Mood-Based E-Commerce Navigation and Marketing System
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Solution Overview
Problem
Online shopping experiences are cumbersome due to the difficulty in navigating and locating desirable items among numerous options, leading to a need for improved user experience in electronic commerce.
Innovation Solution
Systems and methods that monitor user navigation, selection, and purchase events to determine a user's mood, allowing for personalized marketing and enhanced user experience by adjusting marketing messages and navigation models in real-time based on identified mood and behavior patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users navigate through various merchant webpages to locate desirable items, then they can find products they want to purchase, but the process becomes cumbersome and time-consuming due to the large number of items to navigate through
Solution Approach 1:
The system performs preliminary actions by monitoring user navigation events, selection events, and purchase events to determine user mood and purchase patterns before the user explicitly searches for items. This allows the system to pre-identify desirable items and present them proactively, saving the user time and effort in navigation.
Solution Approach 2:
The system continuously monitors user navigation behavior, selection events, and purchase events as feedback to dynamically determine user mood and adjust marketing messages and item recommendations in real-time. This feedback loop enables the system to adapt to changing user preferences and reduce search time.
2Productivity
If merchants offer means to narrow search terms, then users can locate items more efficiently, but the procedure becomes complex and time-consuming because users may not understand how to use the narrowing features
Solution Approach 1:
The system performs the complex task of analyzing navigation patterns and determining user mood automatically without requiring user intervention. The system serves itself by monitoring its own data (navigation events, selection events, purchase events) to generate personalized recommendations, eliminating the need for users to understand complex search procedures.
Solution Approach 2:
The system changes the parameters of item recommendation by transitioning from static, predefined categories to dynamic, mood-based parameters. By monitoring user behavior and determining mood states, the system adjusts which items are presented to users based on real-time behavioral parameters rather than requiring users to navigate complex categorical structures.
3Adaptability or versatility
If the system monitors and analyzes user navigation behavior in real-time to determine mood, then personalized marketing can be provided, but this requires processing and storing large amounts of user data
Solution Approach 1:
The system extracts only the essential information needed for mood determination from the large volume of user data. Instead of processing all navigation events in detail, the system extracts key patterns from navigation events, selection events, and purchase events to determine user mood, reducing the effective data volume while maintaining personalization capability.
Data Source
AI summary
A system and method for facilitating electronic commerce over a network, according to one or more embodiments, includes communicating with a user via a user device and a business entity via a business entity device over the network, monitoring user navigation events over the network, determining a mood of the user based on user navigation behavior, marketing to the user based on the mood of the user, and storing user information related to the user navigation events and the mood of the user.