AI Product Proposal System for Sales Conversion
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Solution Overview
Problem
Current sales promotion methods for products and services often fail to effectively engage users, as they rely on predictions based on purchase history and preferences, leading to missed sales opportunities due to inadequate representation or tryout experiences.
Innovation Solution
A product/service proposal system that utilizes user action history and parameter settings to determine suitable product or service proposals, using various communication means such as displays, to enhance user engagement and sales promotion, incorporating AI for personalized recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sales promotion is performed based on user preferences and purchase history, then product recommendations can be generated, but the prediction may be wrong and sales opportunities may be missed
Solution Approach 1:
The system performs preliminary actions by providing multiple types of product information (images, videos, specifications, user reviews) before the purchase decision, allowing users to thoroughly evaluate products in advance. This reduces prediction errors and missed sales opportunities by ensuring users have comprehensive information beforehand.
Solution Approach 2:
The system introduces an intermediary AI assistant that mediates between user preferences and product recommendations. The AI assistant analyzes user behavior patterns and provides personalized recommendations, improving both prediction accuracy and sales effectiveness by acting as an intelligent intermediary.
2Productivity
If users are provided with comprehensive product information and tryout experiences, then purchase conversion improves, but system complexity increases
Solution Approach 1:
The system implements multi-functionality by integrating multiple features into a unified platform: product information display, AI-powered recommendations, virtual tryout capabilities, and purchase processing. This universal system handles diverse user needs through a single interface, improving conversion without proportionally increasing complexity.
Solution Approach 2:
The system enables self-service through AI assistants that automatically analyze user preferences, generate personalized recommendations, and provide product information without requiring manual intervention. This automation maintains high conversion rates while managing system complexity through intelligent self-service mechanisms.
3Adaptability or versatility
If AI is used for personalized recommendations, then user engagement improves, but data processing requirements increase
Solution Approach 1:
The system extracts only the essential and most relevant user data for personalization, such as purchase history, browsing behavior, and explicit preferences, rather than processing all available data. This selective extraction maintains high personalization capability while reducing overall data processing requirements.
Solution Approach 2:
The AI system applies local quality by providing different levels of personalization for different user segments and contexts. Rather than uniformly processing all user data with the same depth, the system adapts the level of analysis to local needs, improving personalization efficiency while managing data processing loads.
Data Source
AI summary
Provided is a product/service proposal system and computer program product for making, to a user who considers purchase of a product and/or service, a proposal leading the user to purchase a product and/or service using a display serving as communication means between the user and a supplier that supplies a product and/or service. The product/service proposal system includes a user action history acquisition unit configured to acquire a user action history, a parameter setting unit configured to set parameters indicating preferences of at least one of the user and the supplier in a process in which the user considers the purchase of the product and/or service, and a display proposal unit configured to determine a product and/or service to be proposed to the user on the basis of at least one of the user action history and the parameters and to make a proposal leading the user to purchase the determined product and/or service to the user using the display.