CN-121998711-A - Marketing information management method and system based on multi-channel collaborative pushing

CN121998711ACN 121998711 ACN121998711 ACN 121998711ACN-121998711-A

Abstract

The embodiment of the invention discloses a marketing information management method and system based on multi-channel collaborative pushing, and relates to the technical field of digital marketing. The method comprises the steps of collecting and integrating user data from a plurality of channels to construct a unified user portrait, generating personalized marketing information content based on the user portrait, selecting and cooperatively forming a pushing channel combination from a plurality of alternative channels according to the characteristics of the user portrait and each channel, executing content pushing through the pushing channel combination, applying pushing limitation, monitoring key indexes of pushing effects in real time, and optimizing at least one of the user portrait, content strategy, channel strategy and pushing strategy based on the effect data. The implementation mode realizes unified and intelligent management and cooperation of multiple marketing channels, and remarkably improves the accurate touch rate and the overall conversion efficiency of marketing information.

Inventors

CHEN FEI
CHENG JIANJUN
SHEN DAWEI
HAN YANAN

Assignees

北京阿尔法风控科技有限公司

Dates

Publication Date: 20260508
Application Date: 20260120

Claims (10)

1. A marketing information management method based on multi-channel collaborative pushing is characterized by comprising the following steps: Collecting and integrating user data from a plurality of channels to construct a unified user representation, the plurality of channels including public domain channels and/or private domain channels; Based on the user portrait, generating personalized marketing information content matched with the user characteristics; Selecting and cooperatively forming a pushing channel combination from a plurality of alternative pushing channels according to the user portrait and channel characteristics of the alternative pushing channels; Pushing the personalized marketing information content to a target user through the pushing channel combination, and applying a pushing limit rule in the pushing process; the method comprises the steps of monitoring effect data pushed through different channels in real time, and judging the whole pushing effect and the sub-channel pushing effect based on preset key performance indexes; And optimizing at least one of the user portraits, the generation strategy of the personalized marketing information content, the formation strategy of the push channel combination and the push limit rule based on the effect data.
2. The method of claim 1, wherein the collecting and integrating user data from multiple channels to construct a unified user representation comprises: Collecting basic behavior data of a user from at least one public domain channel and/or collecting deep interaction and transaction data of the user from at least one private domain channel; cleaning and standardizing data from different channels; And integrating the processed data into the unified user portrait comprising user attributes, behavior preferences and consumption capability multidimensional labels through a correlation analysis and fusion algorithm.
3. The method of claim 1, wherein generating personalized marketing message content that matches user features based on the user representation comprises: analyzing the user portrait, and extracting interest preference and demand characteristics of the user; Matching or dynamically generating content materials from a content material library according to the interest preference and the demand characteristics; and performing personalized rendering on the content materials to adapt to different users or user groups so as to form the personalized marketing information content.
4. The method of claim 1, wherein selecting and collaborating to form a push channel combination from a plurality of alternative push channels based on the user representation and channel characteristics of the plurality of alternative push channels, comprises: maintaining a channel feature library containing attribute and real-time state information of each channel; And taking the user portraits and marketing campaign targets as inputs, carrying out collaborative optimization calculation based on a preset multichannel decision model, and outputting push channels distributed for each target user or user group and collaborative execution strategies thereof to form the push channel combination.
5. The method of claim 1, wherein pushing the personalized marketing message content to a target user via the push channel portfolio and applying push restriction rules during the pushing process comprises: Scheduling interfaces of the corresponding channels to execute content distribution tasks according to the channels and the strategies determined by the push channel combination; Based on a global push frequency policy and the interaction history of individual users, the push frequency and push opportunity control for the target user are dynamically adjusted and executed.
6. The method of claim 1, wherein the real-time monitoring of the effect data pushed through different channels and determining the overall and sub-channel pushing effects based on the preset key performance indicators comprises: Collecting interaction data of each contact of a user in a push link and associating the interaction data with a corresponding push channel; calculating key performance indexes including exposure, click rate, conversion rate and input-output ratio of the whole channel and the sub channel; and comparing the effect differences of different push channel combinations and content strategy versions through an A/B test.
7. The method of claim 1, wherein optimizing at least one of the user representation, the generation policy of personalized marketing information content, the formation policy of the push channel combination, and the push restriction rule based on the effect data comprises: updating a feature extraction model or a label calculation model for constructing the user portrait by using the effect data as feedback; Analyzing the content characteristics and channel combination characteristics with high conversion rate, and optimizing a content generation strategy and a multi-channel collaborative selection strategy; And dynamically adjusting the push frequency model and the content individuation degree according to the feedback behavior of the user on push.
8. A marketing information management system based on multi-channel collaborative pushing is characterized by comprising: A multi-channel data integration module configured to collect and integrate user data from a plurality of channels including public and/or private channels to construct a unified user representation; a personalized content generation module configured to generate personalized marketing information content matching user features based on the user representation; A multi-channel collaborative decision-making module configured to select and collaborate to form a push channel combination from a plurality of alternative push channels according to channel characteristics of the user representation and the plurality of alternative push channels; The intelligent pushing execution module is configured to push the personalized marketing information content to the target user through the pushing channel combination and apply pushing restriction rules in the pushing process; the full-channel effect monitoring module is configured to monitor effect data pushed through different channels in real time and judge the whole and sub-channel pushing effects based on preset key performance indexes; And a policy iteration optimization module configured to optimize at least one of the user portraits, the generation policies of the personalized marketing information content, the formation policies of the push channel combinations, and the push limit rules based on the effect data.
9. An electronic device, comprising: One or more processors; A storage device having one or more programs stored thereon; The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-7.
10. A computer readable storage medium, characterized in that a computer program is stored thereon, wherein the program, when executed by a processor, implements the method according to any of claims 1 to 7.

Description

Marketing information management method and system based on multi-channel collaborative pushing Technical Field The invention relates to the field of information technology and digital marketing, in particular to a method and a system for integrating and managing a plurality of marketing channels and realizing accurate and automatic collaborative information pushing. Background In the digital marketing era, the contact points of enterprises and consumers are highly dispersed in various public domain and private domain channels such as social media, search engines, emails, mobile applications, instant messaging tools, short video platforms and the like. The current situation of coexistence of multiple channels brings serious challenges to marketing management while expanding market coverage, wherein user data of all channels are mutually isolated to form a data chimney, unified and comprehensive cognition of enterprises to clients is hindered, marketing activities are often independently planned and executed by different teams in all channels, information inconsistency, resource internal consumption and even conflict information are repeatedly sent to the same user, brand experience is damaged, cross-channel coordination, content adaptation and effect analysis workload is huge, response is slow, and large-scale accurate marketing is difficult to realize. Prior art solutions have focused on automation of a single channel (e.g., mail marketing automation tools) or simple, synchronized distribution of multi-channel content. The schemes lack the capability of deep integration and analysis of multi-channel data, cannot make decisions based on unified user insight, depend on fixed rules or manual experience on channel selection, cannot dynamically optimize channel combination and pushing strategies according to real-time feedback, and do not establish a systematic cross-channel collaborative management and effect evaluation system. Therefore, the marketing efficiency and the return on investment are difficult to be effectively improved. In view of this, the prior art lacks a marketing information management scheme capable of intelligently solving an optimal cross-channel push strategy based on a unified, dynamically updated user representation under global budget and user experience constraints, and forming closed-loop optimization based on real-time feedback data. Disclosure of Invention The invention aims to overcome the defects of the prior art and provides a marketing information management method, a marketing information management system, electronic equipment and a computer readable medium based on multi-channel collaborative pushing. The scheme aims to construct a user panoramic portrait by integrating multichannel data uniformly, intelligently carry out multichannel collaborative decision-making, personalized content generation, automatic pushing execution and full-link effect optimization based on the user panoramic portrait, and particularly realize efficient, accurate and integrated management of marketing information by constructing and solving a cross-channel collaborative optimized decision model and establishing a data-driven full-link strategy iteration mechanism. In a first aspect, an embodiment of the present invention provides a marketing information management method based on multi-channel collaborative push, including: Collecting and integrating user data from a plurality of channels to construct a unified user representation, the plurality of channels including public domain channels and/or private domain channels; Based on the user portrait, generating personalized marketing information content matched with the user characteristics; Selecting and cooperatively forming a pushing channel combination from a plurality of alternative pushing channels according to the user portrait and channel characteristics of the alternative pushing channels; pushing the personalized marketing information content to a target user through the pushing channel combination, and applying a pushing limit rule in the pushing process, wherein the pushing limit rule comprises control over pushing frequency, user fatigue, pushing period or content type; the method comprises the steps of monitoring effect data pushed through different channels in real time, and judging the whole pushing effect and the sub-channel pushing effect based on preset key performance indexes; And optimizing at least one of the user portraits, the generation strategy of the personalized marketing information content, the formation strategy of the push channel combination and the push limit rule based on the effect data. In a second aspect, an embodiment of the present invention provides a marketing information management system based on multi-channel collaborative push, including: A multi-channel data integration module configured to collect and integrate user data from a plurality of channels including public and/or private channels to construct