Can I vibe code Google Analytics 4?

Build a full-stack, first-party e-commerce analytics event collector and reporting dashboard tailored for Shopify and web storefronts.

DATA MODEL & BACKEND:
1. Use Node.js with Fastify for high-throughput ingestion and ClickHouse as the event store.
2. Tables required:
   - events: event_id (UUID), session_id (String), anonymous_id (String), user_id (String Nullable), event_name (String - e.g., 'page_view', 'add_to_cart', 'begin_checkout', 'purchase'), timestamp (DateTime64), page_location (String), referrer (String), user_agent (String), ip_address (String), geo_country (String), properties (JSON).
   - ecom_orders: order_id (String), transaction_id (String), revenue (Decimal), currency (String), tax (Decimal), shipping (Decimal), coupon (String), items (Nested JSON: item_id, item_name, price, quantity, category).
3. Setup an HTTP ingestion endpoint `/api/v1/collect` that accepts CORS POST requests with batched JSON payloads.
4. Implement IP-to-country lookup and user-agent parsing (device type, browser, OS) before async streaming inserts into ClickHouse.

CLIENT SDK (JS SNIPPET):
1. Write a zero-dependency JS browser tracking snippet (< 5KB) that attaches to `window.tracker`.
2. Automatic tracking: capture page views, SPA route changes, outbound link clicks, and time-on-page metrics.
3. Explicit e-commerce tracking API:
   - `tracker.trackAddToCart({ itemId, name, price, quantity, currency })`
   - `tracker.trackCheckout({ cartTotal, itemCount, items })`
   - `tracker.trackPurchase({ orderId, total, tax, shipping, items })`
4. Store persistent `anonymous_id` in `localStorage` and `session_id` (expires after 30m inactivity) in `sessionStorage`. Fallback to HTTP-only first-party cookie if web storage is blocked.

DASHBOARD & REPORTS (Next.js / Tailwind / Tremor):
1. Real-time overview: Active users in last 30 mins, pageviews/sec, current top active pages, purchase revenue stream.
2. E-commerce Conversion Funnel: Visual multi-step funnel showing Sessions -> Product Views -> Add to Cart -> Begin Checkout -> Purchase, with drop-off percentages calculated dynamically via ClickHouse funnels (`windowFunnel`).
3. Acquisition & Attribution: Source/Medium/Campaign reporting using standard UTM parameters parsed from `page_location` with First-Touch and Last-Touch attribution models applied to purchase events.
4. Data Export: Raw JSON/CSV export API and BigQuery streaming simulator to output daily event batches.

OUT OF SCOPE:
Do not implement cross-device Google Signal tracking, ad network retargeting pixels, or ML-driven automated insights. Focus exclusively on 100% accurate, unsampled first-party tracking and funnel reporting.

$ each button prefixes agent-specific run instructions · build your own product, never copy proprietary code, trademarks or designs