DACT (Dark Agentic Commerce Traffic)
Also known as: Dark Agentic Commerce Traffic
AI-driven shopper traffic that GA4 and legacy analytics cannot identify, silently bucketing as 'Direct.' Typical brand gap: 4-8× between measured and actual AI revenue.
DACT - Dark Agentic Commerce Traffic - is the AI-driven traffic your Google Analytics 4 can't see. When a shopper taps a product card in ChatGPT/Gemini/Perplexity/Rufus/Copilot/Claude, the referrer header is stripped by the AI surface. GA4 looks at an empty referrer and defaults to "Direct."
The consequence: brands undermeasure their AI channel by 4-8× (median across our customer base). MyMuse's ratio was 7.05× - GA4 reported ₹11.5K/mo; the real number was ₹81.2K/mo.
The fix is a server-side attribution layer using three parallel signals: surface fingerprinting (JA3 hash + UA + IP cluster + timing), query-parameter negotiation via protocol contracts (where available), and a dedicated JavaScript tracking pixel. Confidence-weighted combination produces a stable per-surface DACT panel.
DACT is a Layer-06 measurement instrument in the agentic commerce stack. It tells you whether shoppers are arriving; it does not on its own close the checkout or improve recommendation share.
See also
Citation Rank
Tru Commerce's flagship AI Share-of-Voice score - measures how often and where a brand appears when AI agents answer category-relevant shopper questions.
Server-side AI attribution
Server-side infrastructure that identifies AI-driven traffic without relying on the HTTP Referer header. Three-signal architecture: fingerprinting, query-param negotiation, tracking pixel.
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