User Identification

This guide provides a comprehensive overview of how VocBase identifies users, from the initial matching process to the Universal Customer Identity (UCI) system. It is intended for product managers, designers, researchers, and support agents who want to understand how VocBase links feedback to revenue data.

Introduction

User identification is the process of linking feedback from various sources to the corresponding customers in your revenue data. This is a critical step in understanding the business impact of feedback and making data-driven decisions. By accurately identifying users, you can:

  • Quantify the business impact of feedback: See how much revenue is associated with each piece of feedback.
  • Prioritize with confidence: Focus on the feedback that has the greatest impact on your bottom line.
  • Identify high-value customers: See what your most valuable customers are saying, and take action to keep them happy.
  • Reduce churn: Identify at-risk customers and take proactive steps to prevent them from churning.

The User Identification Process

VocBase uses a multi-step process to identify users. Here's a breakdown of how it works:

  1. Exact Email Match: This is the highest confidence match. If the email address of the user who provided the feedback matches the email address of a customer in your revenue data, it's considered a match.
  2. Company Domain Match + Name Similarity: If the email domain of the user who provided the feedback matches the email domain of a customer in your revenue data, and the names are similar, it's considered a match.
  3. Name Similarity: If the name of the user who provided the feedback is similar to the name of a customer in your revenue data, it's considered a match. This is the lowest confidence match, and it requires a higher similarity threshold.

The Universal Customer Identity (UCI) System

The Universal Customer Identity (UCI) system is a more advanced way to identify users. It uses a combination of data from all your integrations to create a single, unified view of each customer. Here's how it works:

  1. Integration-Specific IDs: When you connect a new integration, VocBase will look for an existing user with the same integration-specific ID. If it finds one, it will link the new feedback to the existing user.
  2. Fuzzy Matching: If it can't find a match based on the integration-specific ID, it will use a fuzzy matching algorithm to find potential matches based on the user's email address and name.
  3. Confidence Score: For each potential match, it will calculate a confidence score based on the similarity of the user's email address and name. If the confidence score is high enough, it will link the new feedback to the existing user.

Troubleshooting

If you encounter any issues with user identification, here are some common problems and their solutions:

  • Feedback is not being linked to revenue data:
    • No Match: The user who provided the feedback may not exist in your revenue data.
    • Low Confidence: The confidence score of the match may be too low.
  • Feedback is being linked to the wrong customer:
    • Incorrect Match: The fuzzy matching algorithm may have made an incorrect match.

If you continue to experience issues, please contact our support team for assistance.