Buyer’s Agent Ranking With Data-Driven Spinner Selection
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Solution Overview
Problem
Existing methods for selecting a quality buyer's agent lack a structured and unbiased approach, often leading to biased decision-making.
Innovation Solution
An apparatus comprising a circular base, pole, inserts, and a spinner, along with a method involving data analysis to rank agents, ensuring a fair and interactive selection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional unstructured methods are used for selecting buyer's agents, then the selection process is simple and quick, but the decision-making becomes biased and unreliable
Solution Approach 1:
The patent applies preliminary action by pre-ranking buyer's agents based on performance data before the actual selection. The system collects historical transaction data, calculates performance metrics (such as price reduction achieved, sale speed), and creates a ranked list of agents in advance. This preliminary ranking ensures that when the spinner is used, only pre-qualified agents are considered, eliminating bias while maintaining simplicity.
Solution Approach 2:
The patent introduces a spinner as an intermediary device that mediates between the user's desire for a simple selection and the need for fair, data-driven results. The spinner randomly selects from the pre-ranked list of qualified agents, acting as an impartial mediator that removes human bias from the final selection while relying on the preliminary data analysis for quality assurance.
2Measurement precision
If comprehensive performance data analysis is conducted to rank agents, then selection quality improves, but data processing time and computational resources increase
Solution Approach 1:
The system performs comprehensive data analysis and agent ranking in advance, before the actual selection moment. Historical transaction data is collected, cleaned, and processed to calculate performance metrics such as price reduction achieved, average days to sale, and transaction volume. This preliminary processing stores the results in a ready-to-use ranked list, so that when selection is needed, the computationally intensive work has already been completed.
Solution Approach 2:
The patent segments the data processing into distinct phases: data collection from multiple sources, data cleaning and validation, performance metric calculation, agent ranking, and final selection. This segmentation allows each phase to be optimized independently and enables the system to reuse processed data for multiple selections without repeating the entire analysis chain.
Data Source
AI summary
The present invention discloses an apparatus and method designed to facilitate the selection of the best buyer's agents. The apparatus consists of a transparent circular base equipped with a centrally positioned pole, around which three inserts with arrows can be attached. These inserts, each associated with a potential buyer's agent's location on an accompanying rectangular map, lay flat against the base once secured. A spinner, attachable to the pole, is designed to spin and point to one of these inserts, thereby selecting a buyer's agent in a visually engaging manner. This method introduces an element of geography in the selection process while maintaining a structured approach, offering a unique solution for individuals or organizations seeking to choose a buyer's agent without inherent biases. The invention is particularly suited for applications where impartiality is valued in the decision-making process, providing a transparent, fair, and interactive method for selection.