AI Dynamic Pricing System for Real-Time Product Price Adjustment
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Solution Overview
Problem
Existing static pricing mechanisms fail to adapt efficiently to changing supply and demand, leading to suboptimal sales and revenue maximization before product expiration or target dates, resulting in waste and lost revenues.
Innovation Solution
A system and method using artificial intelligence to determine an optimum price curve and dynamically update product prices in real-time, incorporating primary and secondary data, including historical information, consumer habits, and competitor pricing, to incentivize purchases and maximize sales or revenue before target dates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static pricing mechanisms are used, then pricing simplicity is maintained, but adaptability to changing supply and demand deteriorates
Solution Approach 1:
The patent implements dynamic pricing by continuously adjusting prices based on real-time supply and demand conditions. The system transitions from static pricing to dynamic pricing where prices fluctuate automatically in response to changing market conditions, product freshness, and demand signals, thereby resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The system incorporates feedback loops that monitor sales data, inventory levels, and demand patterns to automatically adjust pricing. This feedback mechanism enables the pricing system to adapt to changing conditions without manual intervention, achieving high adaptability while managing complexity through automated control algorithms.
2Speed
If traditional discount methods are deployed, then sales motivation is improved, but response time to market changes deteriorates
Solution Approach 1:
The pricing system operates autonomously by automatically monitoring market conditions and adjusting prices without requiring manual decision-making or physical price changes. This self-service capability enables real-time response to market changes, eliminating the time delays associated with traditional discount deployment methods while maintaining sales motivation through dynamic pricing adjustments.
Solution Approach 2:
The patent replaces mechanical pricing methods (physical price tags, manual coupon distribution) with electronic pricing systems that can be updated instantly through software. This substitution eliminates the physical and temporal constraints of traditional pricing mechanisms, enabling immediate price adjustments in response to market conditions.
3Loss of substance
If prices are not adjusted dynamically, then operational simplicity is maintained, but waste from expired products increases
Solution Approach 1:
The system proactively adjusts prices before products reach their expiration dates by predicting demand patterns and implementing preventive pricing strategies. This preliminary action allows the system to maximize product sales before expiry, significantly reducing waste while requiring automated pricing adjustments based on time-to-expiration calculations.
Data Source
AI summary
A system and method are provided for determining an optimum price curve to a target date and dynamically updating a price of a product in real-time in a store of a merchant. A merchant database contains and a third-party source provides information which is relevant to determining the price. An enhanced data engine and database generates and stores enhanced information which is derived from the merchant and third-party information and which is relevant to determining the price of the product. A dynamic pricing mechanism includes an artificial intelligence trained on the enhanced information and is configured to determine the optimum price curve for the product, and to transmit a current price from the optimum price curve via a communications network. An electronic price display is located in the store and receives from the dynamic pricing mechanism and visually displays in real-time the current price of the product.