Visitors and Journeys — How Captivar Tracks Behavior

Most analytics tools show you aggregates — 12,400 visitors, 4,300 sessions, 230 leads. Aggregates are useful but they hide the thing you actually need to know to fix a site: what does a typical visit look like, and what does a converting visit look like? Captivar’s Visitors and detail pages exist to answer that question.

The visitor model

Before the page makes sense, three definitions worth getting right.

A visitor is a unique person identified by a long-lived cookie. The cookie is set by the tracker on the first page load and persists for 12 months. A visitor who comes back next week is still the same visitor.

A session is one continuous visit by a visitor. Sessions end after 30 minutes of inactivity — close the tab and come back two hours later, that’s a new session. Same visitor, new session.

An identified visitor is one who has given the site their contact info — through a form, through chat, through a booking. Before that moment they’re known only as a cookie ID, an approximate location, and a device. After identification, every past session retroactively links to their name and email.

The Visitors page shows all of them, identified and anonymous, with controls to filter for what you actually want to look at.

What the Visitors page shows

Open the Visitors page from the sidebar. The page is a paginated table with one row per visitor.

Columns from left to right:

• Visitor — name if identified, anonymous ID otherwise. Identified rows show a small badge.
• Country and city — derived from IP geolocation. Reasonably accurate at country level, less so at city level.
• Device — desktop / mobile / tablet plus the OS.
• Source — what channel they arrived from. Direct, organic search, paid search, social, referral, email.
• First seen — when their first session started.
• Last seen — when their most recent session ended.
• Sessions — total session count across all time.
• Pages — total page views across all time.
• Time on site — sum across sessions.
• Status — anonymous, identified, lead (made it to the pipeline), customer (closed_won).

Sort by any column. Default sort is Last seen descending — most recent activity at the top, useful for the operational “who’s been active today” view.

Filtering to what matters

Above the table, a filter bar with the controls that turn the dataset from “everyone” into “the people you actually want to look at.” The filters that get the most use:

• Status — identified-only is the single most powerful filter. Strips away anonymous browsing and leaves only people you can contact.
• Source — filter to one channel to see what visitors from “organic” or “paid” look like. Often surprises agencies — paid visitors may be staying twice as long but converting half as much.
• Country — useful for clients with a regional focus. Hide anything outside the target market.
• Time on site — filter to visitors who spent over X minutes. These are your engaged audience.
• Returning vs first-time — returning visitors convert at much higher rates; worth segmenting separately.

Filters stack. Combining identified + source: organic + last seen this week gives you the warm list of recent organic visitors to follow up with.

The visitor detail page

Click any row. The detail page is where the real signal lives.

The detail page has three sections, top to bottom.

The header

A summary of who they are. Name (or anonymous ID), all contact info we have, total sessions, total pages, time on site, and the source they first arrived from. If the visitor became a lead, the lead status is shown here too with a link to the lead pipeline card.

If the visitor has chatted with the AI receptionist, you’ll see a chat transcript link. If they submitted a form, you’ll see the submission. If they booked, the booking shows here with its status. Everything tied to this person is reachable from this header.

The journey timeline

The middle of the page. A chronological list of every session this visitor has ever had with the site.

For each session, you see:

• The session date and time
• How they arrived (direct, the specific UTM if there was one, the referrer URL)
• How long the session lasted
• Every page they visited in order, with time spent on each
• Any custom events that fired (clicks the site explicitly tracked)
• Engagement signals — scroll depth, exit page

This is the part agencies often look at first when something feels off about a site. Patterns become visible fast:

• Every visitor lands on the homepage and bounces. Means the homepage is the problem — copy, design, or load speed.
• Visitors hit the homepage, click to “Services,” then leave. Means Services is failing. Read it like a prospect.
• Identified visitors all touched a specific page before converting. That page is your secret weapon — promote it harder.
• Visitors return three times before converting. The site has a long consideration cycle. Plan retargeting accordingly.

The journey timeline does the thing that aggregate analytics can’t: it lets you see the actual path, not just the destination.

Activity log

Below the journey, an activity log of every interaction — clicks on tracked buttons, form submissions, chat messages exchanged, booking actions. Read like a transcript of the visitor’s full history with the site.

For identified visitors who converted via chat, the entire conversation is here. You can read every back-and-forth between the visitor and the receptionist — what they asked, how the receptionist answered, what the visitor decided. This is gold for two reasons: it shows you what the receptionist is doing well, and it shows you the questions you should preempt with better website copy or better knowledge base content.

Anonymous vs identified — the practical difference

Captivar tracks anonymous visitors too, but the value of an anonymous visitor is fundamentally different from an identified one.

Anonymous visitors are useful for understanding traffic patterns, content performance, and channel quality. They show up in counts, in funnel charts, in source breakdowns. You cannot contact them, you cannot follow up, you cannot retarget through Captivar — they’re a number in the analytics view, no more.

Identified visitors are useful for everything anonymous visitors are, plus actual revenue work. You can email them, call them, see their full history, and place them in your pipeline. One identified visitor is worth more than a thousand anonymous ones from a “what do I do tomorrow” perspective.

The Catch Rate metric, in essence, measures how good a site is at moving people from the first column to the second. Higher Catch Rate = more identified visitors per anonymous one. Lower = the site is busy but isn’t capturing.

A note on privacy

Captivar’s tracking is cookie-based for visitor identification, IP-based for geolocation only. We do not run device fingerprinting, we do not capture mouse movements or keystrokes, we do not record session video.

What we do capture is documented and reviewable: pages visited, time spent, scroll depth, source attribution, device, browser, country, approximate city. Anything the visitor explicitly provides via form or chat is also stored — but only what they typed, never what they were thinking about typing.

For most regions this stays inside the bounds of “legitimate interest” without requiring a cookie banner. For EU regions or specific compliance requirements (HIPAA, etc.) we recommend adding a consent banner to the client’s site, even if it’s just a cookie notice. Captivar respects standard Do Not Track headers and IAB TCF consent strings if the client’s site provides them.

What happens next

You now know how to read individual visitor behavior, journey by journey. The third piece of the analytics picture is understanding which traffic channels are doing the work — which campaigns, which referrals, which search terms are bringing in the visitors who actually convert. That’s the Catch Rate by source, and it’s covered next.