Dynamic Telecommunication Pricing Routing System
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Solution Overview
Problem
Current telecommunications pricing systems face challenges in dynamically adapting prices based on seasonal variations and consumer behavior, leading to inefficient call routing and potential losses in revenue due to inadequate price adjustments.
Innovation Solution
A system and method that involves processing large datasets to deseasonalize call volume data, estimate expected minutes of usage, detect significant changes, and classify the impact of price changes on margins, allowing for dynamic price adjustments and reversion to optimize pricing strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static pricing is used for telecommunications services, then pricing simplicity is maintained, but revenue optimization and adaptability to seasonal variations are lost
Solution Approach 1:
The patent implements dynamic pricing by allowing wholesale carriers to adjust termination rates based on seasonal variations and call volume patterns. The system transitions from static pricing to dynamic pricing where rates can change over time to optimize revenue while adapting to market conditions.
Solution Approach 2:
The patent incorporates feedback mechanisms where least cost routing systems provide call volume data and routing decisions back to the pricing system. This feedback loop enables the pricing system to adjust rates based on actual market response and call patterns, creating a self-optimizing pricing mechanism.
2Loss of energy
If least cost routing selects the least expensive carrier, then call termination cost is minimized, but call quality and carrier capacity constraints are violated
Solution Approach 1:
The patent changes the pricing parameter dynamically based on carrier capacity and quality metrics. When a carrier approaches capacity limits or quality thresholds, the system adjusts the effective price to route calls to alternative carriers, balancing cost minimization with service reliability.
Solution Approach 2:
The patent introduces an intermediary pricing mechanism that mediates between the least cost routing system and carrier capacity constraints. The pricing system acts as a mediator that adjusts rates to influence routing decisions, ensuring carriers operate within capacity limits while maintaining call quality standards.
3Productivity
If dynamic price adjustments are implemented, then revenue optimization is achieved, but pricing system complexity and data processing requirements increase
Solution Approach 1:
The patent makes the pricing system multi-functional by integrating it with least cost routing, call management, and analytics functions. The same system infrastructure supports multiple objectives including revenue optimization, capacity management, and quality assurance, reducing overall system complexity despite dynamic pricing requirements.
Data Source
AI summary
Aspects of the present disclosure relate to telecommunications networks, processing and routing calls between networks, a computing system and methodologies for optimizing pricing particularly in situations with massive amounts of data, processing call volume data, deseasonalizing data, minutes of use data, establishing and distributing pricing data for use in routing decisions, among other features and advantages.