Google Analytics System

Analyze website performance using Google Analytics data — covering setup, key metrics interpretation, custom reports, event tracking, and actionable optimization recommendations.

When to Use

Use this system when:

• Need to understand website traffic patterns and user behavior
• Setting up Google Analytics for a new website or app
• Building custom reports and dashboards
• Optimizing conversion funnels and user journeys

Use other analytics tools when:

• Product analytics with cohort analysis → Mixpanel or Amplitude
• Privacy-first analytics without cookies → Plausible or Fathom
• Real-time server-side analytics → custom solutions

Quick Start

GA4 Setup

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<!-- Google Analytics 4 tag -->
<script async src="https://www.googletagmanager.com/gtag/js?id=G-XXXXXXXXXX"></script>
<script>
  window.dataLayer = window.dataLayer || [];
  function gtag(){dataLayer.push(arguments);}
  gtag('js', new Date());
  gtag('config', 'G-XXXXXXXXXX');
</script>

Custom Event Tracking

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// Track button clicks
gtag('event', 'click', {
  event_category: 'engagement',
  event_label: 'cta_button',
  value: 1
});

// Track form submissions
gtag('event', 'form_submit', {
  event_category: 'conversion',
  event_label: 'signup_form',
  value: 1
});

// Track purchases
gtag('event', 'purchase', {
  transaction_id: 'T_12345',
  value: 49.99,
  currency: 'USD',
  items: [
    { item_id: 'SKU_123', item_name: 'Pro Plan', price: 49.99 }
  ]
});

GA4 API Query

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from google.analytics.data_v1beta import BetaAnalyticsDataClient
from google.analytics.data_v1beta.types import RunReportRequest, DateRange, Dimension, Metric

client = BetaAnalyticsDataClient()

request = RunReportRequest(
    property=f"properties/123456789",
    dimensions=[
        Dimension(name="date"),
        Dimension(name="sessionSource"),
    ],
    metrics=[
        Metric(name="sessions"),
        Metric(name="conversions"),
        Metric(name="bounceRate"),
    ],
    date_ranges=[DateRange(start_date="30daysAgo", end_date="today")],
)

response = client.run_report(request)
for row in response.rows:
    print(f"{row.dimension_values[0].value}: {row.metric_values[0].value} sessions")

Core Concepts

Key Metrics

Metric	Description	Healthy Range
Sessions	Total visits	Growing month-over-month
Users	Unique visitors	Growing, with returning users
Bounce Rate	Single-page sessions	40-60% (varies by type)
Avg Session Duration	Time on site	> 2 minutes
Pages per Session	Engagement depth	> 2 pages
Conversion Rate	Goal completions / sessions	2-5% (varies)

Traffic Sources

Channel	Description	Optimization
Organic Search	SEO traffic	Content, keywords, backlinks
Direct	Typed URL or bookmarks	Brand awareness
Referral	Links from other sites	Partnership, PR
Social	Social media platforms	Social content strategy
Paid Search	Google Ads, etc.	Ad optimization, ROAS
Email	Newsletter clicks	Email campaign optimization

Conversion Funnel Analysis

Landing Page (1000 visitors)
    → Product Page (600 visitors, 60% progression)
        → Add to Cart (200 visitors, 33% progression)
            → Checkout (100 visitors, 50% progression)
                → Purchase (40 visitors, 40% progression)

Overall conversion: 4%
Biggest drop-off: Product → Cart (67% drop)
Action: Optimize product page CTA and pricing display

Configuration

Parameter	Description
property_id	GA4 property identifier
data_stream	Web or app data stream
measurement_id	G-XXXXXXXXXX tag ID
events	Custom event definitions
conversions	Events marked as conversions
audiences	User segment definitions
custom_dimensions	Business-specific dimensions

Best Practices

1. Set up conversions first — define what success means before analyzing data
2. Use UTM parameters for all campaign links to track traffic sources accurately
3. Create custom events for key user actions (signup, purchase, feature usage)
4. Build dashboards for daily monitoring — don't dig through raw data every time
5. Segment your data — overall averages hide insights; compare by source, device, and user type
6. Set up alerts for significant changes — traffic drops, conversion rate changes, error spikes

Common Issues

Data discrepancy with other tools: GA uses session-based counting; other tools may use event-based. Ad blockers prevent ~10-15% of users from being tracked. Check timezone and filter settings.

Low conversion tracking: Verify event firing with GA4 DebugView. Ensure conversion events are properly marked. Check for cross-domain tracking issues on multi-domain setups.

Bounce rate too high: Check page load speed (Core Web Vitals). Ensure content matches search intent. Improve above-the-fold content and clear CTAs.