Multi-Network Caller ID Selection for Reduced Mislabeling
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Solution Overview
Problem
Existing telecommunications systems face challenges in accurately managing brand identity and reputation due to mislabeling, spoofing, and inconsistent caller identification, leading to reduced consumer engagement and brand harm.
Innovation Solution
A method for analyzing call reputation and branding data across multiple communications networks to dynamically select the most favorable calling party identifier, using inquiry call attempts and software control message-based termination to optimize outbound calls and enhance brand identity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional caller identification systems are used, then call routing is simple, but caller identification accuracy deteriorates due to mislabeling and spoofing
Solution Approach 1:
The system performs preliminary reputation analysis and branding verification on calling party identifiers before calls are routed. Number sentry servers pre-assess identifiers across multiple communication networks, storing reputation data and branding accuracy metrics in advance, so that when a call arrives, the routing system can quickly retrieve and use pre-evaluated identifier quality information.
Solution Approach 2:
Number sentry servers act as intermediary components between the calling party and the communication network. These servers analyze calling party identifiers, assess their reputation and branding accuracy, and provide filtered, verified identifier information to the routing system, mediating between raw identifier data and the routing decision-making process.
2Reliability
If multiple communication networks are monitored, then brand reputation management improves, but data collection complexity increases
Solution Approach 1:
The number sentry server is designed as a universal platform that can monitor and evaluate calling party identifiers across multiple different communication networks simultaneously. It performs consistent reputation analysis and branding verification functions regardless of which network the identifier originates from, providing unified multi-network coverage through a single system.
Solution Approach 2:
The system combines multiple network monitoring functions into a unified number sentry server platform. Instead of having separate monitoring systems for each communication network, the invention merges the capabilities to assess identifiers across AT&T, T-Mobile, Verizon and other networks into a single integrated system that handles multiple networks concurrently.
3Measurement precision
If automated inquiry call attempts are made, then identifier reputation data is improved, but call volume increases
Solution Approach 1:
The system performs a limited number of automated inquiry call attempts (typically one or two) to gather sufficient reputation data on calling party identifiers. This partial action approach collects enough information to make informed routing decisions without excessively increasing overall call volume, balancing data accuracy needs with call efficiency constraints.
Data Source
AI summary
The present invention relates to call routing, caller identification management, and telecommunications reputation and brand analysis. It provides methods for increasing call connections to consumers across multiple communications networks by analyzing call reputation and branding data associated with an originating calling party identifier and selecting the identifier with the most favorable reputation and accurate branding. The methods include configuring computing devices with distinct receiving called party identifiers, initiating inquiry call attempts to capture calling party reputation and brand analysis data, and communicating the data to a server. If an inquiry call attempt fails, a second attempt is made to an alternate receiving called party identifier. The server determines a preferred originating calling party identifier based on a computed risk factor derived from reputation and brand analysis data across multiple networks. The preferred identifier is then used for outbound calls reducing mislabeling, improving brand identity, and increasing consumer answer rates.