Coles Price Tracker

Real-time Coles price tracking - one of the two largest Australian supermarket chains. Two ways to get started: a fully managed intelligence platform or a custom scraper built with Bright Data's AI Scraper Builder.

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Option 1: Bright Insights - AI-Powered Price Tracking (Recommended)

Bright Insights is Bright Data's fully managed retail intelligence platform. No scrapers to build, no infrastructure to maintain - just structured, analysis-ready price data delivered to dashboards, data feeds, or your BI tools.

Why teams choose Bright Insights:

• 🚀 Zero setup - Go live in minutes with ready-to-use dashboards and data feeds
• 🤖 AI-powered recommendations - A conversational AI assistant turns millions of data points into actionable insights instantly
• ⚡ Real-time monitoring - Hourly to daily refresh rates with instant alerts (email, Slack, webhook)
• 🌍 Unlimited scale - Any website, any geography, any refresh frequency
• 🔗 Plug-and-play integrations - AWS, GCP, Databricks, Snowflake, and more
• 🛡️ Fully managed - Bright Data handles schema changes, site updates, and data quality automatically

Key use cases:

• ✅ Track grocery price inflation across categories on Coles
• ✅ Monitor promotions and weekly deals automatically
• ✅ Build a price history database for basket analysis
• ✅ Monitor MAP policy compliance and detect pricing violations
• ✅ Track competitor promotions and promotional dynamics
• ✅ Feed clean, harmonized data directly into dynamic pricing algorithms or AI models

Starting from $250/month - Get a tailored quote →

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Option 2: Build Your Own Coles Scraper

No pre-built Coles scraper API? No problem. Bright Data's AI Scraper Builder generates a custom Coles scraper in just a few clicks — no coding required.

Build your Coles scraper in minutes

Open the Coles AI Scraper Builder →

Choose the domain, outline your data requirements, and let our AI scraper builder automatically create the API.

1. Describe data needs in plain English
2. AI instantly generates the scraper API
3. Run API requests for immediate results
4. Edit the code in the built-in IDE, if needed

Once built, your scraper gets a Web Scraper ID (gd_xxxxxxxxxxxx) — copy it for the Setup step below.

Prerequisites

• Python 3.9 or higher
• A Bright Data account (free trial available)
• A Bright Data API token (how to get one)
• A Web Scraper ID for Coles (from the build step above)

Setup

1. Clone this repository

   git clone https://github.com/luminati-io/coles-price-tracker.git
   cd coles-price-tracker

2. Install dependencies

   pip install -r requirements.txt

3. Configure credentials

   Copy .env.example to .env and fill in your values:

   cp .env.example .env

   BRIGHTDATA_API_TOKEN=your_api_token_here
   BRIGHTDATA_DATASET_ID=your_dataset_id_here

   Your Web Scraper ID Paste the Web Scraper ID from your AI Scraper Builder dashboard into BRIGHTDATA_DATASET_ID (format: gd_xxxxxxxxxxxx).

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Usage

Once your Coles scraper is built and your Web Scraper ID is configured in .env, the Python interface works the same way:

1. Track Specific Products by URL

Pass a list of Coles product URLs to retrieve structured price data:

from price_tracker import track_prices

urls = [
    "https://www.coles.com.au/products/sample-product",
    # Add more product URLs here
]

results = track_prices(urls)
for item in results:
    print(f"{item.get('title')} - {item.get('final_price', item.get('price'))} {item.get('currency', '')}")

Or run directly:

python price_tracker.py

2. Discover Products by Keyword

Find products matching a keyword search:

from price_tracker import discover_by_keyword

results = discover_by_keyword("laptop", limit=50)

3. Browse Products by Category URL

Collect all products from a Coles category page:

from price_tracker import discover_by_category

results = discover_by_category(
    "https://coles.com.au/category/example",
    limit=100,
)

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Output Fields

Each result record contains the following fields:

Field	Description
url	Product page URL
name	Product name
brand	Brand
price	Current price
currency	Currency code
unit_price	Price per unit/weight
in_stock	Stock status
category	Product category
sku	SKU / barcode
images	Product image URLs
description	Product description
timestamp	Collection timestamp

Sample output

[
  {
    "url": "https://www.coles.com.au/products/sample-product",
    "title": "Example Product Name",
    "brand": "Example Brand",
    "initial_price": 59.99,
    "final_price": 44.99,
    "currency": "USD",
    "discount": "25%",
    "in_stock": true,
    "rating": 4.5,
    "reviews_count": 1234,
    "images": ["https://coles.com.au/images/product1.jpg"],
    "description": "Product description text...",
    "timestamp": "2025-01-15T10:30:00Z"
  }
]

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Advanced Options

The trigger_collection() function accepts optional parameters to control data collection:

Parameter	Type	Default	Description
limit	integer	-	Maximum number of records to return
include_errors	boolean	true	Include error reports in results
notify	string (URL)	-	Webhook URL to call when the snapshot is ready
format	string	json	Output format: json, csv, or ndjson

Example with options:

from price_tracker import trigger_collection, get_results

inputs = [{"url": "https://www.coles.com.au/products/sample-product"}]
snapshot_id = trigger_collection(inputs, limit=200, notify="https://your-webhook.com/hook")
results = get_results(snapshot_id)

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Resources

• 🌟 Coles Price Tracker - Bright Insights (Managed)
• 🏗️ Build a Coles Scraper
• 📖 Bright Data Web Scraper API Documentation
• 🗄️ Web Scrapers Control Panel
• 🔑 How to get an API token
• 🌐 Bright Data Homepage

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Built with Bright Data - the industry-leading web data platform.