Users Tab
A comprehensive guide to understanding and analyzing individual users in Rybbit's Behavior Analytics
A Guide to Rybbit's Users Tab
The Users tab in Rybbit's Behavior Analytics section provides detailed insights into the individual people visiting your website. While traditional analytics often focuses on aggregated metrics and traffic patterns, the Users tab shifts the perspective to show you who your visitors are, their behaviors, engagement patterns, and how they interact with your site over time.
What is a User?
A user in Rybbit represents a unique visitor to your website. Unlike cookie-based analytics, Rybbit identifies users through privacy-first mechanisms that don't compromise visitor privacy. Each user is assigned a unique identifier that allows you to track their behavior across multiple sessions without using cookies.
Understanding users is fundamental to modern analytics because it allows you to move beyond "how many people visited" to answer more meaningful questions like "who are my users," "what do they do," and "how can I better serve them."
Accessing the Users Tab
To view your site's user data:
- Log into your Rybbit dashboard
- Navigate to the Behavior section in the left sidebar
- Click on the Users tab
You'll be presented with a comprehensive list of unique visitors along with key information about each user, their activity, and engagement metrics.
Key User Metrics
When examining the Users tab, you'll find several important metrics about each user:
User ID
A unique, anonymized identifier for each visitor. This ID allows you to track a user across multiple sessions and devices (if they use the same browser).
First Visit
The date and time when the user first visited your website. This helps you understand user acquisition patterns and identify your oldest engaged users.
Last Visit
The most recent date and time the user visited your site. This metric indicates user retention and helps identify dormant or churned users.
Total Sessions
The number of separate visits the user has made to your website. Users with more sessions are generally more engaged and loyal.
Pages Viewed
The total number of pages visited across all sessions by this user. High page view counts often indicate strong engagement with your content.
Events Triggered
The total number of custom events (like button clicks, form submissions, or purchases) triggered by this user across all their sessions.
Device Type
The type of device(s) the user has accessed your site from (desktop, mobile, tablet). Some users may appear multiple times if they visit from different devices.
Location
The geographic location where the user accessed your site, based on IP address geolocation.
Referrer
How the user initially arrived at your site (organic search, paid ads, social media, direct, etc.).
Last Activity
The type of action the user took during their most recent visit (page view, event triggered, scroll, etc.).
Filtering and Searching Users
Rybbit provides powerful filtering options to help you segment and analyze specific user groups:
Filter by Total Sessions
Find users who have visited your site a specific number of times. For example, identify one-time visitors versus loyal users who return frequently.
Filter by Page Views
Isolate users based on how many pages they've viewed. This helps identify power users who deeply engage with your content versus casual browsers.
Filter by Events
Search for users who have triggered specific events. For instance, find all users who have completed a purchase or signed up for a newsletter.
Filter by Device
Segment users by their device type (desktop, mobile, tablet) to understand usage patterns across different platforms.
Filter by Location
Analyze users from specific geographic regions or countries to understand your global audience and identify regions for growth.
Filter by Referrer
Find users who arrived from specific traffic sources to understand which channels bring high-quality visitors.
Filter by Activity Date
Isolate users who visited within a specific time period. This helps identify recently active users versus historical users.
Filter by First Visit Date
Find users who discovered your site within a specific timeframe. This is useful for measuring the impact of marketing campaigns or product launches.
Analyzing User Behavior Patterns
The Users tab becomes most powerful when you identify and analyze patterns across user groups:
High-Value Users
Identify users who visit frequently, view many pages, and trigger important events. These power users often provide the most value and should be prioritized in retention efforts.
One-Time Visitors
Find users who visited only once and didn't return. Understanding why these visitors churn can help you improve your onboarding and value proposition.
Device-Specific Users
Look for patterns in how different user groups use different devices. Some users may primarily access your site on mobile while others prefer desktop.
Geographic Patterns
Analyze user behavior by location to identify regional differences in engagement, preferences, and conversion patterns.
Traffic Source Quality
Compare users from different referrers to determine which marketing channels and traffic sources bring the most engaged and valuable users.
Common Use Cases
Understanding User Retention
Track how many users return to your site over time. Compare new users versus returning users to measure customer loyalty and identify churn risks.
Identifying High-Value Customers
Find users who have completed valuable actions (purchases, sign-ups, upgrades) and analyze what they have in common. Use these patterns to identify similar users for targeted outreach.
Improving New User Onboarding
Analyze the behavior of first-time visitors to see where they struggle or drop off. Use these insights to streamline your onboarding experience.
Measuring Marketing Campaign Effectiveness
Compare users acquired through different marketing channels to determine which campaigns bring the most engaged and valuable users.
Optimizing for Key User Segments
Identify your most valuable user segments (by geography, device, behavior) and optimize your product and marketing specifically for them.
Detecting Bot or Spam Activity
Look for unusual user behavior patterns that might indicate bots or malicious activity, such as users triggering hundreds of events in seconds.
User Privacy and Data Protection
Rybbit's Users tab maintains strict privacy standards:
- User identification is anonymous and doesn't rely on cookies
- No personally identifiable information (PII) is collected without explicit consent
- Users can opt out of tracking at any time
- All user data is encrypted and stored securely
- User data retention follows GDPR and CCPA compliance standards
You maintain full control over your user data with options for self-hosting and complete data ownership.
Tips for Effective User Analysis
Segment by Behavior, Not Just Demographics: While location and device data is useful, segmenting by behavior (pages viewed, events triggered) often reveals more actionable insights.
Look for First-Time User Patterns: Understanding how new users interact differently from returning users can dramatically improve your onboarding and activation rates.
Track User Lifecycle: Monitor how individual users progress through different stages (awareness, engagement, conversion, retention). Use this to identify drop-off points and opportunities.
Correlate with Business Metrics: Connect user data with your business outcomes. Which user segments generate the most revenue, sign-ups, or other valuable actions?
Monitor Emerging Segments: Regularly check the Users tab for new patterns. Emerging user segments sometimes represent new market opportunities.
Compare Before and After Changes: When you make changes to your site or product, monitor how user behavior patterns change to measure impact.
Troubleshooting Common Issues
Missing user data
Ensure the Rybbit tracking script is installed and that your privacy settings allow user identification. Some strict privacy settings may disable user-level tracking.
Users appearing multiple times
This typically happens when users visit from different browsers or devices. This is expected behavior in Rybbit's privacy-first approach.
Unexpected user counts
If user numbers seem low, check that your traffic is actually being tracked. Verify the script is loading correctly and no content blockers are interfering.
Location data seems inaccurate
IP-based geolocation has inherent limitations. Location should be used as an approximation, particularly for mobile users.
Advanced User Analytics
User Cohort Analysis
Group users by when they first visited (weekly, monthly cohorts) and track how retention and engagement differ. This helps you understand if recent traffic quality differs from historical users.
User Lifetime Value (LTV)
For users who complete valuable actions (purchases), calculate their lifetime value by tracking their total contribution over all sessions. This helps prioritize high-value user retention.
Activation Analysis
Track the path new users take to reach their first meaningful action (first page view, event, conversion). Users who activate quickly are more likely to become long-term users.
Churn Prediction
Monitor users who haven't visited recently. Users with long gaps between visits are at higher risk of permanent churn. Consider re-engagement campaigns for these users.
User Segmentation Strategies
Create mental models of different user types:
- Casual Browsers: Few sessions, low engagement
- Regular Users: Consistent visits, moderate engagement
- Power Users: Frequent visits, high engagement, multiple events
- Converters: Users who complete valuable actions
Each segment may require different optimization strategies.
Connecting Users with Other Analytics
Users and Sessions
Each user typically has multiple sessions. Use the Sessions tab to understand the specific behavior within individual user sessions.
Users and Events
Custom events provide context for user behavior. Correlate user segments with the events they trigger to understand motivation and satisfaction.
Users and Errors
If enabled, error tracking shows which users are experiencing issues. Investigate error patterns to improve product quality.
Best Practices
Privacy-First Approach: Always remember that behind every user ID is a real person. Respect their privacy and use data responsibly.
Focus on Actionable Segments: Don't just identify segments—use insights to make concrete changes to improve their experience.
Regular Monitoring: Check the Users tab regularly to spot emerging trends, new user segments, or changing behavior patterns.
Balance Quantitative and Qualitative: Pair user metrics with qualitative feedback (surveys, support tickets) for a complete understanding.
Conclusion
The Users tab in Rybbit's Behavior Analytics transforms raw traffic data into human-centered insights. By understanding who your users are, how they behave, and what drives their engagement, you can build a better product and marketing strategy.
Start by exploring your recent users, identify your most engaged and valuable users, and use those patterns to guide your optimization efforts. Combined with session analysis and event tracking, user data gives you a complete picture of how people interact with your website.
Additional Resources: