AI Traffic · Private beta — applications open

Your store, ready for the agentic web.

When a shopper clicks out of ChatGPT, Perplexity, Claude, or Gemini, they've already described what they want. Comet reads that context and loads a store tuned to the conversation — not a generic PDP.

While it depicts the merchant-facing store builder rather than the shopper experience, it's the only image that visually connects an AI chat context to a dynamically generated stor

Where this pillar is: schema + llms.txt + referral-aware landing ship today. The full ChatGPT app is in development with a small cohort of design partners. We're onboarding 5 brands per wave — deliberately.

Who this is for

If one of these is you, keep reading.

Forward-looking Head of Growth

You see AI-referral traffic in your analytics already and you know the share only goes up from here. You want to be where the puck is going — before your CMO asks about it.

AI-native ops lead

You already run paid, creator, and organic. AI traffic is the fourth channel you're trying to figure out before everyone else does.

CTO / Head of Engineering

Agentic commerce is going to be an infrastructure story. You want your stack ready for MCP, Apps in ChatGPT, and whatever the next protocol is — not bolted on later.

Why now

AI traffic is a real channel. The landing experience is stuck in 2022.

78%

of AI chatbot referral traffic comes from ChatGPT

Similarweb, 2025

growth in AI-referred traffic to Shopify stores in 2025

Shopify / Alhena benchmarks

~23×

higher conversion rate on AI-referred vs generic organic

Alhena benchmark, 2026

Deep dive

The Comet app for ChatGPT.

The novel thing. An OpenAI App that surfaces your catalogue in ChatGPT conversations, gathers intent, and pre-builds a storefront tuned to the conversation — so when the shopper clicks to buy, they land somewhere that already knows what they want.

01

Conversation

A shopper asks ChatGPT for a recommendation — "best retinol for sensitive skin under $50", "non-toxic workout gear", whatever their ask is.

02

Context gathered

Our ChatGPT app surfaces your products in the conversation. As the shopper clarifies, the app gathers intent — skin type, budget, use case, preferences.

03

Store prepared in background

While the conversation continues, Comet pre-builds a storefront tuned to the gathered context — the right products, the right copy, the right offers.

04

Hand-off on click

When the shopper clicks to buy, they don't land on your generic PDP. They land on a store built for the conversation they just had.

Beyond ChatGPT

The other agents are sending traffic too.

Perplexity already links out. Gemini is indexing. Claude ships MCP. Comet is wired for all four, with different depths today and a roadmap to parity.

Perplexity

Live in beta

Referral-aware landing. When a Perplexity answer links to your store, Comet reads the referring query + session context and serves a matched storefront.

Claude

MCP live · app in scope

MCP-native. Claude agents can browse, compare, and hand shoppers off to Comet stores via the Model Context Protocol.

Gemini

Schema live · app in scope

Schema-first. Gemini's Shopping Graph reads your catalogue via schema.org, and Comet stores surface structured data agents can actually parse.

ChatGPT

Private beta

Full OpenAI App — gathers conversation context, pre-builds the store, hands off on click. The deepest of the four integrations.

The actual moat

Agents build the stores. Agents shop the stores.

When your storefronts are objects an agent can create with a prompt, your AI-traffic strategy stops being a slide in a deck and starts being a workflow your stack runs overnight.

MCP server

Comet speaks Model Context Protocol natively. An AI agent can create, brand, and manage AI-traffic storefronts with a single prompt.

Claude: for each skincare archetype
in our intent map, spin up a
Comet store. Match products,
match copy, publish to subdomain.

REST API

For teams that want to wire Comet into their own AI pipeline — a recommendation engine, a search stack, a custom agent.

POST /api/v1/stores
{
  "intent": "retinol-sensitive-skin",
  "products": ["sku-1", "sku-2"],
  "theme": "clean-minimal"
}

Dashboard

For operators who want to design intent-to-store mappings visually — curated products per query pattern, tested and tuned over time.

Apply for private beta

Be one of the first five brands in the next cohort.

Leave your email. We review weekly and respond within 7 days.

5 brands per cohort. We prioritise DTC brands on Shopify already seeing AI-referral traffic in analytics.

FAQ

The questions AI-curious teams ask us first.

Still have questions? Contact us

The agentic web is sending traffic. Decide where it lands.

Apply for the private beta — 5 brands per cohort, weekly review.