BIG W scraper for prices, tickets and store stock

BIG W prints the reason for a price next to it: Special, Clearance, Price Drop, a WAS figure or an RRP. Our BIG W scraper collects every product with that ticket and its seller.

Plans from €169/month · Free project assessment · Reply within 1 business day

BIG W Scraper
Solutions

BIG W data scraper as a managed service

There is nothing to install or configure. Tell us the scope - the whole bigw.com.au range, a few departments such as Toys or Home and Appliances, a brand list, one Marketplace seller, or a file of article numbers - and how often you need it. We build the crawlers, run them and repair them when BIG W changes its pages.

Availability on BIG W depends on the postcode and store a shopper has picked, and the storefront is guarded against automated traffic, so rendering, pacing, proxy rotation and CAPTCHA handling are part of the service. Runs are one-off or scheduled: daily for prices and tickets, weekly for the full range, on demand ahead of a catalogue sale. Start with a free project assessment, or order a sample for one category.

BIG W product data we extract

A BIG W product page is built around one identifier, the article number. It is printed above the title as Article, repeated in the Specification table and closes the product address after /p/; a colour variant of a garment adds a suffix to it. We use it as the row key, so a product keeps its identity from run to run.

  • Identity - article number, product URL, title, brand, the barcode (GTIN) carried by the page, and the breadcrumb from department down to the last category.
  • Price - the current price in AUD, the SAVE amount and percentage off, the WAS price with its date on Price Drop lines, the RRP where one is shown, the Originally figure on Clearance lines, the Price after promotion on introductory offers and the unit price printed on everyday goods.
  • Tickets - Special, Clearance, Price Drop, Big Deal, New, Flash Deal and multi-buy offers, plus the Lowest price in 14 days call-out that BIG W shows on Marketplace products.
  • Seller - the sold and shipped by line: BIG W itself or a named Marketplace seller, with the returns wording that goes with each.
  • Fulfilment - Free delivery and Limited free delivery flags, the Delivery only, Online only and Not available in store markers, delivery and pick up availability, and whether a delivery fee is added.
  • Content - description, the Product Features list, the Specification table (brand, dimensions, weight, recommended age on toys) and image addresses.
  • Ratings - the star rating on tiles and product pages and the Reviews section; review text on request, without reviewer names.
  • Loyalty - the Everyday Rewards points a purchase collects.

Listing tiles on category, brand and seller pages repeat the price, ticket, star rating and fulfilment markers, so a price run can read listings alone and leave product pages for a slower cycle. Clothing with colour swatches and a size range is split into one row per option, because BIG W shows availability only once a colour and a size are chosen. Field documentation is delivered with every dataset.

BIG W product data we extract
BIG W price tracker: tickets, sellers and store stock

BIG W price tracker: tickets, sellers and store stock

One pass gives a price list. BIG W itself looks back only a fortnight, and only for Marketplace products, with its Lowest price in 14 days label. To track BIG W prices across the whole range we key every run on the article number and keep each price, ticket and seller we see.

  • Ticket calendar. BIG W describes a Special as a discount off the shelf price for a short period, usually a couple of weeks. Daily runs show the day a Special starts, how deep it is and the shelf price it returns to.
  • Listing coverage. A category page loads 48 products at a time behind a Load more button; brand, collection and seller pages follow the same layout, and the largest departments show a rounded counter instead of an exact total. We walk the tree down to the smallest categories and use the Category, Price, Deals, Brand, Condition and Rating filters as slices.
  • Marketplace sellers. Each seller has a page under Marketplace Sellers with its description, categories and range, so one seller, or BIG W-sold lines alone, can be isolated.
  • Store stock. With a postcode set, a product page shows pick up, in-store and delivery availability for the chosen store. We repeat the check across the stores you name; the store finder adds each store's address, services and opening hours for this week and the next.
  • Collections. Clearance, Price drop, New and Trending, pre-orders and catalogue pages are tracked as lists of their own.

About BIG W and how bigw.com.au is organised

BIG W is an Australian discount department store run by Woolworths Group, with stores around the country and one national online shop at bigw.com.au. The range is general merchandise: toys, clothing for women, men, kids and babies, home and appliances, furniture, tech and audio, gaming, books, health and beauty, sports, party, pet care, cleaning, and snacks and drinks.

Three things shape the site for anyone who needs its data. First, it is two catalogues in one. Beside the lines BIG W buys and sells itself sits the Marketplace, where third-party sellers list furniture, appliances, tech and refurbished goods; most of these carry the Delivery only and Online only markers and their own returns wording, and the sold and shipped by line on each product page separates the two. Second, a price never stands alone. BIG W publishes a guide to its value call-outs, so a ticket on a tile - Special, Clearance, Flash Deal, a WAS price, an RRP, Price after promotion - has a stated meaning that can be stored as a column. Third, availability is local: pick up, same day delivery and in-store stock depend on the postcode and store selected, so a national picture is assembled store by store.

The category tree runs several levels deep, each level with a numeric code in its address, and brand pages cut across it.

Get a Quote
dev_w
25

Developers

customers
500+

Customers worldwide

pages
1 500 000 000+

Pages extracted

stime
15000+

Hours saved for our clients

Plans

BIG W Scraping Plans and Pricing

Airplane

€199 / one-time

setup fee - included

Data limits100,000
Frequencyone-time
Run timeup to 5 days
Data storing7 days

Helicopter

€169 / mo

setup fee €499

Data limits250,000
Frequencymonthly
Run timeup to 5 days
Data storing14 days

Glasses

€229 / mo

setup fee €499

Data limits1,000,000
Frequencyweekly
Run timeup to 5 days
Data storing30 days

DNA

€549 / mo

setup fee €799

Data limits3,000,000
Frequency3 times daily
Run timesame day
Data storing90 days

Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.

Full plan details →

Why scrape BIG W prices and tickets

BIG W sells many of the toys, small appliances, books and nappies that Kmart, Target, Amazon Australia and the supermarkets also carry, so its tickets are a natural reference point for general merchandise pricing in Australia. The uses follow the fields.

  • Price monitoring for suppliers. A brand sees its shelf price, every Special and its depth, and whether a line has moved to Clearance - the ticket BIG W uses when it is clearing stock or ceasing to carry a product.
  • Competitor pricing for retailers. Daily prices keyed on article number and barcode map onto your own range, so you see who moved first on a console, a LEGO set or a stick vacuum.
  • Promotion analysis. Ticket type, SAVE amount and duration across a category show how deep and how often each brand is discounted, and, once a history exists, what last year's seasonal event looked like.
  • Marketplace intelligence. The seller line shows who is present in a category, how wide each range is and how third-party prices sit against BIG W-sold products.
  • Availability and range. Out-of-stock flags, online-only lines and new arrivals reveal range changes before a catalogue announces them.

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About ScrapeIt

ScrapeIt is a managed web scraping agency: clients describe the data, we build and run the crawlers and deliver the dataset. Department-store sites like BIG W are familiar ground - one catalogue sold partly by the retailer and partly by marketplace sellers, tickets that turn over every couple of weeks and stock that differs by store. You choose departments, fields and schedule. We deliver CSV, Excel or JSON files, a JSON feed or a load into your database.

FAQ

Do you offer a BIG W API for product and price data?

Yes. The ScrapeIt BIG W API returns article number, title, current price, ticket, the sold and shipped by line and availability as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files, a JSON feed or straight into your database.

Is it legal to scrape BIG W?

Yes. Prices, tickets, product details, seller names and availability are published on bigw.com.au for any shopper to read without an account. We collect only publicly available data - everything a visitor can see on BIG W - and we collect it legally.

Can you build a BIG W price history for my products?

Yes. Send a list of article numbers, barcodes or categories and we record the price, ticket, SAVE amount and seller on every run, daily if needed. The history starts with the first run, so it pays to begin before the sale period you want to analyse.

How often do BIG W prices and Specials change?

By BIG W's own definition a Special runs for a short period, usually a couple of weeks, and a Flash Deal is a price held for a short time. Daily runs catch both, while weekly runs are enough for range and assortment work. Clearance lines deserve a daily look because their stock is being run down.

Can you separate BIG W-sold products from Marketplace sellers and check store stock?

Yes. Every row carries the sold and shipped by line, so BIG W-sold products and each Marketplace seller can be filtered or delivered as separate files. Store availability is collected for the postcodes or stores you name, as pick up, in-store and delivery flags per article number.

How does it Work?

Step 1 - Make a Request

You share your needs, expectations, and desired timeframe. We’ll suggest the best solution based on your request and budget.

Step 2 - Configuring Custom Web Crawlers

Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.

Step 3 - Collect and Deliver

Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.

Step 4 - Maintain and Support

Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.

Request a Quote

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Which sites, which fields, how often. A couple of lines is enough.

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Big W data from €169/month. Free project assessment, reply within 1 business day.

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