We extract appliance listings, promotional pricing, store-level inventory, and specification matrices from The Good Guys. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Appliance Listings objects from thegoodguys.com.au. All fields typed and schema-versioned.
"sku": "5007421", "title": "Samsung 8.5kg Front Load Washer", "brand": "Samsung", "model_number": "WW85T504DAE", "price": 795.0, "energy_rating": "4.5 Stars", "water_rating": "4.5 Stars", "warranty_period": "2 Years"
| # | sku | title | brand | model_number | category | sub_category |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Promos objects from thegoodguys.com.au. All fields typed and schema-versioned.
"sku": "5007421", "current_price": 795.0, "ticket_price": 949.0, "discount_amount": 154.0, "promo_badge": "Pay Less Pay Cash", "cashback_offer": 50.0, "bonus_item": "Free Delivery", "valid_until": "2026-06-30T23:59:59Z"
| # | sku | current_price | ticket_price | discount_amount | promo_badge | cashback_offer |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Store Inventory objects from thegoodguys.com.au. All fields typed and schema-versioned.
"sku": "5007421", "store_id": "TGG_ALEX", "store_name": "Alexandria", "postcode": "2015", "stock_status": "In Stock", "click_and_collect": "Available Today", "display_stock": true, "last_updated": "2026-05-12T10:15:00Z"
| # | sku | store_id | store_name | postcode | stock_status | click_and_collect |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Specifications objects from thegoodguys.com.au. All fields typed and schema-versioned.
"sku": "5007421", "capacity": "8.5kg", "colour": "White", "smart_features": "Wi-Fi Connected", "installation_required": true, "power_consumption": "305 kWh/yr", "weight": "67 kg", "noise_level": "72 dB"
| # | sku | capacity | colour | material | smart_features | installation_required |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from thegoodguys.com.au. All fields typed and schema-versioned.
"review_id": "REV-884921", "sku": "5007421", "rating": 5, "author": "John D.", "date": "2026-04-10", "title": "Quiet and efficient", "verified_buyer": true, "helpful_votes": 12
| # | review_id | sku | rating | author | date | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper targets The Good Guys' specific architecture, handling store-selector cookies, dynamic promotional badges, and deeply nested specification tables.
Extract product titles, brand names, model numbers, and core attributes across the entire catalogue.
Monitor Click & Collect availability and floor stock status across specific postcodes and retail locations.
Capture ticket prices versus actual sale prices, tracking 'Pay Less Pay Cash' offers and limited-time discounts.
Extract standardized energy and water efficiency star ratings and consumption metrics for compliance and comparison.
Parse nested HTML specification tables into flat, queryable JSON fields for dimensions, capacity, and materials.
Identify manufacturer cashbacks, gift card bonuses, and bundled item promotions attached to specific SKUs.
Paginate through customer reviews to extract star ratings, text bodies, and verified purchaser flags.
Traverse category trees to map product taxonomies from root departments down to specific sub-categories.
Extract estimated delivery timeframes and installation service availability based on target postcodes.
Brief in. Clean data out.
Provide categories, search terms, or a list of target postcodes. We map the required data fields.
We configure Scrapy spiders, manage AU residential proxies, and handle location-based session cookies.
We check null rates on pricing, verify store stock accuracy, and ensure schema compliance.
Data is pushed to your preferred endpoint in JSON, CSV, or Parquet format on your required schedule.
Retail sites deploy aggressive caching and regional variations. We manage the session state to ensure accurate, localised extraction.
Inventory and delivery data on The Good Guys requires setting specific store location cookies. We manage these session states per request to pull accurate regional data.
Final prices and cashback badges often load asynchronously. We use Playwright to execute the page JavaScript and capture the fully rendered promotional state.
To prevent IP bans and rate limiting, we route requests through Australian residential proxies, matching the geographic expectation of the target server.
Appliance specifications vary wildly between brands. We normalise these nested tables into consistent column headers so your database schema remains stable.
We hash product records and only emit data when prices, stock levels, or promotions change, reducing your downstream processing costs.
Competing retailers monitor daily price fluctuations to trigger automated price-match guarantees and adjust their own pricing.
Appliance manufacturers audit the site to ensure their products are listed at agreed promotional prices and with correct specifications.
Analysts track store-level stock depletion rates to estimate sales velocity for specific brands and categories.
Research firms aggregate catalogue sizes and review counts to determine brand visibility within the Australian electronics sector.
Environmental and consumer advocacy groups compile energy and water efficiency data across appliance categories.
Marketing teams track the frequency and depth of cashback and bonus item offers to inform their own promotional calendars.
"Appliance pricing is highly dynamic, driven by cashback offers and localised store stock. Static scraping misses the actual transaction price."
Extracting accurate data from The Good Guys requires managing location cookies for Click & Collect status and executing JavaScript to reveal final promotional prices. DataFlirt handles regional session states so your analysts get the exact price a customer sees in Sydney or Melbourne.
Everything supported by our thegoodguys.com.au scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles the core crawl orchestration while Playwright renders the JavaScript required to load dynamic promotional prices and stock levels.
We route traffic through Australian residential IPs to ensure the target server returns localised content without triggering security blocks.
Pipelines run on Kubernetes with Airflow scheduling the jobs. This ensures reliable daily or hourly execution with full observability.
Data delivered to where your team already works — no new tooling required.
About thegoodguys.com.au scraping, legality, and pipeline operations.
Ask us directly →Yes. We configure the pipeline to inject location cookies for your target postcodes, allowing us to extract exact stock statuses for Click & Collect and in-store displays.
Promotional prices and cashback offers are often loaded via JavaScript. We use Playwright to fully render the page and extract the final calculated price alongside the original ticket price.
Yes. A full catalogue sweep can be scheduled daily. For high-priority categories, we can configure intraday runs to catch fast-moving price changes.
Yes. We parse the specification tables on the product pages, extracting attributes like dimensions, energy ratings, and capacities into structured fields.
Scraping publicly available pricing and product data is generally permissible. We do not bypass authentication walls or extract personal user data. Clients should ensure their specific use cases comply with local competition and data laws.
We push data directly to your infrastructure. Common delivery methods include Parquet files to AWS S3, JSON via Webhook, or direct inserts into Snowflake and BigQuery.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need daily price matching feeds or a complete catalogue extraction, we build and manage the infrastructure. Tell us your requirements.
