A marketing-scene-oriented order data generation method, system and storage medium

By using a dual-timeline model and incremental snapshot recording, the problem of static storage of marketing tags is solved, enabling efficient and accurate processing of order data and supporting precise analysis of marketing activities.

CN122243611APending Publication Date: 2026-06-19SHENZHEN YIYUAN NETWORK PLATFORM CO LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN YIYUAN NETWORK PLATFORM CO LTD
Filing Date
2026-03-20
Publication Date
2026-06-19

AI Technical Summary

Technical Problem

In existing technologies, marketing tags are fixed as static fields, which cannot adapt to complex business changes and lack a time-based linkage mechanism. This results in insufficient concurrency control in high-concurrency scenarios, leading to data consistency and accuracy issues.

Method used

By employing a dual-timeline model and incremental snapshot recording, combined with concurrent consistency verification and soft deletion isolation mechanisms, and by constructing event timelines and rule timelines, marketing attribute tags are calculated to achieve efficient processing and accuracy of order data.

Benefits of technology

It achieves consistency and accuracy in order data generation, improves the accuracy of marketing analysis and the scientific nature of decision-making, and reduces storage space redundancy and processing time.

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Abstract

This invention discloses a method, system, and storage medium for generating order data in marketing scenarios, belonging to the field of electronic digital data processing. The method includes the following steps: receiving order operation requests initiated by clients, parsing the requests to obtain operation types and business parameters, validating the business parameters, and distributing the order operation requests to corresponding processing flows based on the operation type to obtain corresponding order data; constructing a dual-timeline model, which includes an event timeline extracted based on incremental snapshot records and creation records, and a rule timeline determined based on marketing activity configuration version change logs; querying the activity configuration version corresponding to the event points in the event timeline on the rule timeline; calculating marketing attribute tags based on the activity configuration versions; merging the calculated tags to generate order data containing the entire lifecycle of marketing attributes, thus improving the effectiveness of order data generation.
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