Real Estate Offer Grid Layout with ML Categorization
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Solution Overview
Problem
The conventional real estate transaction process lacks transparency and auditability, leading to buyers missing higher offers due to incomplete information and sellers being unaware of the number and amounts of offers received, resulting in uninformed decisions and a lack of confidence in the process.
Innovation Solution
A software-based system that displays real estate offers in a grid layout on a seller's device, using machine learning to categorize offers by price range and detect fraudulent offers, allowing sellers to track offers in real-time and make informed decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a conventional real estate offer system is used, then agents can manually handle offers, but transparency and auditability are lost, leading to incomplete information for buyers and sellers
Solution Approach 1:
The patent introduces a centralized server as an intermediary between buyers, sellers, and agents. This server acts as a neutral mediator that receives, stores, and distributes offer information to all parties, ensuring transparency and auditability while maintaining a manageable system architecture through centralized coordination rather than complex peer-to-peer interactions
Solution Approach 2:
The system implements real-time feedback mechanisms where buyers can see the status of their offers, sellers can view all received offers with full details, and all parties receive notifications of new offers and status changes. This continuous feedback loop eliminates information asymmetry and creates an auditable trail of all transactions
2Quantity of substance
If multiple offers are received by a seller, then the seller can potentially get a higher price, but the seller cannot track the number and amounts of offers without speaking to the agent
Solution Approach 1:
The system enables sellers to self-serve by providing them with direct access to a dashboard that displays all offers received, including the number of offers, their amounts, and current status. Sellers can independently view and manage their offers without needing to contact agents, empowering them to make informed decisions based on complete information
Solution Approach 2:
The server implements a universal interface that serves multiple functions: it acts as a receiving endpoint for offers, a storage database for offer information, a distribution network for notifying parties, and a display system for showing offer details. This multi-functional design consolidates what would otherwise require multiple separate systems into a single cohesive platform
3Productivity
If buyers submit offers without complete information, then the buying process can proceed, but buyers may miss opportunities due to slightly higher offers from other buyers they were unaware of
Solution Approach 1:
The system performs preliminary actions by providing buyers with complete information about the property, seller preferences, and current market conditions before buyers submit their offers. This advance information equips buyers to make well-informed offers, reducing the likelihood of missing opportunities due to incomplete understanding of the competitive landscape
Solution Approach 2:
The patent replaces the mechanical system of verbal communication between agents with an automated electronic information distribution system. The server automatically notifies all parties of new offers and status changes, eliminating the need for manual information relay and ensuring that all buyers receive identical, timely information without human error or bias
4Device complexity
If the real estate process relies on agents to be competent and honest, then the process can function with minimal system variables, but there are many variables introduced by human factors
Solution Approach 1:
The system implements self-service functionality where automated algorithms handle offer evaluation, matching, and notification processes without requiring human intervention. The server independently performs tasks such as comparing offers against seller criteria, determining offer status, and communicating outcomes, thereby eliminating variables related to human competence, honesty, and timeliness while maintaining process reliability
Data Source
AI summary
A method implemented in software and a software system for dynamically determining how to display one or more statements of interest (such as an offer or soft offer) is disclosed. After receiving one or more statements of interest from potential buyers, a software-implemented method determines a preferred manner for displaying one or more statements of interest received from the potential buyers to the seller, and displays the offers in a grid layout. The grid layout shows a number of buyers interested in making a hard offer in a manner that gives the seller insight regarding pricing their property as well as other factors that are determined to likely make the property more valuable. The one or more statements of interest are categorized into one or more categories, including the seller's displayed (and quoted) price. Each of the categories is associated with a price range, and optionally the price range is determined using machine learning techniques.