Dynamic Pricing Engine for E-Commerce Personalization

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Solution Overview

Problem

E-commerce platforms struggle to dynamically adjust product prices based on a customer's browsing history, failing to provide personalized pricing strategies that leverage previous product offerings effectively.

Innovation Solution

A computer-implemented method and system that detects a customer's request for a current web page displaying a product, retrieves their browsing history to find a previous price, and dynamically adjusts the current price based on that history, presenting the adjusted price on the current web page.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If e-commerce platforms use standardized pricing for all customers, then operational simplicity is maintained, but personalized pricing opportunities are lost

Engineering Contradiction:

Improvepersonalized pricing capabilityVSAvoidpricing system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by storing browsing history and previous pricing information in advance. When a customer requests a product page, the system has already prepared the browsing data, allowing for rapid personalized pricing adjustment without complex real-time analysis

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback by continuously monitoring customer browsing behavior and using this information to dynamically adjust pricing. The pricing strategy adapts based on feedback from browsing history, creating a closed-loop system that balances personalization with operational simplicity

Inventive Principle:

Principle #23Feedback

2Ease of operation

If e-commerce platforms access browsing history to enable personalized pricing, then customer engagement is improved, but data privacy concerns increase

Engineering Contradiction:

Improvecustomer engagementVSAvoiddata privacy risk

Core Design Contradiction:

Ease of operationVSObject-affected harmful factors

Solution Approach 1:

The system uses an intermediary approach by implementing authorization indicia that mediate between data access needs and privacy protection. The authorization mechanism acts as a controlled interface, allowing browsing history access only when explicitly permitted by the customer, thus enabling personalized pricing while maintaining privacy trust

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If e-commerce platforms dynamically adjust prices based on browsing history, then sales opportunities are increased, but price discrimination risks arise

Engineering Contradiction:

Improvesales conversion rateVSAvoidpricing fairness

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system applies local quality by implementing differentiated pricing strategies tailored to individual customer browsing patterns rather than uniform pricing. Each customer receives pricing adjustments localized to their specific browsing history and preferences, enabling higher sales conversion while maintaining perceived fairness through personalized relevance

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS8473340B2Product marketing utilizing browsing history

Publication Date: 2013.06.25 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer implemented method markets a particular product in an e-commerce system. A web page server receives a request for a current web page that displays a particular product. The request is accompanied by an authorization indicium to retrieve a content of a previous web page that offered the particular product at a previous price. A current price for the particular product is dynamically adjusted based on the previous price offered on the previous web page, and is then presented on the current web page.