Decision Engine Interfacing with Marketing Engine for Product Ranking
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Solution Overview
Problem
Current internet search engines primarily rely on keyword-based search queries to provide information, leaving users to independently compare products and make decisions, without assisting in the evaluation or comparison process.
Innovation Solution
A computer-implemented method and system that integrates a decision engine with a marketing engine to process user inputs, share decision-related data, and provide vendor-related data, facilitating the comparison of products by ranking options based on user-defined factors and importance levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If search engines provide only keyword-based search results, then the system remains simple and fast, but users cannot compare products or make informed decisions
Solution Approach 1:
The system is divided into separate functional modules: a search engine component for keyword-based retrieval, a decision engine component for processing user preferences and comparing products, and a marketing engine component for personalized advertising. This segmentation allows each component to specialize in its function while reducing overall system complexity through modular design.
Solution Approach 2:
The decision engine acts as an intermediary between the search engine and the user. It receives search results, processes them through user-defined criteria and importance levels, and presents comparative analysis to help users make informed decisions without requiring the search engine itself to become more complex.
2Measurement precision
If the system integrates decision-making and marketing functions, then advertising relevance improves, but system complexity increases
Solution Approach 1:
The marketing engine is designed to perform multiple functions: it receives user profile data, processes decision-related data from the decision engine, generates personalized advertisements, and delivers targeted marketing content. This multi-functionality improves advertising relevance while avoiding the need for separate specialized systems.
Solution Approach 2:
The system implements feedback loops where user interactions with search results and decision-making processes are continuously monitored and fed back to the marketing engine. This feedback mechanism allows the system to refine advertising targeting accuracy over time based on actual user behavior and preferences.
Data Source
AI summary
A system, method and computer program product for interfacing a decision engine and a marketing engine in order to provide vendor-related data in response to decision-related data is disclosed. In at least one embodiment, the system and method may include providing a decision engine on a user-accessible network; interfacing a marketing engine with the decision engine on the network; receiving a plurality of user inputs with the decision engine; processing decision-related data with the decision engine in accordance with the plurality of user inputs; sharing the decision-related data with the marketing engine; processing the decision-related data with the marketing engine; and transmitting vendor-related data via the network.