Scroll Depth
A metric that measures how far down a page users scroll, typically reported as percentage thresholds like 25%, 50%, 75%, and 100%, revealing how much of the page content users actually consume.
Scroll depth tracking records how far users scroll on each page, providing insight into content consumption patterns that page view counts alone cannot reveal. A page with a million views but only 10% of users scrolling past the first section is fundamentally different from one where 80% of users reach the bottom.
For growth teams, scroll depth is essential for optimizing content-heavy pages, landing pages, and long-form product pages. AI can analyze scroll depth patterns across pages and user segments to identify where attention drops, predict optimal content length, and recommend content placement strategies. Growth engineers should implement scroll depth tracking at meaningful content boundaries rather than arbitrary percentages, measuring whether users reach key messages, calls-to-action, and conversion elements. Combining scroll depth with time-on-page creates a content engagement score that distinguishes active reading from passive scrolling. The most actionable analysis examines scroll depth in relation to conversion: if the primary CTA sits at 60% scroll depth and most users stop scrolling at 40%, the solution is either more compelling content above the CTA or repositioning the CTA higher on the page.
Related Terms
Event Tracking
The practice of recording specific user interactions within a digital product, such as clicks, form submissions, page views, and feature usage, as structured data events that can be analyzed to understand user behavior.
Event Taxonomy
A structured naming convention and classification system for analytics events that ensures consistency, discoverability, and usability of tracking data across teams, platforms, and analysis tools.
Funnel Analysis
The process of tracking and measuring user progression through a defined sequence of steps toward a conversion goal, identifying where users drop off and quantifying the conversion rate between each stage.
Conversion Rate Analytics
The systematic measurement and analysis of the percentage of users who complete a desired action out of the total who had the opportunity, applied across multiple conversion points throughout the user journey.
Drop-Off Rate
The percentage of users who leave a process or sequence at a specific step without completing the next step, the inverse of step-level conversion rate, used to identify friction points in user flows.
Cohort Analysis
A technique that groups users by a shared characteristic or experience within a defined time period and tracks their behavior over subsequent periods, revealing how user behavior evolves and differs across groups.