Web Analytics Tool - Problem Statement

Overview

Design a web analytics platform similar to Google Analytics that can track user behavior, page views, events, and conversions across millions of websites. The system should provide real-time reporting, historical analysis, and actionable insights while handling billions of events daily with high accuracy and low latency.

Functional Requirements

Core Tracking Features

Page View Tracking: Record every page view with URL, referrer, timestamp
Event Tracking: Custom events (clicks, form submissions, video plays, downloads)
User Session Tracking: Group user activities into sessions with session duration
User Identification: Track anonymous users via cookies, authenticated users via IDs
E-commerce Tracking: Track transactions, revenue, product views, cart actions
Campaign Tracking: UTM parameters for marketing campaign attribution

Real-time Analytics

Live Dashboard: Real-time visitor count and active page views
Real-time Events: Stream of events happening across all tracked sites
Active Users: Current users on site with geographic distribution
Real-time Conversions: Track goals and conversions as they happen
Alert System: Real-time alerts for traffic spikes or anomalies
Live Comparison: Compare current traffic to historical averages

Historical Reporting

Traffic Reports: Page views, unique visitors, bounce rate, session duration
Audience Reports: Demographics, interests, technology, location
Acquisition Reports: Traffic sources, campaigns, referrals, search keywords
Behavior Reports: Site content, landing pages, exit pages, site search
Conversion Reports: Goals, funnels, e-commerce transactions
Custom Reports: User-defined dimensions and metrics

Data Visualization

Interactive Dashboards: Customizable dashboards with drag-and-drop widgets
Charts and Graphs: Line charts, bar charts, pie charts, heat maps
Geographic Maps: Visitor distribution on world and country maps
Funnel Visualization: Visual representation of conversion funnels
Cohort Analysis: User retention and behavior over time
Comparison Views: Compare time periods, segments, or campaigns

Segmentation and Filtering

User Segments: Create segments based on behavior, demographics, technology
Advanced Filters: Filter reports by multiple dimensions and conditions
Custom Dimensions: Define custom attributes for tracking
Custom Metrics: Calculate custom metrics from tracked data
Saved Segments: Reusable segment definitions across reports
Dynamic Segments: Real-time segment evaluation

Integration Features

JavaScript SDK: Lightweight tracking library for websites
Mobile SDKs: Native SDKs for iOS and Android apps
Server-side Tracking: API for backend event tracking
Data Import: Import offline conversion data, CRM data
Data Export: Export raw data to BigQuery, data warehouses
Third-party Integrations: Google Ads, Search Console, CRM systems

Non-Functional Requirements

Performance Requirements

Event Ingestion Latency: <100ms from client to data pipeline
Real-time Dashboard: Update within 5 seconds of event occurrence
Report Generation: Standard reports load within 3 seconds
Custom Report Query: Complex queries complete within 10 seconds
Dashboard Load Time: Initial dashboard load within 2 seconds
API Response Time: 95th percentile <500ms for API queries

Scalability Requirements

Tracked Websites: Support 10+ million websites
Daily Events: Process 100+ billion events per day
Peak Throughput: Handle 5 million events per second during peaks
Concurrent Users: Support 1 million concurrent dashboard users
Data Retention: Store detailed data for 14 months, aggregated data indefinitely
Query Concurrency: Handle 100,000+ concurrent report queries

Reliability Requirements

System Uptime: 99.9% availability for tracking and reporting
Data Accuracy: 99.95%+ accuracy in event tracking and reporting
Data Loss: <0.01% event loss rate under normal conditions
Disaster Recovery: <2 hours RTO, <15 minutes RPO
Tracking Resilience: Continue tracking even if analytics backend is down
Graceful Degradation: Serve cached reports during partial outages

Data Quality Requirements

Bot Filtering: Automatically filter bot traffic and spam
Duplicate Detection: Deduplicate events from multiple tracking calls
Data Validation: Validate event data format and values
Sampling Accuracy: Maintain statistical accuracy when sampling large datasets
Attribution Accuracy: Correct attribution of conversions to sources
Session Stitching: Accurately group events into user sessions

Privacy and Compliance

GDPR Compliance: Support data deletion, anonymization, consent management
CCPA Compliance: Honor do-not-sell requests and data access rights
Cookie Consent: Respect user cookie preferences and consent
IP Anonymization: Option to anonymize IP addresses
Data Retention Policies: Configurable data retention periods
User Opt-out: Honor do-not-track and opt-out mechanisms

Scale Constraints

Data Volume

Events per Day: 100 billion events across all tracked sites
Average Event Size: 2KB per event (including metadata)
Daily Data Ingestion: 200TB of raw event data per day
Storage Growth: 6PB per month of raw and processed data
Historical Data: 100PB+ of historical analytics data
Active Websites: 10 million actively tracked websites

Traffic Patterns

Peak Hours: 3x average traffic during business hours in major regions
Seasonal Spikes: 10x traffic during Black Friday, major events
Geographic Distribution: 40% Americas, 30% Europe, 20% Asia, 10% other
Mobile vs Desktop: 60% mobile, 40% desktop traffic
Real-time Users: 50 million concurrent active users being tracked
Dashboard Users: 1 million concurrent users viewing reports

Query Patterns

Real-time Queries: 10,000 queries per second for live dashboards
Historical Queries: 50,000 queries per second for standard reports
Custom Queries: 5,000 complex ad-hoc queries per second
Data Export: 1,000 large data export jobs per hour
API Calls: 100,000 API requests per second
Report Scheduling: 10 million scheduled reports per day

Technical Constraints

Client-side Tracking

JavaScript Bundle Size: <50KB for tracking library
Page Load Impact: <100ms impact on page load time
Browser Compatibility: Support all modern browsers and IE11+
Mobile Performance: Minimal battery and data usage impact
Offline Tracking: Queue events when offline, send when reconnected
Cross-domain Tracking: Track users across multiple domains

Data Processing

Stream Processing: Real-time event processing with <5 second latency
Batch Processing: Hourly and daily aggregation jobs
Data Enrichment: Geo-location, device detection, bot filtering
Sessionization: Group events into sessions with 30-minute timeout
Attribution Modeling: Multi-touch attribution across channels
Anomaly Detection: Detect traffic spikes and unusual patterns

Storage and Querying

Hot Data: Last 7 days in fast storage for real-time queries
Warm Data: 8-90 days in medium-speed storage for recent reports
Cold Data: 90+ days in archival storage for historical analysis
Query Performance: Sub-second queries on billions of records
Aggregation: Pre-aggregate common metrics for fast reporting
Sampling: Intelligent sampling for large datasets while maintaining accuracy

Edge Cases and Constraints

Tracking Challenges

Ad Blockers: 30% of users have ad blockers that may block tracking
Cookie Restrictions: Safari ITP, Firefox ETP limiting cookie lifetime
Single Page Apps: Track route changes in SPAs without page reloads
Cross-device Tracking: Link user activity across multiple devices
Bot Traffic: Filter out crawlers, scrapers, and malicious bots
Duplicate Events: Handle duplicate tracking calls from client retries

Data Quality Issues

Missing Data: Handle incomplete events or missing required fields
Invalid Data: Validate and sanitize user-provided data
Time Synchronization: Handle client clock skew and timezone issues
Session Boundaries: Accurately determine session start and end
Referrer Spoofing: Detect and handle fake referrer data
Traffic Inflation: Detect and prevent artificial traffic inflation

Performance Challenges

Report Cardinality: Handle reports with millions of unique dimensions
Long Tail Queries: Optimize for infrequent but complex queries
Data Skew: Handle uneven data distribution across partitions
Hot Partitions: Manage high-traffic websites causing hot spots
Query Timeouts: Handle long-running queries gracefully
Resource Contention: Balance real-time and batch processing resources

Success Metrics

Tracking Accuracy

Event Capture Rate: 99.95%+ of events successfully tracked
Data Accuracy: <0.1% discrepancy in reported metrics
Bot Filtering Accuracy: 99%+ accuracy in bot detection
Session Accuracy: 98%+ correct session grouping
Attribution Accuracy: 95%+ correct conversion attribution
Sampling Error: <2% error when using sampled data

Performance Metrics

Tracking Latency: 95th percentile <100ms
Real-time Latency: 95th percentile <5 seconds
Report Load Time: 95th percentile <3 seconds
Query Success Rate: 99.9%+ queries complete successfully
System Uptime: 99.9%+ availability
API Latency: 95th percentile <500ms

User Engagement

Active Websites: 10 million websites actively sending data
Dashboard Users: 5 million monthly active users
Report Views: 1 billion report views per month
API Usage: 10 billion API calls per month
Data Export: 1 million data exports per month
Custom Reports: 50 million custom reports created

Business Metrics

Customer Retention: 95%+ annual retention rate
Feature Adoption: 70%+ adoption of new features within 3 months
Support Tickets: <0.5% of users require support monthly
Infrastructure Cost: <$0.001 per tracked event
Query Cost: <$0.01 per report query
Revenue per Customer: Increase through premium features and higher tiers

This problem statement establishes the foundation for designing a comprehensive web analytics platform that can handle massive scale while providing accurate, real-time insights to millions of users worldwide.