Can I vibe code Wicked Reports?

Build a first-party ecommerce attribution tracking backend and analytics worker in Node.js and PostgreSQL. 1. DATA MODEL: Create tables for 'visitors' (id, created_at), 'sessions' (id, visitor_id, utm_source, utm_medium, utm_campaign, utm_content, referrer, user_agent, ip_address, created_at), 'identities' (visitor_id, email, hashed_email), 'orders' (id, shopify_order_id, email, total_price, order_date), and 'touchpoints' (id, visitor_id, order_id, session_id, touchpoint_type). 2. TRACKING SCRIPT & ENDPOINT: Write a lightweight JS snippet that sets a persistent first-party cookie (365 days), captures all URL params (utm_*), and sends a POST payload to '/api/v1/track' on page load. Store this in PostgreSQL. If an email is captured in a form or at checkout, hit '/api/v1/identify' to link the visitor ID to the email address. 3. SHOPIFY WEBHOOK: Implement a '/api/v1/webhooks/shopify/orders-create' handler. Extract the customer email and cart attributes/cookies. Resolve the email or visitor cookie to link the order to all historical sessions for that visitor. 4. ATTRIBUTION LOGIC: Implement a background job that calculates First-Touch, Last-Touch, and Linear Multi-Touch attribution weights for every order. Store calculated values in an 'order_attributions' table. 5. LTV COHORT ENGINE: Write a SQL query/API endpoint '/api/v1/reports/ltv-cohorts' that groups users by their first touchpoint campaign/source and calculates cumulative average revenue at 30, 60, 90, and 180-day intervals. 6. FAILURE MODES: Handle missing cookie data gracefully using email lookup fallback. Sanitize input to prevent SQL injection. Ignore bot user agents.

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