Clicky
Clicky is a hosted web-analytics service centered on real-time, per-visitor reporting: it shows current activity and individual visitor sessions with their actions, alongside standard aggregate reports. Its emphasis on live, visitor-level views distinguishes it from tools that prioritize processed, aggregate dashboards, and shapes its data and privacy considerations.
What this means
Clicky leans into real-time analytics: a live view of current visitors and a per-visitor breakdown of the actions in a session. Rather than waiting for processed daily reports, you can watch traffic as it happens and drill into individual sessions.
It also offers the usual aggregate reports (top content, sources, and so on), but the live, visitor-level orientation is its defining trait.
How the model reads
The real-time, individual-session model is useful during launches, campaigns, or incident watching, where immediacy beats polished aggregation. As with any tool that shows individual activity, bots and crawlers appear in live views, so filtering and summaries still matter for conclusions.
Feature specifics and terminology should be confirmed against current documentation.
- Real-time view of current visitors
- Per-visitor session and action detail
- Standard aggregate reports as well
- Live views include bots without filtering
How it appears in analytics and logs
Clicky surfaces live and visitor-level activity. Reading it means watching current sessions and actions, which is good for immediacy but still requires bot awareness, since live views include automated traffic.
Diagnostic use case
Use Clicky when real-time monitoring and per-visitor session detail matter — for example watching live traffic during a launch or campaign — alongside conventional summaries.
What WebmasterID can help detect
Clicky's live visitor view answers 'what is happening now'; WebmasterID adds first-party traffic intelligence and bot separation so the live human share is distinguishable from bots.
Common mistakes
- Reacting to live spikes before filtering bots.
- Reading per-visitor detail as fully de-identified.
- Comparing real-time counts to processed reports directly.
Privacy and accuracy notes
Per-visitor, real-time session detail is a granular data model, so consent, retention, and any identifier use deserve review like any client-side analytics. This is educational, not legal advice.
Related pages
- StatCounter
StatCounter is one of the older hosted web-analytics services, built around a visitor log: a chronological record of individual page-load hits with referrer, entry/exit pages, and basic environment details. Its model leans toward inspecting recent individual visits rather than only aggregate dashboards, which shapes how it is read and its privacy considerations.
- Chartbeat
Chartbeat is a real-time analytics product aimed at publishers and newsrooms. Its model centers on concurrent readers and engaged time — how many people are reading right now and how actively — rather than just cumulative pageviews. That editorial focus shapes its metrics, its real-time dashboards, and how teams use it to make in-the-moment content decisions.
- Bot traffic in analytics: filtering it out
Bots — crawlers, scrapers, monitors, scanners — generate requests that, unfiltered, inflate pageviews and distort every metric. Client-side analytics often misses bots (many do not run JavaScript) or miscounts the ones that do. Server-side classification at ingest is the reliable way to keep bot traffic out of human reports.
- Bot intelligence
Distinguish live human traffic from bots.
Sources and verification notes
- Clicky — Help / documentationPublic help describes real-time and visitor-level reporting; confirm current feature names against the docs.
Last reviewed 2026-06-24. Facts are checked against primary/official sources where available; uncertain specifics are marked “Data not yet verified” rather than guessed.