Adaptive User Interface Personalization by Purchase Intent Classification

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing systems struggle to differentiate between serious and non-serious customers in electronic retail environments, leading to inefficient content delivery and user experience, as they lack effective methods to discern customer types and tailor interactions accordingly.

Innovation Solution

A computer-implemented method using machine learning algorithms to analyze customer and user interactions, generating a prediction model that classifies users based on their interest and commitment to purchase, thereby providing an updated user interface tailored to their type.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If a unified user interface is provided to all customers, then the system complexity is reduced, but the ability to tailor content to customer types deteriorates

Engineering Contradiction:

Improvetailoring content to customer typesVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments customers into different types (serious vs. non-serious) based on their interaction patterns and purchase intent. The system then provides differentiated user interface content and functionality based on these segments, allowing tailored content delivery while maintaining a unified underlying system architecture.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The user interface is made dynamic by automatically adjusting content, layout, and functionality based on real-time analysis of customer interactions. The system evolves its response strategy based on observed behavior patterns, transitioning from static unified interfaces to adaptive personalized interfaces without manual reconfiguration.

Inventive Principle:

Principle #15Dynamics

2Measurement precision

If detailed customer analysis is performed, then the accuracy of customer classification improves, but the processing time and computational resources increase

Engineering Contradiction:

Improvecustomer classification accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs preliminary analysis of customer interaction data to establish baseline profiles and classification models before actual purchase decisions are made. Historical data is pre-processed to train classification algorithms, enabling rapid real-time decisions without reanalyzing all historical data from scratch.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors customer interactions and uses this feedback to refine classification accuracy over time. Performance metrics are tracked and used to adjust classification models, improving precision while optimizing processing efficiency through iterative improvement rather than relying solely on initial comprehensive analysis.

Inventive Principle:

Principle #23Feedback

3Ease of operation

If the user interface is simplified for non-serious customers, then engagement is improved, but the functionality needed by serious customers deteriorates

Engineering Contradiction:

Improveuser experienceVSAvoidfunctionality for serious customers

Core Design Contradiction:

Ease of operationVSAdaptability or versatility

Solution Approach 1:

Different portions of the user interface are optimized for different customer segments. The overall interface maintains simplicity and ease of use for non-serious customers, while specific sections, features, and information are enhanced and made more prominent for serious customers based on their identified needs and interaction patterns.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The interface dynamically adapts its complexity and functionality based on real-time customer behavior analysis. Serious customers who exhibit specific interaction patterns receive enhanced functionality and detailed information, while non-serious customers see a simplified interface, all within the same unified system without manual configuration.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12393980B2Methods and systems for updating a user interface based on level of user interest

Publication Date: 2025.08.19 CAPITAL ONE SERVICES LLC

AI summary

A computer-implemented method for providing a personalized interface to a user based on whether the user is serious about making a purchase may include: obtaining customer identification data and customer input data a customer, wherein the customer input data comprises a request from the customer; determining a request status of the customer based on the customer identification data and the customer input data; obtaining customer interface activity data of the customer based on the request status; obtaining customer purchasing data of the customer based on the request status; generating a prediction model based on the customer interface activity data and the customer purchasing data; training the generated prediction model by classifying the customer based on the customer interface activity data and the customer purchasing data; obtaining user identification data and user interface activity data of a user via a user device, the user interface activity data indicating interactive activities between the user and a user interface displayed on the user device; determining a rating of the user to purchase a product based on the user identification data, the user interface activity data, and the prediction model; and providing, to the user, an updated user interface on the user device based on the determined rating.