If you have compared data between two analytics tools, the numbers do not match. This is not a bug -- it is fundamental to how web analytics works.

Common Reasons for Discrepancies

Different Tracking Methods

JavaScript-based tools miss blocked visitors; server-side tools capture bot traffic.

Different Session Definitions

One tool may restart sessions after 30 minutes of inactivity; another after 60 minutes.

Different User Identification

Cookie-based tools recognize returning visitors; cookieless tools cannot across days.

Different Bot Filtering

Each tool has its own approach to identifying and filtering bots.

Different Blocking Rates

Google Analytics is blocked by 30-60% of privacy tools. Privacy-focused tools are blocked at much lower rates.

Tools requiring consent only track visitors who opt in, creating a proportional data gap.

What to Do About It

Pick One Source of Truth

Choose one tool as your primary data source and base all decisions on it.

Focus on Trends, Not Absolutes

Whether traffic is going up or down matters more than exact numbers.

Understand Each Tool's Bias

Know what your tool is likely to undercount or overcount.

Use Tools for Their Strengths

Web analytics for traffic trends, ad platforms for campaign metrics, ecommerce platforms for sales data.

Avoid Combining Numbers

Adding visitors from different tools gives you a meaningless number with overlap and methodology conflicts.

The Bottom Line

No analytics tool provides a perfect picture. Choose one that aligns with your values, understand its limitations, and make decisions based on consistent trend data.