Customized platform for each individual role in distribution

By collecting and analyzing user data in the IT distribution platform, generating personalized interfaces and dynamically updating content, the problem of poor user experience was solved, achieving an efficient and personalized user interface and content recommendation, thereby improving user satisfaction and platform efficiency.

CN122155804APending Publication Date: 2026-06-05INGRAM MICRO INC
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
INGRAM MICRO INC
Filing Date
2025-12-04
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Conventional IT distribution platforms lack the ability to dynamically adjust to changes in user behavior and preferences, resulting in poor user experience, inefficiency, and an inability to provide personalized recommendations and content, impacting user efficiency and productivity across different roles.

Method used

User data is collected through the registration module, user roles are analyzed using a role recognition engine, user behavior is monitored by an interaction tracker, preferences are aggregated by a preference aggregator, personalized user interfaces are generated, and dynamic content updates and personalized recommendations are performed using advanced analytics and machine learning modules to continuously learn user needs.

Benefits of technology

It enables dynamic adjustments to the personalized interface and content based on user roles and preferences, improving user experience and efficiency, ensuring the timeliness and relevance of information, and enhancing user satisfaction and platform adaptability.

✦ Generated by Eureka AI based on patent content.

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Abstract

The system and method provide a customized platform for each individual role in distribution. A server coupled with a processor is configured to execute instructions to perform: collecting initial user data through a registration process using a registration module, analyzing the collected data to identify a role of a user using a role identification engine, monitoring user interactions using an interaction tracker, and aggregating user preferences using a preference aggregator. The system can generate a personalized user interface through a single pane of glass user interface (SPoG UI), dynamically update content using a dynamic content generator, continuously improve personalization via AI techniques using an AI learner, provide personalized recommendations through a recommendation system, monitor effectiveness of processes using a performance monitor, and collect and integrate user feedback using a feedback integrator. The system also incorporates a data ingestion, cleansing, and transformation module to enhance analytics and storage optimization.
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