Recommendation Engine Scoring Product Data Queries
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Solution Overview
Problem
Customers, especially small to medium-sized businesses, struggle to identify and effectively market products that meet their needs due to lack of time and resources. This leads to missed opportunities and reduced revenue and profit margins.
Innovation Solution
A method and system for providing product data and recommendations to users based on database queries and transaction data. This involves receiving query data, determining classifications, identifying associated products, calculating potential revenue and purchase probability, and transmitting product data if a score exceeds a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If customers manually monitor and handle administrative aspects such as pricing, inventory management, and marketing, then they can make informed decisions, but it consumes significant time and resources
Solution Approach 1:
The system enables automated self-service by using machine learning models to automatically analyze transaction data, identify product opportunities, and generate recommendations without requiring manual customer intervention. The system serves itself by continuously processing data and providing actionable insights automatically.
Solution Approach 2:
The patent introduces an intermediary system (the recommendation engine) that acts as a mediator between raw transaction data and customer decision-making. This intermediary processes and interprets data, providing curated recommendations that bridge the gap between data availability and actionable insights.
2Productivity
If product providers actively market products to customers, then sales opportunities increase, but it requires significant resources and effort
Solution Approach 1:
The system changes the parameters of product recommendation by using dynamic scoring mechanisms that evaluate multiple factors (relevance, potential revenue, purchase probability) to determine which products to recommend. This transforms the marketing approach from broad-based to precisely targeted based on calculated parameters.
Solution Approach 2:
The patent implements preliminary action by pre-calculating and storing product recommendations in databases before customers need them. The system proactively identifies opportunities and prepares recommendations in advance, so they are immediately available when needed without requiring real-time complex processing.
3Loss of information
If customers lack awareness of relevant products and services, then they may miss business opportunities, but providing comprehensive product information increases system complexity
Solution Approach 1:
The system extracts only the most relevant product information from the vast available data, presenting a curated subset rather than all possible products. This extraction principle filters out unnecessary information while retaining the most valuable insights for each customer context.
Solution Approach 2:
The patent applies local quality by customizing product recommendations specifically for each customer based on their unique transaction data, industry, and needs. Rather than providing uniform information to all customers, the system tailors the quality and type of information to each local context.
Data Source
AI summary
Provided is a method for providing product data to a user. The method may include receiving query data associated with a plurality of queries of a database by a user. A classification for at least two queries of the plurality of queries may be determined. A product associated with the classification of the at least two queries may be determined. A potential revenue associated with the product may be calculated based on the user. A probability that the user will purchase the product may be calculated. A score may be calculated based on the potential revenue and the probability that the user will purchase the product. Product data associated with the product may be transmitted to the user if the score exceeds a threshold. A system and computer program product are also disclosed.