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User Activity Monitoring

⚠️ Not Yet Implemented (as of 2026-04-16)

This user story is out of scope for the MVP/POC and not yet implemented. The acceptance criteria below describe the target Drop 1 Beta experience.

What exists today: - Raw session data in the sessions table (login timestamps, device info, last-seen) — can be aggregated for basic metrics. - email_logs table captures delivery, open, and click events per email.

What's missing: - Aggregation/reporting service to roll session + audit data into dashboards. - Front-end analytics UI (logins over time, active users, session durations, feature usage). - CSV/PDF export. - Alert/anomaly detection pipeline. - Dependency on the audit-log write path (see compliance-audit-reporting.md) for any metrics beyond sessions and emails.

Roadmap: see Task 24 — Logging & Tracking Reconciliation for the phased implementation plan.

Overview

This user story covers the functionality for tracking and displaying user activity patterns and platform usage statistics, enabling staffing company administrators to understand how the platform is being used and identify usage trends.

User Stories

US-RA-01: Monitor User Activity Patterns

As a staffing company administrator,
I want to monitor user activity patterns and platform usage statistics,
So that I can understand how the platform is being used, identify popular features, and optimize the user experience.

Acceptance Criteria

Scenario 1: Viewing User Login Activity 

Given I am logged in as a staffing company administrator
When I navigate to the user activity monitoring section
Then I should see a visualization of user logins over time
And I should see metrics on active users, session durations, and login frequency
And I should be able to filter the data by time period (daily, weekly, monthly)

Scenario 2: Tracking Feature Usage 

Given I am in the user activity monitoring section
When I select the feature usage tab
Then I should see statistics on which features are most frequently used
And I should see a breakdown of feature usage by user role
And I should see trend data showing changes in feature usage over time

Scenario 3: Identifying Most Active Users 

Given I am in the user activity monitoring section
When I select the user activity tab
Then I should see a list of users sorted by activity level
And I should see detailed metrics for each user's platform usage
And I should be able to drill down into individual user activity patterns

Scenario 4: Setting Up Activity Alerts 

Given I am in the user activity monitoring section
When I configure activity alerts
Then I should be able to set thresholds for unusual activity patterns
And I should be able to specify which activity metrics trigger alerts
And I should be able to configure notification methods for alerts

Scenario 5: Filtering Activity Data 

Given I am viewing user activity data
When I apply filters to the data
Then I should be able to filter by user, time period, and activity type
And the visualizations should update to reflect the filtered data
And I should be able to save filter configurations for future use

Scenario 6: Exporting Activity Data 

Given I am viewing user activity data
When I click the export button
Then I should be able to export the activity data for further analysis
And I should be able to select the format (CSV, Excel)
And I should be able to choose whether to export all data or only filtered data

Scenario 7: Viewing Activity Trends 

Given I am in the user activity monitoring section
When I select the trends analysis view
Then I should see visualizations of activity patterns over time
And I should see comparisons between current and previous periods
And I should see predictions of future activity based on historical patterns

Dependencies

  • User Management System
  • Audit Logging
  • Data Visualization Components

Notes

  • Activity monitoring should respect user privacy and comply with data protection regulations
  • The system should optimize performance when analyzing large volumes of activity data
  • Historical activity data should be retained according to data retention policies
  • The interface should make it easy to identify patterns and anomalies in user activity