How It Works

AttributionHub works in four stages on every page load: detect, classify, store, and populate.

The Attribution Pipeline

Stage 1: Detect

When a page loads, the script reads:

• URL parameters — utm_source, utm_medium, utm_campaign, utm_content, utm_term, and any custom fields
• Click IDs — gclid (Google), msclkid (Microsoft), fbclid (Meta), ttclid (TikTok), li_fat_id (LinkedIn), and more
• Referrer — the document.referrer URL
• Landing URL — the current page URL and path

Stage 2: Classify

Using the detected signals, the script classifies the visit into one of 20+ channel groups using a priority-based rule system:

1. Check for explicit channel signals (e.g., utm_medium=cpc with a search source = “Paid Search”)
2. Check for click IDs (e.g., gclid present = likely Google Ads)
3. Match the referrer against known domains (200+ search engines, 80+ social networks, 18+ AI assistants)
4. Fall back to medium-based classification
5. Default to Direct (no referrer, no UTMs) or “Referral” (unknown external referrer)

Stage 3: Store

The classified data is saved as a touch snapshot in localStorage. Three snapshots are maintained:

Additional stored values:

• ah_visitor_id — a unique UUID generated on the first visit
• ah_touch_count — number of non-direct visits (incremented only on external traffic)

Stage 4: Populate

The script discovers forms on the page and fills matching hidden fields with attribution data. See Conversion Tracking for the full form population architecture, supported platforms, and field mapping details.

Touch Snapshot Lifecycle

Here is how the three touch types behave across multiple visits:

Visit 1: Google Ads click
  first      = { channel: "Paid Search", source: "Google" }
  latest     = { channel: "Paid Search", source: "Google" }
  latestND   = { channel: "Paid Search", source: "Google" }

Visit 2: Direct (typed URL)
  first      = { channel: "Paid Search", source: "Google" }  -- unchanged
  latest     = { channel: "Direct",      source: "Direct" }  -- updated
  latestND   = { channel: "Paid Search", source: "Google" }  -- preserved

Visit 3: LinkedIn organic post
  first      = { channel: "Paid Search", source: "Google" }  -- unchanged
  latest     = { channel: "Organic Social", source: "LinkedIn" }
  latestND   = { channel: "Organic Social", source: "LinkedIn" }

Visit 4: Direct (bookmark)
  first      = { channel: "Paid Search", source: "Google" }  -- unchanged
  latest     = { channel: "Direct", source: "Direct" }       -- updated
  latestND   = { channel: "Organic Social", source: "LinkedIn" } -- preserved

Direct visits update the latest touch but intentionally do not overwrite the first or latest-non-direct touches, preserving the original marketing source.

Deep Dives