Dynamic Price Negotiation via Contextual Data Analysis
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Solution Overview
Problem
Current online shopping platforms lack an efficient method for price negotiation, as retailers often rely on predefined price strategies without considering contextual information, limiting the ability for consumers to obtain the best prices, especially in competitive market environments where multiple retailers offer similar items.
Innovation Solution
A system and method that utilizes purchase context information, such as user interest, competing items, and feedback, to determine a negotiated price for items in an online shopping environment, providing users with dynamic pricing options and incentives to facilitate better purchasing decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If retailers use predefined price strategies without contextual information, then pricing decisions are simple and quick to make, but the prices obtained are not optimized and consumers cannot get the best prices
Solution Approach 1:
The system performs preliminary actions by collecting purchase context information (user profiles, browsing history, competing items, market conditions) before price negotiation occurs. This pre-gathering of data enables accurate price optimization without adding complexity during the actual negotiation moment, as the analytical framework is already in place.
Solution Approach 2:
The patent introduces an intermediary negotiation system that acts as a mediator between consumers and retailers. This intermediary processes contextual information, applies negotiation algorithms, and presents optimized prices, thereby managing the complexity of price optimization internally while keeping the user interface simple and straightforward.
2Adaptability or versatility
If retailers predefine negotiation prices without contextual information, then the negotiation process is simple and fast, but the prices do not reflect market conditions or consumer behavior
Solution Approach 1:
The system performs preliminary actions by collecting purchase context information (user profiles, browsing history, competing items, market conditions) before price negotiation occurs. This pre-gathering of data enables accurate price optimization without adding complexity during the actual negotiation moment, as the analytical framework is already in place.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring purchase context information, consumer responses to negotiated prices, and market conditions. This feedback loop allows the negotiation system to adapt and learn from past interactions, improving price adaptability over time while maintaining efficient negotiation processes through refined algorithms.
3Ease of operation
If price negotiation services require users to name their own specific price, then retailers have simpler pricing control, but users cannot obtain optimized prices and must guess appropriate price points
Solution Approach 1:
The system empowers users with self-service capabilities by providing them with access to the negotiation interface where they can input their desired price range or let the system automatically negotiate. The system then uses contextual information to determine optimized prices, giving users control while ensuring accurate pricing through data-driven algorithms.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting price parameters based on contextual factors such as user purchase history, competing item prices, demand patterns, and retailer margins. This allows the system to transform static predefined prices into dynamic optimized prices that adapt to real-time conditions while maintaining ease of use through automated calculations.
Data Source
AI summary
A system and machine-implemented method for providing a user participating in an online shopping environment with a negotiated price for an item, the method comprising receiving a request to negotiate a price of an item being posted to an online shopping environment and offered at a first price, identify purchase context information corresponding to the item in response to receiving the request, wherein the purchase context information include information regarding the item and information regarding the online shopping environment, determining a negotiated price for the online item based on the purchase context information and providing the negotiated price for display to one or more users.