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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
                        )

                )

            [continent] => Array
                (
                    [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
                        )

                )

            [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
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [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
                        )

                )

            [subdivisions] => Array
                (
                    [0] => 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
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.24
                    [prefix_len] => 22
                )

        )

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

                )

            [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] => 216.73.216.24
                    [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
)

In the digital age, e-commerce has revolutionized how consumers shop, making it essential for businesses to stay competitive by leveraging data. One of the most effective ways to gather valuable insights is through web scraping. This process involves extracting data from websites, and in this case, it targets product information from leading Indian e-commerce platforms like Jiomart, Amazon, BigBasket, Dmart, and Blinkit. This blog will guide you through the process and benefits of Jiomart product data scraping, BigBasket data extraction, Amazon product scraping, Blinkit inventory scraping, and Dmart product data extraction.

What is Web Scraping?

Web scraping, also known as web data extraction, is the process of using automated tools or scripts to gather data from websites. In the context of e-commerce, web scraping services for e-commerce are utilized to collect various types of product data, including prices, descriptions, availability, and reviews. This information can be used for competitive analysis, market research, price monitoring, and inventory management.

Why Scrape Product Data from Multiple Platforms?

Scraping product data from multiple platforms offers a multitude of benefits that can significantly enhance business intelligence and decision-making. In the rapidly evolving e-commerce landscape, leveraging web scraping services for e-commerce enables companies to stay competitive and informed.

Comprehensive Market Analysis

Multi-platform product data scraping allows businesses to gain a comprehensive understanding of market trends. By collecting data from various platforms, companies can analyze diverse product offerings, pricing strategies, and promotional campaigns. For instance, scrape product details from Jiomart and BigBasket price data scraping help in understanding the grocery and retail sector's pricing trends and product availability.

Competitive Intelligence

Understanding competitor strategies is crucial for staying ahead in the market. Amazon product information extraction provides insights into the vast array of products available on one of the world's largest e-commerce platforms. By comparing this data with other platforms like Blinkit product data scraping and Dmart inventory data scraping, businesses can identify gaps in their offerings, optimize their pricing, and enhance their product portfolios.

Dynamic Pricing Strategies

In the e-commerce world, prices fluctuate frequently. Access to real-time data through Jiomart e-commerce scraping and other platforms allows businesses to implement dynamic pricing strategies. This means they can adjust their prices in response to market conditions, competitor pricing, and consumer demand, thereby maximizing profits and staying competitive.

Enhanced Customer Insights

By scraping reviews, ratings, and product descriptions, businesses can gather valuable customer feedback and preferences. This data helps in refining product features, improving customer service, and tailoring marketing strategies. For example, extracting data from customer reviews on Amazon can provide insights into consumer sentiments and expectations.

Efficient Inventory Management

Multi-platform product data scraping aids in efficient inventory management. Businesses can track product availability across platforms, ensuring they are adequately stocked with popular items while avoiding overstocking less popular products.

Scraping product data from multiple platforms like Jiomart, BigBasket, Amazon, Blinkit, and Dmart is a powerful tool for businesses seeking to enhance their market presence. With web scraping services for e-commerce, companies can gain a holistic view of the market, improve decision-making, and ultimately, provide better value to their customers.

Key Platforms for Product Data Scraping

Jiomart

Jiomart is a popular online grocery and retail platform in India, offering a wide range of products. Jiomart product data scraping involves extracting information such as product names, descriptions, prices, discounts, and availability.

BigBasket

BigBasket is another leading online grocery platform. BigBasket data extraction can provide detailed information about product categories, prices, availability, and customer ratings.

Amazon

Being among the biggest e-commerce platforms worldwide, Amazon offers a vast array of products. Amazon product scraping involves collecting data on product details, pricing, availability, and customer reviews.

Blinkit

Blinkit (formerly Grofers) is known for its quick grocery delivery services. Blinkit inventory scraping focuses on gathering data on product availability, pricing, and delivery options.

Dmart

Dmart is a popular retail chain in India, offering a variety of products. Dmart product data extraction involves scraping product information, prices, and stock levels.

How to Scrape Product Data: A Step-by-Step Guide

Step 1: Define Your Objectives

Before starting the web scraping process, it's crucial to define your objectives. Determine the specific data you need, such as product descriptions, prices, availability, or customer reviews. This clarity will help you design a more focused and efficient scraping strategy.

Step 2: Choose the Right Tools and Technologies

Selecting the appropriate tools and technologies is vital for successful data scraping. Some popular options include:

BeautifulSoup: A Python library for parsing HTML and XML documents.

Scrapy: An open-source web crawling framework in Python for extracting data.

Selenium: A browser automation tool that can scrape data from dynamic websites.

Step 3: Understand the Website Structure

Each e-commerce platform has a unique structure. Understanding the HTML structure of the target websites is crucial for effective scraping. Use browser developer tools to inspect elements and identify the HTML tags and classes containing the desired data.

Step 4: Handle Authentication and Anti-Scraping Measures

Many websites have anti-scraping measures like CAPTCHAs and IP blocking. Some platforms may require authentication to access certain data. It's essential to handle these challenges responsibly and ethically. Using proxy servers, rotating IP addresses, and respecting website terms of service are critical for smooth scraping operations.

Step 5: Develop the Scraping Script

Once you understand the website structure, you can develop the scraping script. Here's a basic outline for scraping product data:

• Send a Request: Use HTTP requests to access the target webpage.
• Parse the HTML: Use libraries like BeautifulSoup to parse the HTML content.
• Extract Data: Identify and extract the desired data fields.
• Store Data: Save the extracted data in a structured format, such as CSV or JSON.

Step 6: Data Cleaning and Validation

After scraping, the collected data may need cleaning and validation. This step involves removing duplicates, correcting errors, and formatting data consistently.

Step 7: Data Analysis and Visualization

With clean and validated data, you can perform analysis and visualize the findings. Tools like Tableau, Power BI, or Python libraries like Matplotlib and Seaborn can help create visual representations of the data.

Key Considerations and Best Practices

1. Legal and Ethical Considerations

Respect the terms of service of the websites you scrape. Some platforms may prohibit data scraping, while others may allow it under specific conditions. Always seek permission if required, and avoid scraping personal or sensitive information.

2. Data Accuracy and Consistency

Ensure that the data extracted is accurate and consistent. Cross-check the information from multiple sources if necessary, and keep your scraping scripts updated to account for changes in website structures.

3. Scalability and Efficiency

Design your scraping scripts to be scalable and efficient. This is especially important when scraping large volumes of data from multiple platforms. Implement techniques like parallel processing and asynchronous scraping to optimize performance.

4. Data Security and Privacy

When dealing with data, especially from e-commerce platforms, ensure that you handle it securely. Protect sensitive information and comply with data privacy regulations.

Benefits of Multi-Platform Product Data Scraping

1. Enhanced Competitive Intelligence

Scraping product data from multiple platforms provides a comprehensive view of the market, helping businesses stay ahead of the competition. It allows for detailed analysis of competitor pricing strategies, product availability, and customer preferences.

2. Improved Pricing Strategies

By accessing real-time data on product prices across different platforms, businesses can optimize their pricing strategies. This ensures competitive pricing and helps attract more customers.

3. Better Inventory Management

Understanding the availability of products on various platforms helps businesses manage their inventory more effectively. It enables timely restocking of popular items and avoids overstocking of slow-moving products.

4. Data-Driven Product Development

Insights gained from scraping product data can inform product development decisions. Businesses can identify popular products, understand customer preferences, and tailor their offerings accordingly.

5. Enhanced Customer Experience

By analyzing customer reviews and ratings, businesses can identify areas for improvement in their products and services. This leads to a better customer experience and increased customer satisfaction.

Challenges in Web Scraping for E-commerce

1. Dynamic and Complex Websites

Many e-commerce websites use dynamic content and complex structures, making it challenging to scrape data. This requires advanced techniques like using headless browsers and handling JavaScript rendering.

2. Frequent Website Updates

E-commerce platforms frequently update their website structures and layouts. This can break existing scraping scripts, requiring continuous monitoring and updating of the scraping tools.

3. Anti-Scraping Measures

Websites implement various anti-scraping measures, such as rate limiting, IP blocking, and CAPTCHAs. Navigating these challenges requires careful planning and ethical considerations.

4. Data Quality and Consistency

Ensuring data quality and consistency is crucial when scraping data from multiple platforms. Differences in data formats, terminologies, and categorizations can complicate data integration and analysis.

Future Trends in E-commerce Data Scraping

1. AI and Machine Learning Integration

The integration of AI and machine learning in data scraping is on the rise. These technologies can enhance data extraction accuracy, automate data cleaning processes, and provide deeper insights through advanced analytics.

2. Real-Time Data Scraping

Real-time data scraping is becoming increasingly important, especially in fast-paced industries like e-commerce. Businesses require up-to-date information to make timely decisions and stay competitive.

3. API-Based Data Access

While web scraping is a popular method for data extraction, more platforms are offering APIs for direct data access. APIs provide a structured and reliable way to obtain data, reducing the need for scraping.

4. Increased Focus on Data Privacy

As data privacy regulations become stricter, businesses must ensure compliance when scraping and using data. This includes handling personal data responsibly and securing customer information.

Conclusion

Scraping product data from Jiomart, BigBasket, Amazon, Blinkit, and Dmart provides invaluable insights for businesses aiming to optimize operations, understand market trends, and maintain a competitive edge. With the right tools and techniques, Actowiz Solutions offers comprehensive web scraping services for e-commerce, encompassing everything from Jiomart product data scraping to BigBasket price data scraping and beyond.

Whether you're looking for multi-platform product data scraping, Amazon price and product scraping, or Blinkit and Dmart data extraction, our expert team is equipped to handle your needs. We approach every project with a clear objective and a strong commitment to ethical and legal standards, ensuring that the data you collect is both reliable and compliant.

For businesses and individuals seeking scraping services for Jiomart and Amazon or other platforms, Actowiz Solutions is your trusted partner. We deliver efficient, ethical, and precise data extraction services tailored to your specific requirements. Embrace the future of e-commerce product data scraping with Actowiz Solutions and unlock the potential of your business through data-driven insights.

Contact us today to discover how we can support your data needs and help you achieve business success! You can also reach us for all your mobile app scraping, instant data scraper and web scraping service requirements.

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
                (
                    [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
                        )

                )

            [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
                        )

                )

            [location] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

            [postal] => Array
                (
                    [code] => 43215
                )

            [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
                        )

                )

            [subdivisions] => Array
                (
                    [0] => 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
                                )

                        )

                )

            [traits] => Array
                (
                    [ip_address] => 216.73.216.24
                    [prefix_len] => 22
                )

        )

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

                )

            [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] => 216.73.216.24
                    [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
)

Start Your Project

+1 ▼

Select Service Web Scraping Real-Time API Access Data Dashboards Datasets Review & Sentiment Analysis Price Monitoring Custom Solution

Select Industry E-Commerce Quick Commerce Food Delivery Travel & OTA Grocery & Retail Real Estate Others

Target Country Web Scraping Services Mobile App Scraping Web and App Scraping API Datasets Dashboard

A$лвR$C$CHF¥Kčkr€£HK$FtRp₪₹kr¥₩Mex$RMkrNZ$₱złleikrS$฿₺$R Budget Range $500 - $1,000 - Starter Budget (POC/Single Site) $1,000 - $2,500 - Basic Plan (Small Business Needs) $2,500 - $5,000 - Growth Phase (Multi-site/Data Volume Projects) $5,000 - $10,000 - Business-Scale (Automation/API Integrations) $10,000 - $25,000 - Enterprise Projects (Real-Time Systems, Global Data) $25,000 - $50,000 - Enterprise+ (Custom Dashboards, Ongoing Support) $50,000+ - Strategic Partnership (End-to-End Data Ops)

Additional Trust Elements

✨ "1000+ Projects Delivered Globally"

⭐ "Rated 4.9/5 on Google & G2"

🔒 "Your data is secure with us. NDA available."

💬 "Average Response Time: Under 12 hours"

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize

Explore Solutions Get a Custom Demo

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

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 Galido

Co-Founder / Head of Product at Upright Data Inc.

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.”

Iulen Ibanez

CEO / Datacy.es

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!”

Febbin Chacko

-Fin, Small Business Owner

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

Request Demo Access

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

Actowiz Insights Hub

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

All

Blog

Case Studies

Infographics

Report

Oct 28, 2025

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Discover how Scraping Consumer Preferences on Dan Murphy’s Australia reveals 5-year trends (2020–2025) across 50,000+ vodka and whiskey listings for data-driven insights.

Web Scraping Whole Foods Promotions and Discounts Data to Optimize Grocery Pricing Strategies

Discover how Web Scraping Whole Foods Promotions and Discounts Data helps retailers optimize pricing strategies and gain competitive insights in grocery markets.

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.

Scrape USA E-Commerce Platforms for Inventory Monitoring - Tracking 5-Year Stock Trends Across 50,000+ Online SKUs (2020–2025)

Scrape USA E-Commerce Platforms for Inventory Monitoring to uncover 5-year stock trends, product availability, and supply chain efficiency insights.

Oct 28, 2025

Scraping Consumer Preferences on Dan Murphy’s Australia - Unveiling 5-Year Trends Across 50,000+ Alcohol Listings (2020–2025)

Discover how Scraping Consumer Preferences on Dan Murphy’s Australia reveals 5-year trends (2020–2025) across 50,000+ vodka and whiskey listings for data-driven insights.

Oct 27, 2025

Scraping APIs for Grocery Store Price Matching - Comparing Walmart, Kroger, Aldi & Target Prices Across 10,000+ Products

Discover how Scraping APIs for Grocery Store Price Matching helps track and compare prices across Walmart, Kroger, Aldi, and Target for 10,000+ products efficiently.

Oct 26, 2025

How to Scrape The Whisky Exchange UK Discount Data to Track 95% of Real-Time Whiskey Deals Efficiently?

Learn how to Scrape The Whisky Exchange UK Discount Data to monitor 95% of real-time whiskey deals, track price changes, and maximize savings efficiently.

Read More

Web Scraping Whole Foods Promotions and Discounts Data to Optimize Grocery Pricing Strategies

Discover how Web Scraping Whole Foods Promotions and Discounts Data helps retailers optimize pricing strategies and gain competitive insights in grocery markets.

AI-Powered Real Estate Data Extraction from NoBroker to Track Property Trends and Market Dynamics

Discover how AI-Powered Real Estate Data Extraction from NoBroker tracks property trends, pricing, and market dynamics for data-driven investment decisions.

How Automated Data Extraction from Sainsbury’s for Stock Monitoring Improved Product Availability & Supply Chain Efficiency

Discover how Automated Data Extraction from Sainsbury’s for Stock Monitoring enhanced product availability, reduced stockouts, and optimized supply chain efficiency.

Read More

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.

Top 5 Brands Offering Deepest Discounts on Clothes This Navratri

Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.

Top 10 Most Ordered Grocery Items During Navratri 2025

Discover the top 10 most ordered grocery items during Navratri 2025. Explore popular festive essentials for fasting, cooking, and celebrations.

Read More

Scrape USA E-Commerce Platforms for Inventory Monitoring - Tracking 5-Year Stock Trends Across 50,000+ Online SKUs (2020–2025)

Scrape USA E-Commerce Platforms for Inventory Monitoring to uncover 5-year stock trends, product availability, and supply chain efficiency insights.

Maximizing Margins - Scraping Online Liquor Stores for Competitor Price Intelligence to Monitor Competitor Pricing in the Online Liquor Market

Explore how Scraping Online Liquor Stores for Competitor Price Intelligence helps monitor competitor pricing, optimize margins, and gain actionable market insights.

Real-Time Price Monitoring and Trend Analysis of Amazon and Walmart Using Web Scraping Techniques

This research report explores real-time price monitoring of Amazon and Walmart using web scraping techniques to analyze trends, pricing strategies, and market dynamics.

Read More

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Our team focuses on clear, transparent communication to ensure that every project is aligned with your goals and that you’re always informed of progress.

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Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations

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