How Analytics Work in Self

Self Analytics is designed to answer a practical question: is your page only getting clicks, or is it actually creating attention and trust with recruiters?

At a big-picture level, the dashboard combines five core signals in one view: total views, unique viewers, sessions, average time on page, and average scroll depth. Together, they show both reach and quality of attention.

You also get context to understand where performance comes from. The traffic chart shows movement over time, while breakdowns by source, device, and country help you identify which channels are bringing the right audience.

The most important signal for CV performance is scroll depth. A resume page is a narrative, and if people stop early, key sections like projects, achievements, or final call-to-action may never be seen.

That is why Self highlights scroll depth with a dedicated funnel and drop-off analysis between stages (25%, 50%, 75%, and 100%). This is a rare capability in CV builders, and it gives you direct evidence of whether recruiters are reaching the end of your profile.

When you detect major drop-off, you can iterate with purpose: tighten the opening summary, shorten dense sections, improve headings, and move your strongest proof earlier. Small structure changes often produce better completion rates.

The goal is simple: move from guessing to learning. With clear analytics, your CV page becomes an asset you can continuously improve based on real recruiter behavior, not assumptions.