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GeoIp2\Model\City Object
(
    [raw:protected] => Array
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            [city] => Array
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                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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                    [ip_address] => 216.73.216.115
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    [continent:protected] => GeoIp2\Record\Continent Object
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                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
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                            [de] => Nordamerika
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                            [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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                    [names] => Array
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                            [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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    [registeredCountry:protected] => GeoIp2\Record\Country Object
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
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                            [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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    [traits:protected] => GeoIp2\Record\Traits Object
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            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [network] => 216.73.216.0/22
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            [validAttributes:protected] => Array
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                    [14] => isTorExitNode
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                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

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    [city:protected] => GeoIp2\Record\City Object
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                            [pt-BR] => Columbus
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                            [zh-CN] => 哥伦布
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 country : United States
 city : Columbus
US
Array
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    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

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  • Grocery & Supermarket Data Scraping Services USA | Actowiz Solutions

Grocery & Supermarket Data Scraping Services in USA – Real-Time Prices, Availability & Market Insights

Stay ahead in the competitive grocery and supermarket industry with Actowiz Solutions. Our grocery & supermarket data scraping services deliver real-time insights into pricing, product availability, promotions, and customer reviews from leading platforms like Walmart, Amazon Fresh, Instacart, BigBasket, Carrefour, Tesco, and Costco.

We serve enterprises in the USA, UAE, India, Japan, Denmark, UK, Germany, Canada, Singapore, and Australia, delivering >99% accurate, structured datasets in JSON, CSV, or Excel, seamlessly integrated into your systems.

With Actowiz, you can:

  • Track grocery & FMCG prices across marketplaces
  • Monitor product availability & out-of-stock alerts
  • Analyze supermarket promotions, coupons & seasonal offers
  • Benchmark private label vs. national brand pricing
  • Gain city-level & hyperlocal grocery market insights

Turn raw grocery data into actionable intelligence that helps optimize pricing, manage inventory, and stay ahead of competitors across the USA, UAE, and global markets.

Request a Free Quote
Top Web Scraping & Data Intelligence Company In The USA 01

Top Countries:

USA UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia
UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia UK Germany Japan India France Canada Australia

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B2B-B2C-Marketplace-amazon
B2B-B2C-Marketplace-IndiaMART
B2C-Marketplace-Amazon
B2C-Marketplace-Flipkart
D2C-Marketplace-Nykaa
D2C-Marketplace-Walmar
Electronic-D2C-Apple
Electronic-D2C-boAt
Fashion-Marketplace-Farfetch
Fashion-Marketplace-Myntra
FMCG-Marketplace-Boxed
FMCG-Marketplace-Udaan
Food-Delivery-Swiggy
Food-Delivery-Uber-Eats
Quick Commerce-Blinkit
Quick Commerce-GoPuff
Social-Commerce-Meesho
Social-Commerce-Poshmark
Taxi-Aggregator
Taxi-Aggregator-Uber

Why Grocery & Supermarket Data Scraping is Essential in USA & UAE

The grocery and supermarket industry in the USA and UAE is highly competitive and constantly evolving. In the USA, leading platforms like Walmart, Amazon Fresh, and Instacart dominate, while in the UAE, players such as Carrefour, Lulu Hypermarket, and Talabat Mart are reshaping consumer expectations. With rising online grocery adoption, even small shifts in pricing, stock availability, and promotions can significantly impact customer loyalty and sales.

Prices and availability change multiple times a day across thousands of SKUs. Seasonal promotions, private label competition, and sudden out-of-stock (OOS) issues make manual monitoring impractical. Delivery fees and dynamic pricing further complicate the landscape, forcing retailers and FMCG brands to adopt data-driven strategies.

By leveraging grocery and supermarket data scraping, businesses in the USA, UAE, India, Japan, Denmark, and other global markets gain:

  • Real-time price intelligence to benchmark against competitors
  • OOS and substitution tracking for improved supply chain planning
  • Promotional monitoring to capture coupons, flash sales, and loyalty programs
  • Consumer sentiment insights from reviews and ratings
  • City-level and hyperlocal grocery intelligence to refine regional strategies

This intelligence empowers retailers, e-commerce platforms, and FMCG companies to stay ahead of competition, optimize pricing, manage inventory efficiently, and deliver a better customer experience.

What Types of Data are Typically Extracted When Scraping Grocery & Supermarket Information?

Grocery data scraping services typically extract a wide range of information from supermarket websites. This includes product details, pricing, discounts, and availability. Supermarket web scraping also gathers data on store locations, customer reviews, and promotional offers, enabling comprehensive analysis through grocery store data extraction and supermarket product data scraping.

  • Product Name
  • Product Category
  • Brand
  • Price
  • Discount Price
  • Availability Status
  • Product Description
  • Ingredients List
  • Nutritional Information
  • Allergen Information
  • Product Images
  • Weight/Volume
  • SKU Number
  • Barcode
  • Shelf Life
  • Customer Reviews
  • Customer Ratings
  • Store Name
  • Store Location
  • Store Hours
  • Contact Information
  • Delivery Options
  • Delivery Fees
  • Pickup Options
  • Promotion Details
  • Expiry Dates
  • Manufacturer Information
  • Packaging Type
  • Minimum Order Quantity
  • Loyalty Program Information
What-Types-of-Data-are-Typically-Extracted-When-Scraping-Grocery-Supermarket-Information
Inspiration-Awaits-Sample-Travel-Delivery-Data-Showcase-01

Inspiration Awaits: Sample Grocery Delivery Data Showcase

Take a look at our curated sample grocery delivery data and get inspired.See the impact of detailed grocery insights on innovation and strategy development.

See Data Samples

No matter the shape or size, we capture all data. Our extensive range ensures you get the complete and detailed data you need for any application.

  • Comprehensive Grocery Data Capture

    Capture comprehensive grocery data with our supermarket web scraping services, covering prices, inventory, and product details seamlessly.

  • Detailed Market Insights

    Extract detailed insights with supermarket product data scraping for effective grocery market analysis scraping and strategic decision-making.

  • Automated Data Extraction

    Automate grocery store data extraction with our advanced tools, ensuring efficient online grocery data scraping and accurate results.

  • Competitor Analysis

    Conduct competitor analysis for supermarkets using our web scraping expertise to uncover pricing strategies and market trends.

  • Effective Price Monitoring

    Monitor supermarket prices effectively with our specialized tools for supermarket price monitoring and dynamic market insights.

  • Enhanced Inventory Management

    Enhance operations with supermarket inventory scraping services, providing real-time stock data for improved inventory management.

  • Comprehensive Data Extraction

    Utilize automated grocery data extraction for comprehensive grocery store product scraping and detailed market intelligence.

  • Strategic Optimization

    Optimize strategies with online grocery data scraping, empowering you with valuable data for competitive advantage and growth.

  • Tailored Data Solutions

    Access supermarket data mining solutions tailored to your needs, from grocery store data scraping tools to strategic insights.

No-matter-the-shape-or-size-we-capture-all-data

Explore the Best Techniques to Collect Grocery Data

Premium-Industry-Datasets-on-Demand
Web Scraping Solutions

Our web scraping services encompass your target grocery websites, delivering data in a standardized schema. This approach streamlines your workflow and saves you valuable time and resources.

Web Scraping
Efficiency Meets Expertise
Web Scraping API

Experience the leading web scraping API, meticulously designed to sidestep bans with ease, maximizing cost-effectiveness and streamlining your project timeline.

API
Tailored Data Solutions for Your Enterprise
Web Scrapers

Our web scrapers offers advanced tools for comprehensive data extraction from diverse sources, ensuring optimized web scraping capabilities. Trust us to get innovative solutions tailored to your specific requirements.

Scraper
Commitment-to-Ethical-Data-Practices
Enterprise-Ready Solutions

Enterprise-Ready Solutions for Robust Data Extraction and Integration. Our advanced tools and expertise ensure seamless integration and scalable performance, meeting the rigorous demands of large-scale data extraction projects.

Enterprise Solution

How to get grocery delivery details from grocery sites?

Monitor Competitor Pricing

Track competitors' scraping grocery prices daily to stay competitive and adjust your pricing strategy accordingly.

Trend Analysis

Analyze grocery shopping trends to understand consumer preferences and stock popular products.

Inventory Management Optimization

Optimize inventory by predicting demand for specific grocery items using historical sales data.

Supplier Evaluation

Compare prices and quality of products from various suppliers to choose the best options for your store.

Customer Insights

Gather data on customer preferences and buying patterns to personalize marketing campaigns.

New Product Launch

Assess the market demand and competitor landscape before launching new grocery products.

Market Research

Conduct comprehensive market research to identify emerging trends and potential growth areas in the grocery sector.

Price Monitoring

Automatically monitor price fluctuations to make timely adjustments and maintain competitive pricing.

Promotional Analysis

Evaluate the effectiveness of promotional campaigns by analyzing sales data and customer response.

List of Popular Grocery Platforms

Popular grocery platforms have revolutionized how people shop for daily essentials, offering convenience and a wide variety of products. Leading platforms like Instacart, Amazon Fresh, and Walmart Grocery provide seamless online shopping experiences with fast delivery services. Other notable names include Kroger, FreshDirect, and Peapod, which cater to diverse consumer needs. Internationally, platforms like BigBasket in India and Ocado in the UK are popular. These platforms ensure that fresh produce, pantry staples, and household items are just a click away. Here is the list of popular grocery websites:

Popular Grocery Websites

Online Grocery Delivery App

Scrape Country Wise

USA

UK

UAE

Australia

Austria

Argentina

Belarus

Belgium

Brazil

Bulgaria

Canada

Chile

China

Colombia

Croatia

Czech Republic

Denmark

Ecuador

Egypt

Estonia

Finland

France

Germany

Greece

Hong Kong

Hungary

India

Indonesia

Iran

Ireland

Israel

Italy

Japan

Kazakhstan

Kenya

Korea

Kuwait

Latvia

Luxembourg

Malaysia

Mexico

Morocco

Netherlands

New Zealand

Nigeria

Norway

Pakistan

Panama

Peru

Philippines

Poland

Portugal

Romania

Russia

Saudi Arabia

Serbia

Singapore

Slovakia

Slovenia

South Africa

Spain

Sweden

Swiss

Taiwan

Thailand

Turkey

Ukrainian

Vietnam

Frequently Asked Questions

You can receive your data through various methods such as SFTP, FTP, email, Dropbox, Google Cloud storage, AWS S3, or Google Drive. We offer delivery in JSON, CSV, XML, or JSONLines formats, tailored to your project needs. Custom delivery options are also available upon request to meet specific requirements.
While we possess the technical capability to extract data from any website, each project must adhere to legal considerations. This includes scraping behind logins and compliance with privacy policies, terms and conditions, and copyright laws. Our solution architects and legal team assess each project to ensure adherence to web scraping best practices and legal requirements.
After submitting your project request, a member of our solution architecture team will promptly initiate a project discovery call. They will delve into your e-commerce data scraping requirements, including which sites to crawl, specific data extraction needs, the scope of scraping, data transformation requirements, and necessary integrations. Once gathered, our architects will propose tailored e-commerce data scraping solutions within a few days for your approval.
Our expertise lies in data extraction solutions designed for mission-critical business needs, prioritizing the delivery of high-quality, accurate data to our clients. Implementing a rigorous four-layer Data Quality Assurance process ensures continuous monitoring of crawl health and data accuracy through manual, semi-automated, and automated testing. Count on us for reliable grocery data scraping services, including online store data scraping and competitor price monitoring.
We provide complimentary support to all our customers for coverage issues, missed deliveries, and minor site changes. Larger website data extraction changes that require a complete spider overhaul may invite additional costs.
Yes, if sample data is available for the source you wish to scrape, we can provide it. For new sources not previously crawled, sample data will be shared after the development kick-off, which occurs post-purchase. Additionally, for product or news & article data, you can trial our Automatic Extraction product with a user-friendly interface for free.
Actowiz offers comprehensive Data Extraction services, providing hassle-free web content extraction for clean, structured data quickly and accurately. Alternatively, Actowiz also provides DIY web data extraction tools for those preferring a hands-on approach.
Data extraction refers to the process of retrieving specific information or datasets from various sources such as databases, websites, or documents. It involves systematically gathering relevant data for analysis, reporting, or storage purposes. This method is crucial in industries like finance, healthcare, and grocery, where accessing and analyzing large volumes of data is essential for decision-making. Data extraction typically utilizes tools and techniques such as web scraping, API calls, or database queries to fetch structured data. The extracted data is then transformed and loaded into a format suitable for analysis, enabling businesses to derive insights, improve efficiency, and support strategic initiatives.
Data extraction is crucial as it enables organizations to access, collect, and utilize valuable information from diverse sources efficiently. By extracting data from databases, websites, or other repositories, businesses can derive actionable insights, improve decision-making processes, and enhance operational efficiency. This process is particularly vital in industries like finance, healthcare, and retail, where analyzing large datasets helps in trend analysis, customer behavior understanding, and market forecasting. Data extraction also supports compliance with regulatory requirements by ensuring accurate reporting and data governance. Overall, it empowers organizations to leverage data-driven strategies, innovate products and services, and maintain a competitive edge in the market.
Certainly! An example of data extraction could involve extracting customer information from an grocery website. Using web scraping techniques, specific data such as customer names, email addresses, purchase histories, and preferences can be gathered from multiple pages of the website. This extracted data can then be structured into a format like CSV or JSON for further analysis or integration into a customer relationship management (CRM) system. By automating this process, businesses can streamline customer data management, personalize marketing efforts, and improve customer service strategies based on insights derived from the extracted data. 
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
                        )

                )

            [continent] => Array
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                            [fr] => Amérique du Nord
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                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                    [iso_code] => US
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                            [es] => Estados Unidos
                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [location] => Array
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                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
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                    [code] => 43215
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            [registered_country] => 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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            [subdivisions] => Array
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                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
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                                    [de] => Ohio
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                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                )

            [traits] => Array
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                    [ip_address] => 216.73.216.115
                    [prefix_len] => 22
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        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => NA
                    [geoname_id] => 6255149
                    [names] => Array
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                            [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

    [locales:protected] => Array
        (
            [0] => en
        )

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

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

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

        )

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

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.115
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

            [validAttributes:protected] => Array
                (
                    [0] => autonomousSystemNumber
                    [1] => autonomousSystemOrganization
                    [2] => connectionType
                    [3] => domain
                    [4] => ipAddress
                    [5] => isAnonymous
                    [6] => isAnonymousProxy
                    [7] => isAnonymousVpn
                    [8] => isHostingProvider
                    [9] => isLegitimateProxy
                    [10] => isp
                    [11] => isPublicProxy
                    [12] => isResidentialProxy
                    [13] => isSatelliteProvider
                    [14] => isTorExitNode
                    [15] => mobileCountryCode
                    [16] => mobileNetworkCode
                    [17] => network
                    [18] => organization
                    [19] => staticIpScore
                    [20] => userCount
                    [21] => userType
                )

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => 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
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                (
                    [0] => en
                )

            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

        )

    [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
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

        )

    [postal:protected] => GeoIp2\Record\Postal Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [code] => 43215
                )

            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => confidence
                )

        )

    [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
                                    [zh-CN] => 俄亥俄州
                                )

                        )

                    [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
                        (
                            [0] => en
                        )

                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

                )

        )

)

 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
)

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From Raw Data to Real-Time Decisions

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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.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
Trusted by Global Leaders – Secured by International Standards

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

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Real results from real businesses using Actowiz Solutions

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'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
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Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
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Iulen Ibanez
CEO / Datacy.es
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★★★★★
“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
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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

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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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Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place

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Oct 17, 2025

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Build and analyze Historical Real Estate Price Datasets to forecast housing trends, track decade-long price fluctuations, and make data-driven investment decisions.

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Scrape Diwali Real Estate Discounts: How Actowiz Solutions Analyzed 50,000+ Property Listings Across India

Actowiz Solutions scraped 50,000+ listings to scrape Diwali real estate discounts, compare festive property prices, and deliver data-driven developer insights.

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Festive Price Surge Tracker: Amazon Fresh vs BigBasket vs JioMart in India

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Build and analyze Historical Real Estate Price Datasets to forecast housing trends, track decade-long price fluctuations, and make data-driven investment decisions.

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How Travel Agencies in Italy Use Trenitalia Data Scraping for Route Optimization to Enhance Customer Experience?

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Oct 16, 2025

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Discover where Indians are flying this Diwali 2025. Actowiz Solutions shares real travel data, price scraping insights, and booking predictions for top festive destinations.

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Scrape Diwali Real Estate Discounts: How Actowiz Solutions Analyzed 50,000+ Property Listings Across India

Actowiz Solutions scraped 50,000+ listings to scrape Diwali real estate discounts, compare festive property prices, and deliver data-driven developer insights.

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Scraping 250K Restaurant Menus: How Actowiz Solutions Decoded Diwali Dining Trends Across India

Actowiz Solutions used scraping of 250K restaurant menus to reveal Diwali dining trends, top cuisines, festive discounts, and delivery insights across India.

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Tracking Diwali Barbie Resale & Pricing Data How Actowiz Solutions Mapped Real-Time Price Spikes and Global Collector Demand

Actowiz Solutions tracked Diwali Barbie resale prices and scarcity trends across Walmart, eBay, and Amazon to uncover collector insights and cross-market analytics.

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Festive Price Surge Tracker: Amazon Fresh vs BigBasket vs JioMart in India

Track how prices of sweets, snacks, and groceries surged across Amazon Fresh, BigBasket, and JioMart during Diwali & Navratri in India with Actowiz festive price insights.

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Top 5 Brands Offering Deepest Discounts on Clothes This Navratri

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Competitive Product Pricing on Tesco & Argos Using Data Scraping to Uncover 30% Weekly Price Fluctuations in the UK Market

Discover how Competitive Product Pricing on Tesco & Argos using data scraping uncovers 30% weekly price fluctuations in UK market for smarter retail decisions.
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Airline Ticket Price Trends - Scrape Airline Ticket Price Trend and Track 20–35% Market Volatility in U.S. & EU

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