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Actowiz Metrics Now Live!
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Actowiz Metrics Now Live!
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GeoIp2\Model\City Object
(
    [city:protected] => GeoIp2\Record\City Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

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

            [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
                        )

                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

        )

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

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

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

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

                    [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
                                )

                        )

                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

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

            [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
                        )

                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

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

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

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

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

            [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
                        )

                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

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

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [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
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.110
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

        )

    [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] => 216.73.216.110
                    [prefix_len] => 22
                )

        )

)
 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
)
Why-Should-You-Extract-ASOS-Product-Data-for-Key-Insights-into-Promotions-and-Pricing

Introduction

In the competitive world of fashion e-commerce, understanding a brand's pricing and promotional strategies is key to staying ahead. For retail, apparel, and fashion analytics companies, gaining insights into brands like ASOS can be especially valuable. ASOS, a global online fashion and cosmetic retailer, offers a vast and diverse range of products, often accompanied by promotions and competitive pricing. Extract ASOS product data can reveal essential insights into trends, pricing intelligence, and promotions that drive customer engagement.

This blog explains how and why extract ASOS product data can be an indispensable strategy for your business. We’ll dive into how data from ASOS can fuel competitive analysis, enhance pricing intelligence, support pricing strategies, and ultimately lead to a better understanding of product diversity on popular platforms.

Why Extract ASOS Product Data?

Why-Extract-ASOS-Product-Dataaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa

ASOS is a benchmark for many retailers and fashion brands, providing insights for those aiming to compete effectively in the online fashion market. As of 2024, ASOS has approximately 85,000 product listings that span a vast array of styles, brands, and categories. This diversity offers a rich dataset for analyzing consumer preferences, promotional trends, and pricing strategies.

The ability to extract ASOS product data is invaluable for businesses. With its detailed product descriptions, category variations, and frequent promotional events, ASOS data allows companies to identify trends and tailor their offerings accordingly. Tracking these trends is essential for aligning with market demands and forecasting changes, especially in a market where new styles emerge rapidly.

Moreover, ASOS pricing insights scraping can provide actionable intelligence on pricing strategies. By analyzing ASOS’s pricing patterns, competitors can refine their strategies— matching price points, identifying high-margin opportunities, or offering competitive discounts during peak sales periods. Scrape ASOS promotions data also reveals how frequently ASOS applies discounts, on which categories, and during which times of the year, allowing businesses to structure their promotional calendar better.

Using web scraping fashion retail ASOS allows quick and efficient data extraction from such a large site. Many businesses rely on API-based solutions to extract ASOS API product data, enabling seamless integration into analytics platforms. This data can then be used for competitive analysis, pricing optimization, and promotional planning, making ASOS a valuable reference point for fashion e-commerce businesses striving to optimize their strategies and offerings.

For any fashion brand or retailer seeking to thrive, extract popular e- commerce website data like ASOS is key to making data-driven decisions in a highly competitive market.

Key Insights from Extracting ASOS Data

Key-Insights-from-Extracting-ASOS-Data

Pricing Strategies: Gaining real-time access to pricing data reveals ASOS's price points, discounts, and seasonal promotions, allowing competitors to understand their pricing trends and adjust their own.

Promotional Analysis: Regular sales and promotional events, like flash sales or clearance discounts, are key drivers of ASOS's sales strategies. Scraping ASOS data helps you track these events and identify trends.

Product Diversity and Trends: With thousands of new items added monthly, tracking the product lineup on ASOS helps identify emerging fashion trends and popular brands, supporting businesses in managing inventory or launching new product lines.

Benefits of Extracting ASOS Product Data

Benefits-of-Extracting-ASOS-Product-Data

Using web scraping techniques or ASOS API product data extraction through Actowiz Solutions enables businesses to access vast amounts of data efficiently. This data provides several key benefits:

Competitive Promotional Pricing Data

In a highly competitive market, real-time promotional and pricing data is crucial. ASOS pricing and promotions web scraping provides insight into how ASOS structures its discounts, sales, and markdowns. Understanding these dynamics is critical for any business to align its promotional strategies.

For example, a retail brand may observe that ASOS frequently implements a “20% off everything” promotion during holiday seasons. By mirroring or slightly undercutting these offers, competitors can attract price-sensitive customers, retain engagement, and drive conversions.

Informed Pricing Strategy

Building an effective pricing strategy requires ongoing data on competitor pricing. By scraping ASOS pricing insights, businesses can analyze how ASOS prices similar products in different categories, track historical pricing changes and understand how ASOS dynamically adjusts prices based on demand.

A 2024 study shows that 63% of consumers prioritize price over brand loyalty when shopping online. Therefore, aligning pricing strategies with market leaders like ASOS can directly impact revenue.

Pricing Intelligence for Data-Driven Decisions

Scraping data from ASOS can offer in-depth pricing intelligence. This includes tracking changes in regular prices, promotional discounts, and the frequency and depth of markdowns. Businesses can use this intelligence to:

Optimize their pricing model: For example, by tracking average markdowns in a particular category, such as women's accessories, brands can adjust their pricing to compete directly with ASOS.

Plan inventory and promotions: Data on when and how frequently ASOS updates prices or adds new promotions helps retailers adjust their inventory accordingly, ensuring they are not overstocked or underprepared for demand shifts.

How ASOS Data Fuels Product Diversity Analysis

How-ASOS-Data-Fuels-Product-Diversity-Analysis

The ASOS catalog features various brands, including in-house collections and popular third-party brands. ASOS product diversity analysis involves categorizing and analyzing this vast array of products to understand which categories or brands are trending.

Tracking ASOS’s product diversity can help businesses answer questions like:

  • What are the most popular brands and categories?
  • How quickly does ASOS add or remove new products?
  • Which products are frequently promoted or discounted?

This level of analysis helps fashion retailers, designers, and brands stay ahead by adapting to trends early. For example, if ASOS suddenly promotes sustainable or eco-friendly fashion brands, a similar business might consider expanding its inventory of sustainable products.

Examples of Use Cases for ASOS Product Data Extraction

Examples-of-Use-Cases-for-ASOS-Product-Data-Extraction-

To understand how extracting ASOS product data can directly benefit a business, let’s explore some specific use cases.

Example 1: Pricing Comparison for a Fashion Startup

A fashion startup looking to position itself competitively might use price comparison by scraping ASOS data regularly. They can gather data on similar products regarding material, style, and category and benchmark their prices. By consistently monitoring ASOS’s pricing, the startup can avoid underpricing or overpricing, maintaining an attractive position in the market.

Example 2: Optimizing Promotions for E-commerce Competitors

An e-commerce platform that competes with ASOS may scrape data to understand ASOS’s promotional trends and adjust its marketing strategies. If ASOS tends to have monthly discounts on particular collections, the competitor can proactively run similar promotions to attract customers during peak ASOS promotional periods, ensuring a balanced competition.

Example 3: Inventory Management for a Multi-Brand Retailer

A multi-brand retailer could benefit from web scraping ASOS data to track which brands and products are frequently updated or removed. For example, if ASOS frequently rotates certain styles of footwear, this insight allows the retailer to refine its inventory and stock up on popular items.

The Importance of Competitive Promotional Pricing Data in 2024

The-Importance-of-Competitive-Promotional-Pricing-Data-in-2024

Data on competitive promotional pricing is more important than ever. In 2024, digital shoppers increasingly look for promotions and compare prices before purchasing. According to recent statistics, nearly 82% of online consumers check multiple sites before purchasing, meaning staying competitive on pricing is essential.

Scraping ASOS for promotional data provides insights into:

When ASOS applies discounts on seasonal items like winter jackets or summer apparel.

How deep discounts go on clearance items compared to regular inventory.

What categories receive frequent discounts, helping competitors understand consumer demand?

For instance, if ASOS offers 30% or more discounts on summer clothing during August, a competitor can plan a similar discount strategy to attract price-sensitive customers looking for end-of-season deals.

How Actowiz Solutions Can Help Extract ASOS Data

How-Actowiz-Solutions-Can-Help-Extract-ASOS-Data

Extracting data from complex sites like ASOS is not without challenges. Actowiz Solutions offers a comprehensive platform for extracting popular e-commerce website data, including real-time access to ASOS pricing and promotions web scraping capabilities. Actowiz uses advanced techniques such as:

Dynamic Content Extraction: For handling JavaScript-based content, Actowiz can render and extract information from complex web pages.

Data Cleansing and Validation: Actowiz performs automated data quality checks to ensure that the data is complete, accurate, and relevant.

API-Based Data Access: If you prefer integrating ASOS API product data, Actowiz provides API solutions for seamless data delivery and integration with your internal systems.

Overcoming the Challenges of Scraping ASOS Data

Overcoming-the-Challenges-of-Scraping-ASOS-Data

ASOS employs anti-scraping technologies, which can make data extraction challenging. Common challenges include:

CAPTCHA and Bot Protection: Actowiz uses CAPTCHA-solving techniques and smart IP rotation to bypass restrictions.

Dynamic Content and AJAX Loading: ASOS loads content dynamically, but Actowiz’s solution can render and extract the complete product catalog with minimal errors.

Frequent Site Structure Changes: Websites like ASOS frequently change their structure. Actowiz provides adaptive scraping solutions to adjust and continue seamless data extraction.

Integrating ASOS Data into Your Analytics

Integrating-ASOS-Data-into-Your-Analytics

Once you have access to ASOS product data, integrating it with analytics tools like Power BI, Tableau, or Google Data Studio can reveal actionable insights. This integration enables companies to visualize:

Over time, pricing trends allow for a dynamic pricing strategy.

Promotion effectiveness, showing how discounts correlate with demand.

Product diversity and new arrivals can influence purchasing and stocking decisions.

Conclusion: Drive Business Growth with ASOS Product Data

For fast fashion businesses, extracting ASOS product data offers a clear competitive advantage. From pricing intelligence and competitive promotional pricing data to ASOS product diversity analysis, web scraping enables companies to access the insights they need to adapt to market shifts.

Actowiz Solutions offers expert support in web scraping ASOS data, empowering businesses to obtain accurate, timely data and convert it into actionable strategies. Whether you're looking to gain an edge in pricing, boost your promotional effectiveness, or improve inventory management, Actowiz Solutions provides the tools and expertise to help you succeed.

Ready to extract valuable insights from ASOS data? Contact Actowiz Solutions to discuss how our web scraping service solutions can elevate your business. You can also reach us for all your mobile app scraping, data collection, web scraping, and instant data scraper service requirements.

GeoIp2\Model\City Object
(
    [city:protected] => GeoIp2\Record\City Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => names
                )

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

            [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
                        )

                )

        )

    [location:protected] => GeoIp2\Record\Location Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => averageIncome
                    [1] => accuracyRadius
                    [2] => latitude
                    [3] => longitude
                    [4] => metroCode
                    [5] => populationDensity
                    [6] => postalCode
                    [7] => postalConfidence
                    [8] => timeZone
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [accuracy_radius] => 20
                    [latitude] => 39.9625
                    [longitude] => -83.0061
                    [metro_code] => 535
                    [time_zone] => America/New_York
                )

        )

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

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

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [validAttributes:protected] => Array
                        (
                            [0] => confidence
                            [1] => geonameId
                            [2] => isoCode
                            [3] => names
                        )

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

                    [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
                                )

                        )

                )

        )

    [continent:protected] => GeoIp2\Record\Continent Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => code
                    [1] => geonameId
                    [2] => names
                )

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

            [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
                        )

                )

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

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

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

    [maxmind:protected] => GeoIp2\Record\MaxMind Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => queriesRemaining
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

        )

    [registeredCountry:protected] => GeoIp2\Record\Country Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                )

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

            [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
                        )

                )

        )

    [representedCountry:protected] => GeoIp2\Record\RepresentedCountry Object
        (
            [validAttributes:protected] => Array
                (
                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
                    [4] => names
                    [5] => type
                )

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

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                )

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [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
                )

            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.110
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

        )

    [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] => 216.73.216.110
                    [prefix_len] => 22
                )

        )

)
 country : United States
 city : Columbus
US
Array
(
    [as_domain] => amazon.com
    [as_name] => Amazon.com, Inc.
    [asn] => AS16509
    [continent] => North America
    [continent_code] => NA
    [country] => United States
    [country_code] => US
)

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From Raw Data to Real-Time Decisions

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

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Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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Iulen Ibanez
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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 & palniring

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 inights Top-slling SKUs

Our Data Drives Impact - Real Client Stories

Blinkit | India (Relail Partner)

"Actow's helped us reduce out of ststack 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

"Actow's helped us reduce out of ststack 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
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Case Studies
Infographics
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Aug 08, 2025

Discounted Devotion? Janmashtami Offer Mapping Across Quick Commerce Platforms

Actowiz Solutions compares Janmashtami offers on puja items & sweets across quick commerce platforms with real-time scraping & price tracking insights.

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Track Janmashtami Quick Commerce Banner Leaders – Dairy, Mithai & Puja Brands Insights

Discover which dairy, mithai & puja brands led Janmashtami quick commerce banners with Actowiz Solutions’ visibility scores & festive promotions insights.

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🇮🇳 India: Independence Day Sale Price Mapping – Flipkart vs Amazon

Actowiz Solutions compares Flipkart & Amazon prices during India’s Independence Day Sale 2025. Discover top deals, price drops & brand discount trends.

Aug 08, 2025

Discounted Devotion? Janmashtami Offer Mapping Across Quick Commerce Platforms

Actowiz Solutions compares Janmashtami offers on puja items & sweets across quick commerce platforms with real-time scraping & price tracking insights.

Aug 08, 2025

Grocery Discount Trends from Toters, JOKR, and Getir – Regional Analysis

Explore Toters, JOKR & Getir grocery discounts across regions—data insights, trends, and strategic analysis by Actowiz Solutions.

Aug 07, 2025

How to Track Weekly Flipkart Electronics Prices for Smarter Pricing Decisions & Competitive Edge?

Track weekly Flipkart electronics prices to stay competitive, adjust pricing smartly, and make data-driven decisions that boost visibility and conversions.

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Track Janmashtami Quick Commerce Banner Leaders – Dairy, Mithai & Puja Brands Insights

Discover which dairy, mithai & puja brands led Janmashtami quick commerce banners with Actowiz Solutions’ visibility scores & festive promotions insights.

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Price Tracking of Rakhi Gift Hampers – Did Discounts Really Deliver Value?

Discover how Actowiz Solutions scraped Rakhi gift hamper prices from Q-commerce platforms to reveal real festive discount insights with real-time pricing data.

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Real-Time Ride Fare Comparison: Uber vs DiDi vs Bolt Across 7 Countries

Compare Uber, DiDi & Bolt ride fares across 7 countries with real-time scraping insights. Discover surge patterns, price differences & platform efficiency globally.

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🇮🇳 India: Independence Day Sale Price Mapping – Flipkart vs Amazon

Actowiz Solutions compares Flipkart & Amazon prices during India’s Independence Day Sale 2025. Discover top deals, price drops & brand discount trends.

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Lazada Grocery App Dataset Analysis - Market Intelligence & Grocery Delivery Trends for American Startups

Explore Lazada grocery App dataset insights to uncover grocery delivery trends, pricing, and market gaps for American startups entering Southeast Asian markets.

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Raksha Bandhan & Independence Day 2025: How Holiday Travel Surges Impacted Flight and Hotel Pricing in India

Explore Actowiz Solutions' scraped data report on travel price surges in India during Raksha Bandhan & Independence Day 2025. Flight, hotel & booking insights inside.