Social Network Trust Ranking for Purchasing Advice
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Solution Overview
Problem
Consumers face challenges in obtaining trusted purchasing advice due to limitations in existing methods, including lack of access to expert reviewers within their social network, potential biases, and risks associated with seeking advice from unknown or untrustworthy sources, especially in complex purchasing decisions.
Innovation Solution
A computer-implemented system and method that identifies and ranks trusted expert reviewers based on their social network proximity and expertise, allowing consumers to receive advice from within their network, and facilitates transactions by analyzing transaction histories and social connections to provide a ranked list of trusted advisors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If consumers seek advice from expert reviewers outside their social network, then they can access specialized knowledge, but trust levels are limited and fraud risk increases
Solution Approach 1:
The patent introduces a social network intermediary system that connects consumers with expert reviewers through trusted social connections. The system uses social network data to identify reviewers who are both experts in the relevant field and have proven trustworthiness through their social connections and transaction history, thereby mediating between the need for expert knowledge and the need for trust.
Solution Approach 2:
The system performs preliminary verification of reviewer credentials, expertise areas, and trust levels before connecting consumers with reviewers. Transaction histories and social network analyses are conducted in advance to pre-establish trust metrics, so that when a consumer needs advice, the matching reviewer has already been vetted and verified.
2Ease of operation
If consumers use personal shopping services from external experts, then they receive specialized purchasing advice, but the cost is high and consumer recourse is limited
Solution Approach 1:
The system enables consumers to independently access and evaluate multiple reviewers based on transparent trust metrics and expertise profiles. Rather than paying for a single expert's service, consumers can self-navigate through reviewer profiles, transaction histories, and social connections to select the most appropriate advisor for their needs.
Solution Approach 2:
The system provides consumers with more than they would typically receive from a single paid consultant—multiple reviewer options, detailed trust metrics, and transparent transaction histories. This excessive information availability allows consumers to make better-informed decisions without incurring high service fees.
3Adaptability or versatility
If consumers rely on merchant-provided advice, then they have recourse for returns, but the advice is biased toward merchant interests
Solution Approach 1:
The system introduces an independent social network intermediary that separates the consumer from direct merchant influence. Reviewers are selected based on their social connections and proven expertise rather than merchant affiliation, creating an intermediary layer that provides objective advice while maintaining consumer protection through the platform's transaction oversight.
4Reliability
If consumers conduct extensive research for purchasing decisions, then they can evaluate product aspects thoroughly, but the effort and time required is substantial
Solution Approach 1:
The system performs preliminary research and evaluation work by analyzing reviewer expertise, transaction histories, and product performance data before the consumer makes a decision. This pre-computed information is presented in an easily digestible format, eliminating the need for consumers to conduct extensive independent research.
Solution Approach 2:
The system aggregates feedback from multiple sources including transaction histories, reviewer ratings, and social network validations to provide comprehensive product evaluations. This synthesized feedback replaces the need for consumers to individually research and evaluate multiple product aspects.
Data Source
AI summary
Facilitating the solicitation of expert advice from trusted reviewers using a system that maintains a registry of product reviewers with areas of expertise. The system can identify reviewers that have an area of expertise relating to a consumer's purchase advice request (PAR) and are directly or indirectly connected to the consumer's social network. The system can calculate the trust level of the reviewers based on the relevance of each reviewer's area of expertise to the PAR and the degree of social separation between each reviewer and the consumer. The system provides the consumer with a ranked list of reviewers to answer the PAR and can forward the PAR to the reviewer selected by the consumer. In addition, the system can also complete the purchase of product/service recommended by the reviewer pursuant to the PAR on behalf of the consumer.