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GeoIp2\Model\City Object
(
    [raw:protected] => Array
        (
            [city] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [continent] => Array
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                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                        (
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                            [zh-CN] => 美国
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            [location] => Array
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
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                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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                    [ip_address] => 216.73.216.141
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        )

    [continent:protected] => GeoIp2\Record\Continent Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
                        (
                            [de] => Nordamerika
                            [en] => North America
                            [es] => Norteamérica
                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                )

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            [validAttributes:protected] => Array
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    [country:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [3] => isoCode
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    [maxmind:protected] => GeoIp2\Record\MaxMind Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                )

            [validAttributes:protected] => Array
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                    [0] => queriesRemaining
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [validAttributes:protected] => Array
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                    [2] => isInEuropeanUnion
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                    [4] => names
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        )

    [traits:protected] => GeoIp2\Record\Traits Object
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                    [ip_address] => 216.73.216.141
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                    [network] => 216.73.216.0/22
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                    [2] => connectionType
                    [3] => domain
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                    [8] => isHostingProvider
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                    [11] => isPublicProxy
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                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
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                )

        )

    [city:protected] => GeoIp2\Record\City Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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            [validAttributes:protected] => Array
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    [location:protected] => GeoIp2\Record\Location Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [validAttributes:protected] => Array
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                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
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                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
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                    [code] => 43215
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            [validAttributes:protected] => Array
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                    [0] => code
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        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
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)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)
/Woolworths-Grocery-Discount-Tracking-with-Web-Scraping-in-Sydney

Overview

In Sydney’s fast-paced retail ecosystem, real-time pricing data is essential for FMCG brands and retail analysts to remain competitive. Our client—a data-driven consumer goods company—was struggling to track dynamic discounts and price shifts on Woolworths’ platform. Manual efforts were not scalable, and existing APIs lacked depth and flexibility.

That’s when Actowiz Solutions was brought in to automate and enhance grocery discount tracking using advanced web scraping technology for Woolworths product data.

Objective

The-Client

To extract and monitor live pricing, discount rates, promotional tags, and product availability across Woolworths' online listings in Sydney, with the goal of:

  • Identifying discount trends by category
  • Benchmarking against competitor brands
  • Informing optimal pricing and promotional strategies

Challenges

1. Dynamic Pricing Models: Frequent price changes meant data had to be updated multiple times daily.

2. Geo-Specific Pricing: Woolworths displays different prices based on the shopper’s location (e.g., Sydney vs. Melbourne).

3. High SKU Volume: Thousands of products needed to be monitored, categorized, and normalized daily.

4. Promotion Tags Parsing: Offers like “Everyday Low Price” or “Buy 2 Save $1” were embedded within product descriptions and required structured extraction.

Actowiz Solutions' Approach

Key-Solutions

Actowiz Solutions deployed a custom Woolworths web scraping solution tailored for location-based pricing in Sydney. Key implementation steps included:

  • Dynamic Crawling: Smart crawlers updated product data every 4 hours to capture all active discount changes.
  • Proxy Rotation & Geo-targeting: Scrapers simulated a Sydney-based shopper using proxy IPs to fetch city-specific pricing.
  • Structured Data Output: Data was formatted in CSV and JSON formats, enriched with:
    • Product name
    • Brand
    • SKU ID
    • Category
    • Original price
    • Discounted price
    • Offer description
    • Timestamp
  • Daily Dashboard Integration: Visual dashboards displayed daily trends in discounts by category and brand.
Sample Extracted Data (Sydney-based):
Product Name Brand Category Price (AUD) Discounted Price Discount Type Availability City
Arnott’s Tim Tam 200g Arnott’s Snacks $4.00 $3.00 Save $1 In Stock Sydney
Dove Shampoo 1L Unilever Personal Care $7.90 $6.50 Everyday Low Price In Stock Sydney
Uncle Toby’s Oats 1kg Nestlé Breakfast $5.50 $4.40 20% Off In Stock Sydney

Key Outcomes

1. 40% Faster Discount Detection

The client could identify changes in promotional campaigns within 4 hours, allowing faster response compared to manual tracking (which took up to 24 hours).

2. +28% Accuracy in Pricing Reports

With structured, timestamped product-level data, the accuracy of the client's internal pricing reports improved significantly.

3. Improved Competitive Benchmarking

Brands were able to compare Woolworths promotions in Sydney against Coles data for the same products, guiding smarter allocation of marketing budgets.

4. Trend Insights by Category

Woolworths ran more frequent discounts in Snacks and Beverages compared to Personal Care, prompting brands to reconsider launch timing in certain categories.

Client Feedback

"Actowiz Solutions transformed the way we track promotions in real time. The city-specific Woolworths data enabled us to deploy pricing updates and promotions with confidence—often within the same day."

Future Plans

Following the success in Sydney, the client expanded the scraping scope to Melbourne and Brisbane, with a goal to include store-level stockouts and loyalty card pricing in the next phase.

Actowiz is also integrating AI-driven price prediction models into its scraping platform to suggest discount cycles and timing based on historical patterns.

Conclusion

This case study proves how real-time grocery discount tracking through Woolworths web scraping has a tangible impact on FMCG pricing strategies. With Actowiz Solutions’ scalable and accurate scraping infrastructure, businesses now have the tools to act on market changes as they happen—not days later.

If your team needs high-frequency product scraping for supermarkets like Coles, Woolworths, IGA, or others in Australia, Actowiz Solutions delivers the speed, accuracy, and intelligence you need.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape Structure Analyze Visualize

Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
1 min
★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
1 min

See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price Insights Top-selling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

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