Unlocking the Power of Social Proofing: How CURD's Social Search Engine and Review System Enhance User Experience

Unlocking the Power of Social Proofing: How CURD's Social Search Engine and Review System Enhance User Experience

Social Proofing on CURD:

At CURD, social proofing is a foundational element that drives user interactions, recommendations, and decision-making processes. Social proofing leverages the power of users' networks to validate recommendations, reviews, and search results, creating a trusted and reliable ecosystem for users.

CURD's Search Engine:

CURD's search engine is unlike traditional search engines like Google. Instead of relying solely on algorithms and keywords, CURD's search results are socially validated based on users' interactions with their network. When users search for a business or service, the top results are determined by factors such as:

  1. Reviews from Mutual Connections: The number and quality of reviews from users' mutual connections play a significant role in ranking search results. Businesses or services with higher reviews from mutual connections are prioritized, indicating a stronger endorsement from trusted sources.


  1. Number of Closed Businesses with Mutual Connections: CURD also considers the number of closed deals or transactions between users and their mutual connections on the CURD app. Businesses that have successfully conducted transactions with users' mutual connections are given preference, showcasing real-world interactions and trustworthiness.

CURD's Review System:

CURD's review system is designed to provide users with socially validated feedback on businesses and services. When users visit a business page and search for reviews, they are presented with reviews from their network in a hierarchical manner:

  • Reviews from 1st-Level Connections: Users first see reviews from their direct connections or 1st-level connections. These reviews carry significant weight as they come from individuals users personally know and trust.

  • Reviews from 2nd-Level Connections: Next, users see reviews from their extended network or 2nd-level connections. While not as close as 1st-level connections, these reviews still provide valuable insights from individuals within users' broader network.

  • Reviews from 3rd-Level Connections: Following 2nd-level connections, users may encounter reviews from 3rd-level connections, further expanding the scope of feedback.

  • Random Reviews: Finally, users may encounter random reviews from users outside their immediate network. While these reviews are included for additional context, the emphasis is placed on socially validated feedback from closer connections.

Integration with AI:

In cases where users do not receive responses on referral posts, CURD's AI algorithm goes beyond conventional methods by analyzing all businesses connected to the user. By considering factors such as businesses with reviews from the user's network, CURD AI generates socially validated recommendations, ensuring users receive relevant and trustworthy suggestions based on their network interactions.


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