Web Analytics

Web analytics is the process of collecting, measuring, interpreting, and applying data about user behavior on a website or application. It helps understand how people interact with a resource, which pages generate traffic and conversions, where problems arise, and how to improve website and advertising effectiveness.

What is Web Analytics?

Web analytics is a system of metrics, tools, and methods that allow tracking of user actions:

• Visits/sessions
• Traffic sources
• Clicks and scrolls
• Conversions
• On-page behavior
• Goal completions
• Interface interactions

With analytics, specialists make data-driven decisions rather than relying on assumptions.

Why Use Web Analytics?

• Assess Website Effectiveness: Understand which pages perform well and which need improvement.
• Analyze Advertising: Identify channels that deliver the best traffic, purchases, or leads.
• Optimize Conversions: Find bottlenecks where users drop off.
• Audit Interface and Usability: Analyze how users interact with site elements.
• Forecast and Plan: Model future performance and adjust strategies.

Key Web Analytics Metrics

• Traffic (sessions, visits, users)
• Traffic source/channel
• Pages per session
• Time on site
• Bounce rate
• Conversion rate (CR)
• Cost per lead (CPL)
• Customer acquisition cost (CAC)
• Revenue and profit
• Customer Lifetime Value (LTV)

Popular Tools

• Google Analytics / GA4
• Yandex.Metrica
• Google Tag Manager
• Hotjar, Microsoft Clarity (heatmaps and behavior tracking)
• Roistat, Calltouch (attribution analytics)
• CRM systems (customer and deal data)

What is Analyzed in Web Analytics?

1. Traffic and Sources: Where users come from (search, social media, ads, email, direct visits).
2. On-Site Behavior: How they navigate pages, what they view, where they click.
3. Conversions: How many people complete target actions (purchases, form submissions, registrations).
4. Sales Funnels: At which stage users drop off.
5. Content: Which articles, products, or pages attract attention.
6. Advertising Channels: Which campaigns are profitable and which are not.

Examples of Web Analytics Tasks

• Determine why high advertising costs aren’t driving conversions.
• Identify which pages most often lead to purchases.
• Pinpoint weak points in the interface.
• Improve the product through customer behavior analysis.
• Forecast future demand.
• Automate event tracking (clicks, form submissions, scrolls).

Common Web Analytics Mistakes

• Incorrectly configured goals or events.
• Lack of UTM tagging.
• Duplicate data tracking.
• Lack of segmentation.
• Analyzing only traffic without conversion analysis.
• Comparing data from different systems without adjustments.
• Making decisions without statistical significance.

Conclusion

Web analytics is the foundation of digital marketing. It helps understand how a website performs, which channels deliver results, and where to allocate resources.