Dynamic Customer Segmentation for Real-Time Search Personalization

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Solution Overview

Problem

Existing web search systems fail to provide personalized search results based on user interests or needs, leading to inefficient user experiences and lower conversion rates.

Innovation Solution

A system that tracks customer behavior and preferences in real-time, dynamically updates customer segments, and personalizes search results using machine learning algorithms to enhance relevance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the same search terms are used for multiple users, then the search results are consistent and easy to generate, but the search results are not personalized based on user interests or needs

Engineering Contradiction:

Improvepersonalization capabilityVSAvoidsearch system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments users into different customer segments based on their behavior, preferences, and characteristics. This segmentation enables personalized search results for each segment while maintaining system manageability by grouping users with similar profiles together, thus resolving the contradiction between personalization capability and system complexity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent changes the parameters used in search result generation by incorporating user-specific parameters (customer segments, behavior patterns, preferences) alongside traditional search parameters. This allows the system to provide personalized results without fundamentally changing the search infrastructure, balancing personalization with system complexity.

Inventive Principle:

Principle #35Parameter changes

2Ease of operation

If detailed search criteria are required for personalization, then search results can be tailored to user needs, but users must provide more detailed search criteria and sort through generic results

Engineering Contradiction:

Improvesearch efficiencyVSAvoidtime for detailed criteria input

Core Design Contradiction:

Ease of operationVSLoss of time

Solution Approach 1:

The patent performs preliminary actions by pre-segmenting users into customer segments based on their historical behavior and preferences before the search occurs. This pre-segmentation allows the system to automatically apply personalized filtering and ranking to search results without requiring users to input detailed criteria or manually sort through generic results, thus improving search efficiency while minimizing time investment from users.

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If static customer segments are used, then the system is simpler to implement, but the search results cannot adapt to real-time changes in user behavior and preferences

Engineering Contradiction:

Improvereal-time adaptabilityVSAvoidreal-time evaluation automation

Core Design Contradiction:

Adaptability or versatilityVSExtent of automation

Solution Approach 1:

The patent implements dynamic customer segments that automatically update in real-time based on user behavior and preferences. This dynamic segmentation allows the system to adapt search results to current user needs without manual intervention, achieving real-time adaptability through automated evaluation of user characteristics and actions.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent incorporates feedback mechanisms that continuously monitor user behavior, preferences, and interactions with search results. This feedback loop enables the system to automatically update customer segments and adjust search results in real-time, resolving the contradiction between real-time adaptability and the extent of automation required.

Inventive Principle:

Principle #23Feedback

4Productivity

If personalized search results are provided, then user engagement and conversion rates improve, but the system requires large-scale tracking of consumer behavior and preferences

Engineering Contradiction:

Improveconversion rateVSAvoidtracking system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent implements a universal tracking framework that collects user behavior and preference data for the dual purpose of both personalization and analytics. This multi-functional tracking system enables the business to achieve personalized search results (improving conversion rates) while also gaining valuable insights into consumer patterns, thereby justifying the tracking infrastructure through multiple benefits.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12499459B2System and method for real-time customer segment-based personalization including dynamic segment switching

Publication Date: 2025.12.16 BLOOMREACH

AI summary

Methods and apparatuses for customer engagement include: receiving a first product search query from a visitor identified in a visitor session, wherein the first product search query includes at least a visitor identifier associated with customer segments; returning first product search results based on the first product search query; updating, after the first product search query, the customer segments associated with the visitor identifier based on real time evaluation of visitor characteristics and/or actions; receiving a second product search query that is the same as the first product search query from the visitor, wherein the second product search query includes at least the visitor identifier associated with the updated customer segments; and returning second product search results based on the second product search query that is different from the first product search results.