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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] => 216.73.216.160
                    [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] => 216.73.216.160
                    [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
)
shopify-data-scraping-insights

In today's fast-paced e-commerce landscape, staying ahead of the competition requires timely access to crucial market insights. For businesses relying on Shopify as their e-commerce platform, keeping track of new products can make all the difference. But manually monitoring these updates can be a time-consuming and tedious task. Enter Actowiz Solutions, your ultimate partner in Shopify data scraping, ensuring you never miss a beat when it comes to newly added products to your favorite stores.

Why Shopify Data Scraping Matters

In today's digital age, data is the driving force behind successful businesses. It's the key to understanding customer behavior, market trends, and making informed decisions. For e-commerce businesses, staying on top of the latest products and trends is crucial for maintaining a competitive edge. This is where Shopify data scraping comes into play, and its importance cannot be overstated.

The E-Commerce Landscape and New Product Introductions

E-commerce platforms like Shopify have revolutionized the way businesses operate online. They offer a seamless way for entrepreneurs and established brands to set up their online stores, showcase their products, and reach a global audience. With the rise of dropshipping, print-on-demand, and various other business models, new products are being added to Shopify stores at an astonishing rate.

However, the sheer volume of products being added makes it challenging for businesses to manually track and monitor these changes. Keeping an eye on every store, every product category, and every newly added item can be overwhelming, especially as the e-commerce ecosystem continues to expand rapidly.

The Role of Shopify Data Scraping

This is where Shopify data scraping steps in as a game-changer. Data scraping, also known as web scraping, involves automating the process of extracting data from websites. In the context of Shopify, this means using specialized software or scripts to crawl through Shopify stores' pages, identifying and collecting information about newly added products.

But why does Shopify data scraping matter so much?

1. Real-time Insights

Real-time-Insights

Imagine being the first to know about a trending product that has just been introduced on a popular Shopify store. With data scraping, you can gain real-time insights into new product releases, giving you a competitive advantage. This information can help you adjust your inventory, marketing strategies, and even product offerings to align with emerging trends.

2. Faster Decision-Making

Faster-Decision-Making

In the world of e-commerce, speed matters. Being able to make informed decisions quickly can be the difference between capitalizing on a hot trend and missing out. With scraped data, you can make decisions based on actual market movements rather than relying on outdated or incomplete information.

3. Targeted Marketing

Targeted-Marketing

Knowing about new products in your niche allows you to create targeted marketing campaigns. Whether it's reaching out to potential customers interested in similar products or tailoring your ads to capitalize on emerging trends, scraped data empowers you to be strategic in your marketing efforts.

4. Inventory Management

Inventory-Management

For businesses involved in dropshipping or managing inventory, scraped data can be a lifesaver. You can adjust your inventory levels based on the popularity of new products, preventing stockouts and minimizing overstock situations.

5. Competitive Analysis

Understanding what your competitors are doing is essential for staying ahead. With scraped data, you can keep a close eye on your competitors' product offerings and pricing strategies, enabling you to adjust your own approach accordingly.

The Actowiz Advantage: Simplifying Shopify Data Scraping

In the ever-evolving world of e-commerce, staying competitive requires more than just a great product or an attractive website. It's about having access to timely and accurate insights that drive strategic decisions. For businesses relying on Shopify as their e-commerce platform, the Actowiz Advantage in Shopify data scraping offers a streamlined solution to extract new product data effortlessly, providing a cutting-edge edge in a fast-paced marketplace.

Understanding the Complexity of Shopify Data Scraping

Data scraping, especially from dynamic platforms like Shopify, can be a daunting task. The sheer volume of information, the constant updates, and the intricacies of website structures require a robust and technically adept approach. Manually monitoring multiple Shopify stores for newly added products is time-consuming and prone to errors. This is where Actowiz Solutions steps in, simplifying the entire process and offering businesses an effective way to stay informed.

Tailored Solutions for Precise Results

One of the standout features of the Actowiz Advantage is its ability to tailor solutions to meet the specific needs of each client. Every business is unique, and their data requirements can vary greatly. Actowiz collaborates closely with clients to understand their objectives, the stores they want to monitor, and the data points they need to extract. This customization ensures that the scraped data is not only accurate but also directly aligned with the client's goals.

The Shopify Data Fields You Need

In the bustling world of e-commerce, data is the lifeblood that fuels success. To ensure your business thrives, consider utilizing our specialized E-commerce Data Scraping services. When it comes to Shopify, one of the leading e-commerce platforms, keeping a pulse on newly added products is essential for staying competitive. To harness the power of this data, understanding the key data fields to extract is paramount. Here, we delve into the essential Shopify data fields you need to make informed decisions, and how extracting them can transform your e-commerce strategy.

1. Product Name

At the core of every product is its name, a powerful identifier that speaks volumes about what's on offer. Extracting product names from Shopify stores allows you to swiftly categorize and sort products, facilitating efficient data analysis and decision-making.

2. Product Description

Beyond the name, the product description provides valuable insights into the features, benefits, and unique selling points of each item. By scraping product descriptions, you gain a comprehensive understanding of what sets a product apart, enabling you to tailor your marketing efforts and customer communication effectively.

3. Price

Price is a crucial factor for both buyers and sellers. Extracting product prices allows you to monitor pricing trends, compare your offerings to competitors', and adjust your pricing strategy to remain competitive without compromising profitability.

4. Availability

Knowing whether a product is in stock or out of stock is vital for managing customer expectations and inventory levels. By scraping availability information, you can avoid disappointing customers with out-of-stock items and ensure you're always ready to fulfill orders.

5. Product URL

The product URL serves as a direct link to the product's page on the Shopify store. Extracting this URL allows you to access the product's details and images easily, facilitating deeper analysis and integration with other systems.

6. Image URL

In the visually-driven world of e-commerce, product images are worth a thousand words. Extracting image URLs enables you to visually identify products, which is especially valuable for quick assessments and categorization.

7. Timestamp of Addition

While not always visible on the front end of a Shopify store, the timestamp of when a product was added can provide valuable insights into the timing of new product introductions. This data can be particularly useful for understanding the cadence of new releases and aligning your strategies accordingly.

8. Product Category/Tags

The categorization of products helps in structuring your data and understanding the range of products available. Extracting product categories or tags allows you to analyze trends within specific product groups and tailor marketing efforts accordingly.

Why Extracting These Data Fields Matters

The benefits of extracting these Shopify data fields are manifold:

Informed Inventory Management: Price, availability, and timestamp data help you manage your inventory effectively, preventing stockouts and optimizing stock levels.

Strategic Marketing: Product names, descriptions, and image URLs enable you to create compelling marketing content and campaigns that resonate with your target audience.

Competitive Analysis: Pricing and availability data provide insights into your competitors' strategies, enabling you to adjust your pricing and promotions to maintain a competitive edge.

Trend Identification: Extracted data fields help you identify emerging product trends, empowering you to quickly adapt your product offerings to changing consumer preferences.

Time-Efficiency: With automated data scraping, you save time on manual monitoring, allowing you to focus on strategic decision-making.

The Web Scraping Process: Step-by-Step

In the digital landscape of e-commerce, extracting valuable insights from Shopify stores can provide a significant advantage. Web scraping is the key to unlocking this treasure trove of data. Let's embark on a step-by-step journey through the Shopify data scraping process, followed by how Actowiz Solutions brings their expertise to simplify and enhance this process.

Step 1: Define Your Data Needs

Before diving into web scraping, clarify your objectives. Determine the specific data fields you're targeting—product names, descriptions, prices, availability, URLs, images, and more. A clear understanding of your data needs will guide the entire scraping process.

Step 2: Choose Your Toolkit

Select the appropriate tools and technologies for web scraping. Python, a versatile programming language, offers libraries like Beautiful Soup and Scrapy that enable efficient data extraction. These tools simplify the process of navigating websites and gathering data.

Step 3: Inspect Website Structure

Before coding, examine the HTML structure of the Shopify store's web pages using browser developer tools. Identify the HTML elements containing the data you need. This inspection is crucial for writing accurate scraping code.

Step 4: Develop Scraping Code

Write the scraping code that navigates the website, locates relevant HTML elements, and extracts the desired data. Here's an example using Beautiful Soup:

Develop-Scraping-Code

Step 5: Automation and Pagination

If new products are spread across multiple pages, implement automation and pagination logic. Your script should navigate through these pages, ensuring you capture all relevant data.

Step 6: Format and Organize Data

The extracted data might be unstructured. Organize it into a structured format like a CSV file. Each row corresponds to a product, and columns represent different data fields.

Step 7: Quality Assurance

To ensure accurate data, perform quality checks. Compare the scraped data against the actual Shopify store to catch any discrepancies. Regular checks maintain the integrity of your insights.

Step 8: Schedule and Automate

For timely updates, automate the scraping process. Schedule the script to run at specified intervals, giving you fresh insights into new products added to the Shopify store.

Step 9: Enter Actowiz Solutions

Now, let's enhance this process with Actowiz Solutions. Actowiz brings their expertise to the table, making Shopify data scraping even more efficient and reliable.

Step 10: Actowiz Expertise

Custom Solutions: Actowiz Solutions tailors their approach to your specific requirements. They work closely with you to ensure the scraping process aligns with your business objectives.

Accuracy and Quality: Actowiz ensures the accuracy of scraped data through rigorous quality checks. This accuracy is essential for making informed decisions.

Automation and Regular Updates: Actowiz provides scheduled scraping options, ensuring that you receive timely updates on new products. This eliminates manual effort while keeping you informed.

Data Security: Actowiz prioritizes data security, handling your data with the utmost confidentiality and adhering to industry standards.

Benefits of Shopify Data Scraping with Actowiz Solutions

In the bustling realm of e-commerce, staying ahead of the curve is not a luxury—it's a necessity. The ability to access timely and accurate insights can mean the difference between success and obscurity. This is where Shopify data scraping steps in, and when coupled with Actowiz Solutions' expertise, it becomes a game-changing partnership that unlocks a multitude of benefits for your business. Let's delve into the transformative advantages of harnessing Shopify data scraping with Actowiz Solutions.

1. Time Efficiency

Manual monitoring of Shopify stores for new products is a resource-intensive endeavor. The constant need to visit websites, collect data, and update your records can tie up valuable human resources. With Actowiz Solutions, the process is automated, freeing up your team to focus on strategic tasks that drive growth.

2. Real-Time Insights

In the dynamic world of e-commerce, timing is everything. Shopify data scraping with Actowiz Solutions ensures you receive real-time updates on newly added products. This agility allows you to swiftly adjust your strategies, capitalize on emerging trends, and make decisions based on the most current information available.

3. Competitive Edge

Access to accurate and timely data gives you a significant advantage over your competitors. By being among the first to know about new product additions, you can tailor your marketing campaigns, adjust your inventory, and position yourself as a trendsetter in your industry.

4. Data-Driven Decision Making

Informed decisions are the cornerstone of successful businesses. Shopify data scraping provides you with a wealth of information to guide your strategies. To harness this potential effectively, consider utilizing our comprehensive Shopify Data Collection services. With our expertise, you can efficiently extract valuable insights, monitor market trends, and optimize your e-commerce strategies. With Actowiz Solutions, this data is accurate, reliable, and ready to be integrated into your decision-making processes.

5. Customization for Relevance

No two businesses are the same, and Actowiz Solutions understands that. They offer customization options that ensure the data you receive is tailored to your specific needs. Whether you're interested in additional data points or specific data fields, Actowiz can adjust the scraping process accordingly.

6. Unbiased Insights

Scraped data provides an objective view of the market. It's devoid of personal biases or subjective judgments that might color human observations. This impartial perspective can lead to more accurate trend analysis and strategic planning.

7. Data Security

When partnering with Actowiz Solutions, data security is a top priority. Your scraped data is handled with the utmost care and adheres to stringent security measures, ensuring the confidentiality and integrity of your information.

8. Expertise and Reliability

Actowiz Solutions brings years of experience and expertise to the table. Their proven track record in web scraping and data extraction ensures that you receive reliable and accurate insights, giving you the confidence to base your decisions on sound information.

9. Timely Updates

Actowiz Solutions offers flexible scheduling options, including daily updates. This means you can have your finger on the pulse of the e-commerce landscape, always armed with the latest information to steer your strategies in the right direction.

10. Strategic Focus

With the time and effort saved through automated Shopify data scraping, you can redirect your resources toward strategic initiatives that drive business growth. Whether it's refining your product offerings, enhancing customer experiences, or optimizing marketing campaigns, you can invest your energy where it matters most.

Conclusion

In the fast-evolving world of e-commerce, missing out on new product introductions can mean missing out on valuable opportunities. Actowiz Solutions takes the hassle out of Shopify data scraping, providing businesses with timely, accurate, and actionable insights. With a proven track record, customizable solutions, and a commitment to excellence, Actowiz is your partner in staying ahead of the competition and making data-driven decisions. Choose Actowiz, and unveil the hidden treasures of the e-commerce landscape. For your mobile app scraping, instant data scraper and web scraping services requirements, you can reach us too!

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] => 216.73.216.160
                    [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] => 216.73.216.160
                    [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

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💬 "Average Response Time: Under 12 hours"

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

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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.
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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.”
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Iulen Ibanez
CEO / Datacy.es
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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

Actowiz Insights Hub

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

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Sep 17, 2025

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Extract Festive Sale Data from Amazon, Flipkart & Reliance — 90% flash-sale alerts; 50+ brands analyzed

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Unlock Sephora’s Stock Secrets - Sephora Inventory & Stock Data Scraping API by Regions Tracks 90–98% Accuracy

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Sep 17, 2025

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Web Crawlers for Grocery Coupon & Discount Tracking Across Walmart, Kroger & Safeway

Web Crawlers for Grocery Coupon & Discount Data Tracking across Walmart, Kroger & Safeway to boost savings insights.

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Tracking Hermès Birkin Availability & Resale Pricing via Web Scraping – Powered by Actowiz Solutions

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Extract Festive Sale Data from Amazon, Flipkart & Reliance — 90% flash-sale alerts; 50+ brands analyzed

reveals how brands Extract Festive Sale Data from Amazon, Flipkart & Reliance with 90% flash-sale alerts and 50+ brands analyzed.

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Web Scraping Services in UAE – Historical Navratri Sales Data – 2020–2025 Discount Trends

Explore Historical Navratri Sales Data from 2020–2025 to track discounts, flash sales, and consumer trends across Amazon, Flipkart, and Myntra.

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Myntra vs Ajio Navratri discount scraping 2025

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