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User Insights

This document provides an in-depth overview of LoginRadius’ user insights and user segmentation features. These capabilities help businesses manage user data, optimize engagement strategies, and enhance reporting. The document covers user segmentation, analytics, and data export functionalities, offering a structured approach to understanding and leveraging user data.

User Segmentation

User segmentation allows businesses to categorize and analyze user data for targeted insights. Organizations can group and filter users based on profile fields or custom object queries, enabling strategic decision-making and personalized engagement. The segmented data can be exported in CSV/JSON format for seamless integration with marketing platforms.

  • Key Features:

    • Saved Segmentation: Manage and access previously saved user segments for quick retrieval and analysis.

    • user Query: To refine search results, filter users using profile fields and logical operators (AND/OR).

    • user Object Query: For advanced data filtering, segment users based on custom object fields, such as purchase history or wishlist items.

Use Case 1

Businesses can use segmentation to identify key user groups, such as frequent buyers or potential churn risks, and tailor marketing campaigns accordingly. For example, a B2C company can analyze purchase histories and wishlist data to create personalized promotions and improve user retention.

Use Case 2

Retail businesses can segment users based on purchase frequency and spending habits. High-value users can be enrolled in loyalty programs with exclusive discounts, while infrequent shoppers can receive targeted promotions to encourage repeat purchases.

For further details, refer to the following document for more information about the user segmentation section.

User Analytics

Analytics will give you an idea of your LoginRadius site's key statistics. We have user analytics available in the Insight tab under the Admin Console, which represents user information regarding various aspects of analytics. This tab contains valuable charts and analytic tools to view and measure your site's overall performance regarding user registrations and logins. The information is aggregated and categorized into identity analytics and login analytics. These analytics will help you improve application performance and understand the user experience.

Identity Analytics

This section focuses on user growth and demographics, offering detailed charts and reports on:

  • Key Analytics: Growth trends, provider breakdowns, geographic distribution, age groups, gender, browser usage, and device preferences.

  • Data Collection: User profiles and logs are the primary data sources for analysis.

Use Case: Businesses can leverage demographic insights to target specific user segments, track growth patterns, and refine user experience strategies.

Login Stats

This section provides an overview of user login behavior, including:

  • Key Metrics: Login distribution, daily and monthly active users, and user return dates.

  • Engagement Details: Insights into provider, browser, and device engagement.

  • Data Collection: Data is derived from the user agent, provider, IP address, language, host, and login timestamps.

Use Case: Businesses can use login analytics to assess user engagement, optimize authentication experiences, and identify preferred login methods.

Refer to the following document for more information about the user analytics section.

Platform Analytics

This section provides a comprehensive overview of API behavior and system performance, including:

  • Key Metrics: Request volume, API response codes, and endpoint-level performance trends.
  • Performance Details: Visual insights into API traffic, error types, and response times for core authentication and profile management operations.
  • Data Collection: Metrics, including response codes, timestamps, endpoints accessed, and execution times, are derived from API calls to the LoginRadius backend.

Use Case: Businesses can leverage platform analytics to monitor API health, optimize response times, troubleshoot errors, and ensure service reliability across user-facing and internal applications. Refer to the following document for more information about the platform analytics section.