How to Use the SourceLoop Anonymous Visitors View

The Visitors view is the other half of SourceLoop’s Contacts page, everyone who has come to your site but hasn’t converted yet. No email, no name, no phone number, just an anonymous browser, its sessions, and the attribution attached to those sessions.

It’s the right view for diagnosing top-of-funnel performance: are paid clicks coming in but not converting, is one campaign driving unusually engaged anonymous visitors, are organic visitors browsing deeply but bouncing without filling a form.

Open it from the left sidebar of the Contacts page, Visitors -> All visitors.

What the Visitors view answers

In one screen:

• How many anonymous visitors arrived in a date range, and from which channels
• How deeply they engaged (sessions, pageviews, an engagement bucket)
• Where they came from geographically, on what device, in what browser
• Their first-touch and last-touch attribution, even though they haven’t converted
• Their full per-visitor journey, every page they viewed, every ad they clicked

Step 1: Pick your date range and filters

Same controls as the Leads view:

1. Date range — defaults to the last 30 days
2. Column header filter — quick filter per column (dropdown for Channel / Device / Country; text input for everything else)
3. Filter builder — multi-condition filter across any dimension
4. Column visibility menu — toggle which columns appear

The page-level filters at the top apply across both Leads and Visitors views, so swapping between them keeps your filter context.

Step 2: Read the row

Each row is one anonymous visitor (one unique browser, cookie-based). The default columns:

Column	What it shows
Visitor	Either “Anonymous” with an incognito-style avatar, or the name / email if SourceLoop has captured any identifying detail short of a full conversion.
Engagement	Highly / Moderately / Slightly active, with a visual bar. Derived from session count + pageview count.
First seen	When the visitor first arrived (relative, e.g., “2 days ago”).
Last seen	When their most recent session ended.
Country	Country with flag emoji (from the converting session’s IP).
City	City from the same.
Pageviews	Total page loads across all sessions.

Step 3: Read the attribution columns

Same first-touch / last-touch column pairs as the Leads table:

First touch	Last touch	Meaning
First Channel	Latest Channel	Paid Search, Organic Social, Direct, etc.
First Source	Latest Source	The utm_source value
First Medium	Latest Medium	The utm_medium value
First Campaign	Latest Campaign	The utm_campaign value
First Term	Latest Term	Search term
First Content	Latest Content	The utm_content value (hidden by default)
First Landing Page	Latest Landing Page	URL of the first arrival and the most recent arrival

For a visitor who has only had one session, First and Latest match. For repeat visitors, the two diverge, useful for spotting “first arrived via Paid Search, came back via Direct” patterns.

Step 4: Read the technical columns

Column	What it shows
Device	Desktop, Mobile, or Tablet
OS	Operating system (hidden by default)
Browser	Browser name (hidden by default)

Toggle the hidden columns via the column visibility menu when you need them.

What you won’t see here (compared to the Leads view)

The Visitors view is intentionally stripped of every identified-contact field:

• No name, email, phone, or company
• No status, qualified flag, lead score, expected revenue, or revenue
• No conversion type (because there’s no conversion yet)
• No click IDs in the table (still tracked underneath, visible in the journey drawer)
• No inline editing — the view is read-only

The moment a visitor identifies themselves (submits a form, books a meeting, starts a chat with an email, pays), they’re promoted to the Leads view and disappear from here.

Step 5: Open the journey drawer

Click any row. The right-side drawer opens, the same drawer the Leads table uses, in read-only mode.

For an anonymous visitor, the drawer shows:

• Last Touch Attribution and First Touch Attribution sections, exactly as for an identified lead
• Personal Information — mostly empty for an anonymous visitor; populated as soon as identifying data lands
• Technical Information — browser, device, OS
• Journey timeline on the right side, every session the visitor has had, expanded into individual events: page views, ad clicks, custom events, scroll milestones, video plays, form starts (without submissions), etc.

The journey timeline is what makes this view valuable. You can see the pages a Paid Search visitor browsed before bouncing, the ads a return visitor clicked, the videos a high-engagement anonymous visitor watched, all of it, even without a conversion.

Step 6: Spot the patterns that matter

A few useful reading patterns:

High engagement, no conversion → visitors are getting interested but the path to convert isn’t clear. Look at their last viewed page and check the CTA placement and copy. Click their row to see the journey timeline; did they look at the pricing page and bounce?

Specific campaign driving lots of unconverted visitors → filter Latest Campaign = “your campaign name”. If the volume is high but no one converts, the campaign is targeting the wrong audience, the landing page is wrong, or the CTA is too far below the fold.

Return-visitor traffic from Direct after Paid Search → indicates real interest. These are the visitors most likely to convert next; consider a retargeting campaign that catches them on their third visit.

High organic traffic from a specific country with zero conversions → either you’re not localised for that market, or your form / payment flow is failing for that geo (currency, language, payment method). Drill into a journey to confirm.

Step 7: Export to CSV

Same Export button, top-right. The CSV includes every visible column plus full attribution per visitor, one row per browser.

Typical exports:

• Audience upload to ad platforms — export, hash, and upload as a custom audience to retarget high-engagement non-converters
• Top-of-funnel quality check — export by Latest Channel to compare engagement metrics across paid vs organic sources
• Bounced-campaign analysis — filter to a campaign with high cost but no Leads, export, and review session-by-session in a spreadsheet

What’s next

• See identified leads with full revenue and lifecycle data: Contacts (Leads) table
• Slice the same data by channel rather than per-visitor: Traffic dashboard
• See pre-conversion page sequences in aggregate: Paths dashboard
• Compare attribution credit across models: 7 Types of Attribution Models