Monitor Competitor Price Shifts with Slack Alerts

How It Works

A scheduled n8n workflow pulls a list of competitor product URLs, hands them to the Apify E-commerce Scraping Tool, stores one row per product per day in Postgres, and compares today against a trailing baseline to flag only the moves that matter. An AI agent writes the recommendation and posts it to Slack, while a second branch reports any URLs that failed to scrape.

Setup Steps

1. Install the Apify node: Add the @apify/n8n-nodes-apify community node. On n8n Cloud, search for it on the canvas (the instance owner must have verified community nodes enabled); self-hosted, install it under Settings, Community nodes.
2. Apply the Postgres schema: Run supabase_schema.sql (linked in the sticky note) against Postgres 15 or later. It creates a private schema with RLS enabled, so the table is never exposed through Supabase’s Data API.
3. Add credentials: Connect Apify, Postgres, a chat model, and Slack.
4. Set your watchlist: Open the Pages to watch node, replace the example URLs with yours, and point the workflow at your Slack channel.
5. Confirm the timezone: The schedule says 06:00 and n8n reads it in the instance timezone; adjust the instance or the trigger.
6. Dry run once: Trigger the workflow manually and confirm a row landed in pricing.price_history.

Automation Workflow

Schedule (06:00)
    ↓
Read competitor URLs
    ↓
Apify E-commerce Scraping Tool
    ↓
Normalize prices, currency, stock
    ↓
Insert into Postgres (pricing.price_history)
    ↓
SQL view: compare to 30-day avg, 90-day low, 14-day baseline gate
    ↓
Branch
    ├→ Moves detected → AI agent writes recommendation → Slack
    └→ Scrape failures → Slack health warning

Benefits

• Transitions, not states: The SQL view reports a price move once, so a rival who cuts and holds does not spam the channel every morning.
• Deterministic detection: Thresholds live in one SQL view (5% band, 90-day low, 14-day baseline gate); the model only writes, it never decides.
• Locale-safe parsing: Both 1.299,99 and $1,299.99 read correctly, and currency is stored as an ISO code rather than a symbol.
• Scraping health signal: A second branch flags URLs that returned nothing, so a broken product page does not look like a quiet market.
• No scraper to maintain: Apify handles anti-bot, proxies, and per-retailer extraction.

Advanced Features

• Three-state stock field so “not reported” is kept separate from “out of stock”.
• 14-day silence window before any alert fires, because a baseline of one day is noise.
• Private Postgres schema with row-level security and security_invoker views, keeping snapshots out of Supabase’s Data API.
• Keyword mode option: run the Apify Actor in keyword mode once to harvest URLs, then pin them; keyword results drift daily and cannot produce a clean price series.
• Replace Slack with email, Sheets, or a webhook by swapping a single node.

Use Cases

• Daily repricing commentary for ecommerce merchandising teams.
• Early warning on competitor flash sales and markdowns across a watchlist.
• Monitoring retailers for stock changes on key SKUs during peak season.
• Tracking price positioning for private-label launches against incumbent brands.
• Reporting scraping health so a dead product page does not quietly go unmonitored.