business strategy, utilizes rule engine to execute cross-channel collaborative processing, the uniform sales fact record of whole channel is summarized, and multidimensional analysis result is generated, the application relates to sales data management technical field, by channel adapter and configuration access specification, the uniform sales fact record of multiple source heterogeneous channel data is converted, the standardization of whole channel data is realized, the problem of each channel data fragmentation is solved;Different channel is dynamically loaded by channel capacity model Differentiated business strategy, improve the adaptability of system to direct sales, distribution, online self-operation and other multiple sales modes.

Description

Technical Field

[0001] This invention relates to the field of sales data management technology, specifically to a unified management method and system for cross-platform sales data. Background Technology

[0002] With the diversification of business sales models, a single company often operates multiple sales channels simultaneously, including direct sales, distribution and agency, online self-operation, bidding and tendering, and internal service settlement. Each channel typically uses an independent system, such as a customer relationship management system, enterprise resource planning system, e-commerce back-end, project management system, or spreadsheet, with data isolated between the systems.

[0003] This data silo situation leads to the following problems: transaction records for the same customer across different channels cannot be linked, making it difficult to form a complete customer profile; inventory, pricing, and credit limits are independently managed across channels, easily leading to overselling or price conflicts between different channels; the attribution of payments and sales performance is chaotic, for example, when direct sales teams and distributors have overlapping orders for the same customer, performance cannot be clearly defined, and cross-selling exists between online and offline channels; management cannot analyze the true contribution and cost of each channel from a holistic perspective, making it difficult to optimize resource allocation. Therefore, there is an urgent need for a method and system that can uniformly manage omnichannel sales data. Summary of the Invention

[0004] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a unified management method and system for cross-platform sales data, in order to solve the problem of fragmented data across sales channels and the inability to manage it in a unified manner.

[0005] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a unified management method for cross-platform sales data, comprising: S1. Collect raw sales data for each sales channel by configuring an independent channel adapter for each channel; S2. According to the preset mapping configuration, the original sales data is converted into a unified sales fact record. The unified sales fact record includes channel code, unified customer identifier, unified product identifier, sales amount and channel-specific attribute fields. The channel-specific attribute fields store channel extended data not included in the general fields in JSON format. S3. Construct a channel capability model and assign a set of capability tags to each channel. The capability tags indicate whether the channel supports pricing, inventory management, independent settlement, and credit control. S4. Based on the capability tags, dynamically load the corresponding channel business strategies, including inventory allocation strategies and settlement strategies; S5. Utilize a rules engine to perform cross-channel collaborative processing, which includes: merging customers from different channels to generate a unified customer identifier; performing order collision detection on sales opportunities from direct sales channels and distribution channels for the same customer and determining performance attribution based on a preset time window and reporting rules; monitoring order prices in each channel and triggering an alarm when the sales price of any order is lower than the minimum selling price allowed by the channel; and accumulating the total outstanding receivables of the same customer across all channels, blocking new orders when the accumulated amount exceeds the customer's shared credit limit. S6. Summarize the unified sales fact records across all channels and generate a multidimensional analysis result that includes at least one of the following indicators: sales revenue, order volume, and channel contribution profit for each channel.

[0006] In some embodiments, the inventory allocation strategy includes: When any channel’s capability tag indicates that it manages inventory, the channel’s inventory is divided into owned inventory and virtual inventory. The owned inventory is physical inventory that the channel owns the rights to and can directly control. The virtual inventory is other channel’s salable inventory that is visible to the channel but whose ownership does not belong to the channel. When the channel experiences a stock shortage and the capability tag allows the use of inventory from other channels, the system automatically selects the virtual inventory source that is closest to the stock-out channel based on the principle of proximity to the inventory in geographical location, and generates an allocation instruction to transfer the virtual inventory to the channel.

[0007] In some embodiments, the channel adapter in step S1 performs data collection and transformation by loading the channel access specifications stored in the configuration center. The channel access specifications include data source type, triggering method, key data item mapping, and status mapping.

[0008] In some embodiments, in step S2, the original sales data is converted into the unified sales fact record, and the original order status of each channel is mapped to a unified status identifier, which includes pending, confirmed, shipped, settled and returned.

[0009] In some embodiments, step S5, which involves merging customers from different channels to generate the unified customer identifier, includes: Obtain customer attribute information from various channels, including unified social credit code, mobile phone number, and company name; The similarity of the customer attribute information is calculated using a fuzzy matching algorithm. Customers with similarity exceeding a preset threshold are merged and assigned a unified customer identifier.

[0010] In some embodiments, the order collision detection and performance attribution determination according to the preset time window and the reporting rules in step S5 includes: When it is detected that the direct sales channel and the distribution channel generate the sales opportunity for the same unified customer ID, check whether there is a valid reporting record; If the aforementioned reporting record exists and the reporting time is within the preset time window, the performance will be attributed to the reporting party. If the reported record does not exist or the preset time window has expired, the collision event record will be written into the dispute event table and marked as pending adjudication.

[0011] In some embodiments, monitoring order prices across channels in step S5 includes: For each order placed through the online self-operated channel, the sales price is obtained in real time and compared with the preset channel price floor threshold. If the selling price is lower than the channel price threshold, a price anomaly alarm is generated and written to the alarm log.

[0012] In some embodiments, step S5 involves accumulating the total outstanding receivables of the same customer across all channels, and blocking new orders when the accumulated amount exceeds the customer's shared credit limit, including: Upon receiving a new order, query the sum of the outstanding orders across all channels for the customer corresponding to the new order; The sum of the aforementioned amounts plus the amount of the new order yields the estimated total receivable. If the estimated total receivables exceeds the customer's shared credit limit, the new order is rejected and an over-limit notification is displayed; otherwise, the new order is accepted and the available credit limit is deducted.

[0013] In some embodiments, it also includes: S7. Obtain settlement statement files from various channels according to a preset cycle, automatically match the settlement records in the settlement statement files with the unified sales fact records stored locally, mark the discrepancies for records that do not match, and generate a channel reconciliation discrepancy table. S8. Calculate the channel contribution profit for each channel. The channel contribution profit is equal to the sales revenue of the channel minus the corresponding product cost, channel fee and allocated service cost. The allocated service cost is calculated by allocating the total service cost based on the proportion of each channel's sales to the total sales.

[0014] Secondly, the present invention also discloses a unified management system for cross-platform sales data, including a processor, a memory, a communication module, a channel access gateway, a data standardization module, a channel capability model library, a channel strategy engine, and a unified data storage unit. The memory is used to store computer programs; The channel access gateway includes multiple channel adapters corresponding to the sales channels, used to collect the original sales data of each channel; The data standardization module is used to convert the original sales data into the unified sales fact record according to the preset mapping configuration. The channel capability model library stores the capability tags for each channel; The channel strategy engine is used to dynamically load the corresponding channel business strategy based on the capability tag, and to execute the cross-channel collaborative processing using the rule engine; The communication module is used for data interaction with external channel systems; When the processor executes the computer program stored in the memory, it controls the channel access gateway, the data standardization module, the channel capability model library, the channel strategy engine, and the unified data storage unit to realize the unified management method of cross-platform sales data.

[0015] (III) Beneficial Effects The beneficial effects of this invention are: The unified management method and system for cross-platform sales data provided by this invention transforms multi-source heterogeneous channel data into unified sales fact records through channel adapters and configurable access specifications, achieving standardized aggregation of data across all channels and solving the problem of data fragmentation among channels. By dynamically loading differentiated business strategies for different channels through a channel capability model, the system's adaptability to various sales models such as direct sales, distribution, and online self-operation is improved. Through a rule engine driving customer merging, order collision detection, price monitoring, and credit limit sharing, collaborative conflicts such as inconsistent customer identities, chaotic performance attribution, low-price cross-selling, and excessive accounts receivable are effectively resolved. Finally, by using a channel profit accounting method that allocates service costs according to sales revenue, the system provides enterprises with a quantitative basis for the true contribution of each channel. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0017] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] The unified management method for cross-platform sales data proposed in this invention achieves integrated management of orders, inventory, customers, and funds across all channels by constructing a unified sales data platform with the channel as the primary perspective.

[0019] To better understand the above technical solutions, exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present invention can be understood more clearly and thoroughly, and that the scope of the present invention can be fully conveyed to those skilled in the art.

[0020] Example Please see Figure 1 This invention provides a technical solution: a unified management method for cross-platform sales data. By constructing a unified sales data platform with a channel-centric perspective, it transforms heterogeneous data from various channels into standardized, interconnected unified sales fact records. Adaptive management strategies are loaded based on the differences in business capabilities of each channel. Simultaneously, a rule engine automatically handles cross-channel conflicts, achieving integrated management of orders, inventory, customers, and funds across all channels. The specific steps of this method include S1 to S6.

[0021] S1. Raw sales data from each sales channel is collected through an independent channel adapter configured for each channel. Sales channels include direct sales channels, distribution agent channels, online self-operated channels, bidding channels, and internal service settlement channels. The channel adapter, as a core component of the channel access gateway, collects and transforms data by loading the channel access specifications stored in the configuration center. The channel access specifications include data source type, triggering method, key data item mapping, and status mapping. Data source types include API interfaces, read-only database views, and file imports; triggering methods include timed polling, event message push, and manual upload triggering; key data item mapping maps the channel's customer code and product code to the system's unified customer identifier and unified product identifier, respectively. When a new sales channel is added, only the corresponding channel access specification needs to be added to the configuration center; the channel adapter code does not need to be modified.

[0022] During data acquisition, the channel adapter categorizes and handles anomalies: When the external system is unresponsive under timed fetching, the adapter retryes according to a preset retry strategy, which includes a maximum number of retries and a retry interval. If data cannot be acquired after reaching the maximum number of retries, the adapter generates a data acquisition anomaly alarm and writes it to the operation log. For event push methods, the adapter provides a unified message receiving endpoint. When various channel systems push data to this endpoint, the adapter verifies the message signature to prevent data tampering.

[0023] S2, the data standardization module receives raw sales data collected from various channel adapters and converts it into a unified sales fact record according to a preset mapping configuration. The unified sales fact record includes a globally unique identifier, channel code, original channel order number, unified customer identifier, unified product identifier, sales quantity, sales price, sales amount, cost price, tax rate, transaction time, settlement status, responsible sales organization, associated marketing activity or project number, source system identifier, and channel-specific attribute fields. Among these, the channel-specific attribute fields store exclusive extended data for each channel in JSON format. For example, the extended data for bidding channels includes the bid document number, bidding result, and contract number; the extended data for distribution channels includes the distributor code and rebate percentage. During the conversion process, the original order status of each channel is mapped to a unified status identifier, which includes pending, confirmed, shipped, settled, and returned.

[0024] When mapping original order statuses to unified status identifiers, the data standardization module marks any unrecognizable original status value as an abnormal status and records the original status value in a channel-specific attribute field, while simultaneously generating a data mapping anomaly notification. For cases where the same customer has conflicting attribute information across different channels, the data standardization module prioritizes attribute selection based on the data credibility level of the data source channel. The data credibility level is pre-configured in the channel access specifications.

[0025] S3. Construct a channel capability model, assigning a set of capability tags to each channel. These capability tags indicate whether the channel supports pricing, inventory management, independent settlement, and credit control. All capability tags are Boolean values, configured by the administrator based on the channel's actual business characteristics during channel registration and stored in the channel capability model library.

[0026] Channel capability tags are initially configured by the system administrator through the management interface during channel registration and then written to the channel capability model library. When a channel's business model changes, the administrator can update the capability tags. The channel strategy engine listens for change events in the capability model library, and upon detecting a tag update, reloads the corresponding channel's business strategy, enabling dynamic adjustment of channel management strategies without interrupting system operation.

[0027] S4. The channel strategy engine dynamically loads the corresponding channel business strategies based on the capability tags. The channel business strategies include inventory allocation strategies and settlement strategies. For channels whose capability tags indicate that they manage inventory, the inventory allocation strategy is enabled; for channels whose capability tags indicate that they have independent settlement, settlement is executed according to the independent rules of that channel.

[0028] S5. Utilize a rules engine to perform cross-channel collaborative processing. The rules engine is implemented using the Drools rules engine or a self-developed lightweight rules engine. Cross-channel collaborative processing includes four aspects: merging customers from different channels to generate a unified customer identifier; performing order collision detection on sales opportunities from direct sales channels and distribution channels for the same customer and determining performance attribution based on preset time windows and reporting rules; monitoring order prices in each channel and triggering an alarm when the sales price of any order is lower than the minimum selling price allowed by that channel; and accumulating the total outstanding receivables of the same customer across all channels, blocking new orders when the accumulated amount exceeds the customer's shared credit limit.

[0029] The rules engine runs multiple collaborative processing rules with preset execution priorities: the credit limit check rule has the highest priority and is triggered first when an order is created to prevent excessive orders in real time; the price monitoring rule is the next highest priority and is triggered when the order amount is confirmed; the order collision detection rule is triggered when a sales opportunity is entered; and the customer merging rule has the lowest priority and is executed asynchronously in preset time periods each day to merge incremental customer data. The triggering conditions and execution actions of each rule are stored in the rule base as rule scripts, which can be dynamically loaded and updated during system runtime without requiring a system restart.

[0030] S6. Aggregate unified sales data across all channels to generate multidimensional analysis results containing at least one of the following indicators: sales revenue, order volume, and channel contribution profit, providing data support for business decisions. The unified data storage unit uses PostgreSQL to store online data and ClickHouse to store analytical data, supporting second-level multidimensional analysis of orders across all channels.

[0031] The unified management method for cross-platform sales data provided in this embodiment converts heterogeneous sales data scattered across various channels into standardized and relatable unified sales fact records through the execution of the above steps S1 to S6. It also loads appropriate management strategies based on the differences in business capabilities of each channel and uses a rule engine to automatically handle cross-channel conflicts, thus solving the problems of fragmented data, chaotic performance attribution, and inability to manage data uniformly across sales channels.

[0032] In this embodiment, the inventory allocation strategy is implemented as follows: When any channel's capability tag indicates that it manages inventory, the channel's inventory is divided into owned inventory and virtual inventory. Owned inventory refers to physical inventory that the channel owns and can directly control, while virtual inventory refers to inventory from other channels that is visible to the channel but whose ownership does not belong to the channel. When a channel experiences a stockout and its capability tag allows the use of inventory from other channels, the virtual inventory source with the shortest distance to the stockout channel is automatically selected based on the principle of proximity, and a transfer instruction is generated to allocate the virtual inventory to that channel. The inventory's geographical location information is obtained from the warehouse information table of each channel, and the distance is calculated using straight-line distance or road network distance.

[0033] In this embodiment, the specific implementation of merging customers to generate a unified customer identifier is as follows: Customer attribute information from various channels is obtained, including the unified social credit code, mobile phone number, and company name; a fuzzy matching algorithm is used to calculate the similarity of the customer attribute information. The fuzzy matching algorithm employs either the edit distance algorithm or the cosine similarity algorithm. Customers with similarity exceeding a preset threshold are identified as the same customer and merged, and a unified customer identifier is assigned. Customers with completely identical unified social credit codes are directly merged; for customers with similar names but missing codes, the mobile phone number is used for auxiliary identification.

[0034] During the customer merging process, when customer attribute information from multiple channels is found to have partial matches but inconsistent key fields, the following priority rules apply: customers with completely matching Unified Social Credit Codes are merged first; customers with missing Unified Social Credit Codes but whose company names have a similarity exceeding a preset high threshold and whose mobile phone numbers are the same are merged second best; for customers whose company names have a similarity exceeding the threshold but other information is missing or conflicting, a manual review task is generated and written into the customer merging review queue, and the data management personnel confirm it before merging.

[0035] In this embodiment, the specific implementation of order collision detection and performance attribution based on a preset time window and reporting rules is as follows: When a sales opportunity is detected between a direct sales channel and a distribution channel for the same unified customer identifier, it is checked whether there is a valid reporting record. The reporting record is pre-entered into the system by sales personnel and includes the customer identifier, reporting time, and reporting party information. If a reporting record exists and the reporting time is within the preset time window, the performance is attributed to the reporting party; if no reporting record exists or the preset time window has expired, the order collision event is recorded in the dispute event table and marked as pending adjudication, while an adjudication notification is sent to the relevant sales manager.

[0036] The preset time window is configured according to the sales business type: for standard product sales, the time window is set to thirty calendar days after the filing; for sales opportunities of bidding projects, the time window is extended to ninety calendar days after the filing to match the longer procurement cycle of the project. The time window parameter is stored in the channel strategy configuration table and supports differentiated settings according to business type and channel combination.

[0037] In this embodiment, the specific implementation of monitoring order prices across various channels is as follows: For each order placed through the online self-operated channel, the unit price is obtained in real time upon order creation and compared with a preset channel price floor threshold. The price floor threshold can be set separately for different product categories. If the unit price is lower than the channel price floor threshold, a price anomaly alarm is generated, written to the alarm log, and an alarm message is sent to the channel management personnel.

[0038] The channel price floor threshold is imported from the product pricing system and configured differently according to product category and channel type. Each product's price floor threshold includes a base value and an allowed fluctuation percentage. The final floor threshold for online self-operated channels is the base value multiplied by the allowed fluctuation percentage. When the product pricing system updates the price floor threshold, the updated data is pushed to the channel strategy engine in real time via a message queue, ensuring that price monitoring rules always use the latest threshold data.

[0039] In this embodiment, the specific implementation of credit limit sharing is as follows: when a new order is received, the sum of the unsettled order amounts of the customer corresponding to the new order across all channels is queried; the sum of the amounts is added to the new order amount to obtain the estimated total receivable; if the estimated total receivable is greater than the customer's shared credit limit, the new order is rejected and an over-limit notification is displayed, and the relevant sales personnel are notified; otherwise, the new order is accepted and the available credit corresponding to the new order amount is deducted from the shared credit limit.

[0040] Credit limit deduction operations are executed within a database transaction, with the transaction isolation level set to serializable. This ensures the atomicity of credit limit queries, deductions, and confirmations when multiple orders from the same customer are submitted concurrently through different channels. If concurrent transactions cause a credit limit deduction conflict, the database's locking mechanism rolls back the later-submitted transaction and returns a message indicating insufficient credit limit. The client then retryes or abandons the transaction based on the returned result.

[0041] This embodiment also includes automated reconciliation and channel profit analysis steps S7 and S8. S7: Obtain settlement statement files from each channel according to a preset cycle, which can be configured to be once a month or once a quarter. The settlement statement files can be in PDF, Excel, or CSV formats. Automatically reconcile the settlement records in the settlement statement files with the locally stored unified sales fact records. The reconciliation fields include order number, amount, and date. Mark discrepancies in the reconciliation records and generate a channel reconciliation discrepancy table. S8: Calculate the channel contribution profit for each channel. The channel contribution profit equals the channel's sales revenue minus the corresponding product cost, channel fees, and allocated service costs. Channel fees include commissions, rebates, and promotional expenses generated by the channel. The allocated service costs are calculated by weighting the total service costs based on the proportion of each channel's sales revenue to the total sales revenue. The total service costs include technical development service costs, data service costs, and customer support service costs.

[0042] For discrepancies in the channel reconciliation discrepancy table, the system executes the corresponding processing procedure according to the discrepancy type: if the discrepancy type is that the channel has a record but the local record is missing, the missing local record is supplemented based on the channel settlement statement; if the discrepancy type is that the local record has a record but the channel has no record, the record is marked as pending verification and a verification request is initiated to the channel; if the discrepancy type is that the amounts are inconsistent, the lower of the amounts from both parties is taken as the provisional settlement amount, and the difference is carried over to the next reconciliation period. All discrepancy processing operations are logged, including the operator, operation time, and processing result.

[0043] This embodiment also provides a unified management system for cross-platform sales data, including a processor, a memory, a communication module, a channel access gateway, a data standardization module, a channel capability model library, a channel strategy engine, and a unified data storage unit. The memory stores computer programs. The channel access gateway contains multiple channel adapters corresponding to sales channels, used to collect raw sales data from each channel. The data standardization module converts raw sales data into unified sales fact records according to a preset mapping configuration. The channel capability model library stores capability tags for each channel. The channel strategy engine dynamically loads corresponding channel business strategies based on capability tags and uses a rule engine to execute cross-channel collaborative processing. The communication module interacts with external channel systems, including direct sales CRM systems, distribution ERP systems, e-commerce open platforms, and bidding project management systems. When the processor executes the computer program stored in the memory, it controls the channel access gateway, data standardization module, channel capability model library, channel strategy engine, and unified data storage unit to implement the aforementioned unified management method for cross-platform sales data.

[0044] The channel access gateway sends the collected raw sales data to the data standardization module via a message queue. This message queue is implemented using a Kafka cluster to ensure high throughput and no data loss. The data standardization module writes the transformed, unified sales fact records into a unified data storage unit. Simultaneously, it publishes events requiring real-time processing to the message queue for the channel strategy engine to subscribe to and perform cross-channel collaborative processing. The channel strategy engine updates the corresponding records in the unified data storage unit with the processing results via callbacks.

[0045] The system's workflow is as follows: First, channel adapters for each channel collect raw sales data from external systems such as direct sales CRM, distribution ERP, and e-commerce platforms via scheduled retrieval or event-driven push, according to the channel access specifications in the configuration center. The communication module is responsible for data transmission with external channel systems. After receiving the raw sales data, the data standardization module converts heterogeneous order data from each channel into unified sales fact records based on preset mapping configurations. Simultaneously, it maps the raw order status of each channel to a unified status of pending, confirmed, shipped, settled, or returned. Extended data such as bid document numbers and contract numbers for bidding channels, and distributor codes and rebate ratios for distribution channels, are stored in channel-specific attribute fields in JSON format. Unidentifiable raw status values ​​are marked as abnormal and an exception notification is generated. Conflicts in multi-source customer attributes are handled according to data reliability levels. The channel capability model library pre-stores capability tags for each channel. After reading the tags, the channel strategy engine loads inventory allocation strategies for channels managing inventory, distinguishing between owned inventory and virtual inventory, and automatically generating transfer instructions based on geographical proximity when stockouts occur; it also loads exclusive settlement rules for channels with independent settlements. The rule engine continuously runs cross-channel collaborative processing tasks according to preset priorities: credit limit check rules are executed in real-time with the highest priority when orders are created, ensuring data consistency in concurrent scenarios through serializable transaction isolation levels; price monitoring rules compare the sales unit price with the minimum threshold in real-time when the order amount is confirmed, triggering alarms and writing to the alarm log when the price falls below the threshold; order collision detection rules determine performance attribution based on reporting records and time windows when sales opportunities are entered, writing to the dispute event table and notifying the sales manager when automatic determination is not possible; customer merging rules are executed asynchronously in batch processing during preset daily time periods, merging cross-channel customers through fuzzy matching algorithms and handling attribute conflicts according to priority rules. After unified sales fact records across all channels are summarized into a unified data storage unit, multi-dimensional business analysis results are generated. According to a preset cycle, the system automatically retrieves settlement statement files from each channel, compares them with local records to generate a reconciliation discrepancy table, and processes the discrepancies according to their types. Simultaneously, it allocates service costs based on sales revenue ratios and calculates the channel contribution profit for each channel. Through this process, unified collection, standardization, collaborative management, and analysis of sales data across all channels are achieved, resolving the issues of data fragmentation and collaboration conflicts between channels.

[0046] In the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0047] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make modifications, alterations, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A unified management method for cross-platform sales data, characterized in that, include: S1. Collect raw sales data for each sales channel by configuring an independent channel adapter for each channel; S2. According to the preset mapping configuration, the original sales data is converted into a unified sales fact record. The unified sales fact record includes channel code, unified customer identifier, unified product identifier, sales amount and channel-specific attribute fields. The channel-specific attribute fields store channel extended data not included in the general fields in JSON format. S3. Construct a channel capability model and assign a set of capability tags to each channel. The capability tags indicate whether the channel supports pricing, inventory management, independent settlement, and credit control. S4. Based on the capability tags, dynamically load the corresponding channel business strategies, including inventory allocation strategies and settlement strategies; S5. Utilize the rule engine to perform cross-channel collaborative processing, wherein the cross-channel collaborative processing includes: merging customers from different channels to generate the unified customer identifier; Perform order collision detection on sales opportunities for the same customer in direct sales channels and distribution channels and determine the performance attribution according to preset time windows and reporting rules; monitor the order price of each channel and trigger an alarm when the sales price of any order is lower than the minimum selling price allowed by the channel; and accumulate the total amount of unsettled receivables of the same customer in all channels and block new orders when the accumulated amount exceeds the customer's shared credit limit. S6. Summarize the unified sales fact records across all channels and generate a multidimensional analysis result that includes at least one of the following indicators: sales revenue, order volume, and channel contribution profit for each channel.

2. The unified management method for cross-platform sales data according to claim 1, characterized in that, The inventory allocation strategy includes: When any channel’s capability tag indicates that it manages inventory, the channel’s inventory is divided into owned inventory and virtual inventory. The owned inventory is physical inventory that the channel owns the rights to and can directly control. The virtual inventory is other channel’s salable inventory that is visible to the channel but whose ownership does not belong to the channel. When the channel experiences a stock shortage and the capability tag allows the use of inventory from other channels, the system automatically selects the virtual inventory source that is closest to the stock-out channel based on the principle of proximity to the inventory in geographical location, and generates an allocation instruction to transfer the virtual inventory to the channel.

3. The unified management method for cross-platform sales data according to claim 1, characterized in that, The channel adapter in step S1 collects and transforms data by loading the channel access specifications stored in the configuration center. The channel access specifications include data source type, triggering method, key data item mapping and status mapping.

4. The unified management method for cross-platform sales data according to claim 1, characterized in that, In step S2, which converts the original sales data into the unified sales fact record, the original order status of each channel is mapped to a unified status identifier, which includes pending processing, confirmed, shipped, settled, and returned.

5. The unified management method for cross-platform sales data according to claim 1, characterized in that, Step S5, which involves merging customers from different channels to generate the unified customer identifier, includes: Obtain customer attribute information from various channels, including unified social credit code, mobile phone number, and company name; The similarity of the customer attribute information is calculated using a fuzzy matching algorithm. Customers with similarity exceeding a preset threshold are merged and assigned a unified customer identifier.

6. The unified management method for cross-platform sales data according to claim 1, characterized in that, Step S5, which involves detecting order collisions and determining performance attribution based on the preset time window and the reporting rules, includes: When it is detected that the direct sales channel and the distribution channel generate the sales opportunity for the same unified customer ID, check whether there is a valid reporting record; If the aforementioned reporting record exists and the reporting time is within the preset time window, the performance will be attributed to the reporting party. If the reported record does not exist or the preset time window has expired, the collision event record will be written into the dispute event table and marked as pending adjudication.

7. The unified management method for cross-platform sales data according to claim 1, characterized in that, The monitoring of order prices across various channels mentioned in step S5 includes: For each order placed through the online self-operated channel, the sales price is obtained in real time and compared with the preset channel price floor threshold. If the selling price is lower than the channel price threshold, a price anomaly alarm is generated and written to the alarm log.

8. The unified management method for cross-platform sales data according to claim 1, characterized in that, Step S5 involves accumulating the total outstanding receivables of the same customer across all channels, and blocking new orders when the accumulated amount exceeds the customer's shared credit limit. Upon receiving a new order, query the sum of the outstanding orders across all channels for the customer corresponding to the new order; The sum of the aforementioned amounts plus the amount of the new order yields the estimated total receivable. If the estimated total receivables exceeds the customer's shared credit limit, the new order is rejected and an over-limit notification is displayed; otherwise, the new order is accepted and the available credit limit is deducted.

9. The unified management method for cross-platform sales data according to claim 1, characterized in that, Also includes: S7. Obtain settlement statement files from various channels according to a preset cycle, automatically match the settlement records in the settlement statement files with the unified sales fact records stored locally, mark the discrepancies for records that do not match, and generate a channel reconciliation discrepancy table. S8. Calculate the channel contribution profit for each channel. The channel contribution profit is equal to the sales revenue of the channel minus the corresponding product cost, channel fee and allocated service cost. The allocated service cost is calculated by allocating the total service cost based on the proportion of each channel's sales to the total sales.

10. A unified management system for cross-platform sales data, used to implement the unified management method for cross-platform sales data as described in any one of claims 1 to 9, characterized in that, This includes a processor, memory, communication module, channel access gateway, data standardization module, channel capability model library, channel strategy engine, and unified data storage unit; The memory is used to store computer programs; The channel access gateway includes multiple channel adapters corresponding to the sales channels, used to collect the original sales data of each channel; The data standardization module is used to convert the original sales data into the unified sales fact record according to the preset mapping configuration. The channel capability model library stores the capability tags for each channel; The channel strategy engine is used to dynamically load the corresponding channel business strategy based on the capability tag, and to execute the cross-channel collaborative processing using the rule engine; The communication module is used for data interaction with external channel systems; When the processor executes the computer program stored in the memory, it controls the channel access gateway, the data standardization module, the channel capability model library, the channel strategy engine, and the unified data storage unit to realize the unified management method of cross-platform sales data.

Images