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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] => 216.73.216.126
                    [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] => 216.73.216.126
                    [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
)

Introduction

Black Friday has become one of the most critical sales periods for retailers worldwide. With millions of shoppers looking for deals simultaneously, pricing strategy and speed of execution are paramount. Traditional manual methods of tracking competitor prices and analyzing discounts are too slow and error-prone to meet the demands of today's hyper-competitive market.

The Real-Time Retailer Price Tracking APIs for Black Friday by Actowiz Solutions empower retailers to make 50% faster pricing decisions, monitor competitors instantly, and optimize offers in real time. By integrating these APIs into analytics and eCommerce platforms, businesses can maintain dynamic pricing, maximize margins, and respond to competitor moves instantly.

Between 2020 and 2025, Black Friday eCommerce sales have grown by over 120%, while the number of promotional campaigns per retailer has increased from an average of 5 to 18 per season, highlighting the need for automated, data-driven pricing intelligence. With Real-Time Retailer Price Tracking APIs for Black Friday, retailers gain an edge by accessing accurate, real-time pricing data, enabling smarter, faster, and more profitable decisions during the busiest shopping season of the year.

Why Real-Time Track Competitor Prices is Critical During Black Friday?

Monitoring competitor pricing in real time has become a cornerstone of retail success during Black Friday. With shoppers expecting instant deals and discounts, businesses can no longer rely on manual checks or outdated spreadsheets. The Real-Time Track Competitor Prices solution allows retailers to access live updates from competitors, including pricing, promotions, and stock availability.

From 2020 to 2025, the Black Friday retail landscape has grown increasingly complex. The average number of competitors monitored per retailer rose from 4 in 2020 to 12 in 2025, while pricing adjustments per day increased from 10 to 38, demonstrating the rapid pace at which retailers must react.

Year	Competitors Monitored	Pricing Adjustments/Day	Revenue Uplift (%)
2020	4	10	5%
2021	6	16	9%
2022	8	22	13%
2023	10	30	18%
2024	11	35	21%
2025*	12	38	25%

The insights from Real-Time Track Competitor Prices help retailers make rapid, data-driven decisions. Businesses can avoid overpricing that drives customers to competitors or underpricing that erodes margins. By comparing competitor offers instantly, retailers can implement dynamic discounts, adjust inventory, and optimize promotions.

Moreover, automated competitor tracking reduces operational errors, saves staff time, and enhances strategic decision-making. Retailers who adopt these solutions gain the ability to predict competitor behavior, respond to sudden promotional campaigns, and maintain visibility over multiple channels simultaneously.

In summary, Real-Time Track Competitor Prices is not just a tool; it's a strategic advantage that allows retailers to act decisively during the Black Friday rush. The growing scale of competition and the accelerated pace of price changes demand automated, real-time solutions to ensure profitability and customer satisfaction.

Leveraging Data Scraping API for Black Friday Deals and Discounts

A Data Scraping API for Black Friday deals and discounts enables retailers to automatically collect detailed information on promotions, discounts, and competitor pricing across multiple eCommerce platforms. This automation removes the inefficiencies of manual tracking and ensures businesses can respond to market trends in real time.

Between 2020 and 2025, the number of Black Friday deals tracked per retailer increased from 120 to 520, reflecting the rising complexity of the market. Simultaneously, the average discount variation per SKU increased from 5% to 18%, highlighting the need for precise, automated insights to maintain competitiveness.

Year	Deals Tracked per Retailer	Avg. Discount Variation (%)	Sales Uplift (%)
2020	120	5	4%
2021	180	7	7%
2022	250	10	11%
2023	340	13	15%
2024	430	16	19%
2025*	520	18	23%

By leveraging a Data Scraping API for Black Friday deals and discounts, retailers gain access to a comprehensive view of market offerings. This enables quick identification of high-demand products, trending discounts, and competitor strategies.

Automation ensures that promotions are monitored in real-time, which allows businesses to implement dynamic pricing strategies and optimize sales campaigns. It also improves data accuracy, reduces operational errors, and frees teams to focus on strategic decisions rather than manual data collection.

Additionally, the API supports analytics workflows by feeding accurate data into dashboards and predictive models. Retailers can analyze trends across regions, categories, and competitor segments, identifying opportunities to maximize revenue while maintaining margin integrity.

In essence, Data Scraping API for Black Friday deals and discounts is a critical tool for modern retailers, providing the insights and agility needed to thrive in a competitive, high-volume environment.

Boost your Black Friday sales with Data Scraping API for deals and discounts — automate insights and optimize pricing instantly!

Contact Us Today!

Real-Time Retail Price Tracking During Black Friday

The Real-Time Retail Price Tracking During Black Friday solution allows retailers to monitor thousands of SKUs across multiple channels in real time. This capability ensures pricing decisions are always based on the most current market conditions, eliminating guesswork and minimizing revenue loss.

From 2020 to 2025, adoption of real-time retail price tracking increased from 28% to 75% among top retailers, while price revision speed improved by 50%. Faster decision-making translates directly into higher sales, optimized margins, and enhanced competitiveness during the Black Friday peak.

Year	Retailers Using Real-Time Tracking (%)	Avg. SKU Updates/Day	Pricing Accuracy (%)
2020	28%	12	72%
2021	38%	18	77%
2022	49%	24	82%
2023	61%	30	87%
2024	69%	34	90%
2025*	75%	40	94%

By implementing Real-Time Retail Price Tracking During Black Friday, businesses can instantly identify pricing gaps, adjust promotions, and maintain competitive advantage. Real-time insights also support inventory management by indicating which products require restocking or discounting to optimize turnover.

Moreover, this API integration allows businesses to feed accurate, timely data into analytics dashboards, enabling predictive modeling and strategic planning. Retailers can forecast trends, evaluate competitor performance, and implement dynamic pricing models with confidence.

Overall, Real-Time Retail Price Tracking During Black Friday ensures retailers are agile, accurate, and ready to respond to the fast-paced, high-volume nature of Black Friday sales.

Retail Pricing Analytics During Black Friday

Retail pricing analytics during Black Friday provides actionable insights into pricing trends, competitor behavior, and promotional effectiveness. Businesses leveraging analytics can optimize pricing, plan inventory, and forecast demand to maximize revenue during the peak sales period.

Between 2020 and 2025, analytics adoption in retail grew by 150%, while revenue per SKU improved by 22%, demonstrating the tangible impact of data-driven pricing strategies.

Year	Analytics Adoption (%)	Revenue per SKU ($)	Price Optimization Accuracy (%)
2020	25%	12	70%
2021	36%	14	74%
2022	48%	16	78%
2023	59%	18	83%
2024	67%	20	88%
2025*	75%	22	92%

By using Retail pricing analytics during Black Friday, retailers can identify which products generate the highest ROI, optimize discount strategies, and plan effective bundle offers. Analytics also enables segmentation of consumers by behavior, location, and purchasing patterns, helping tailor promotions to maximize engagement and sales.

Additionally, analytics tools allow monitoring of competitor pricing patterns in real time, providing insights for immediate tactical responses. Retailers can adjust discounts dynamically, launch targeted campaigns, and maintain competitiveness across multiple marketplaces.

Implementing Retail pricing analytics during Black Friday ensures retailers are not only reactive but proactive, with predictive insights that allow them to anticipate consumer demand, identify pricing opportunities, and maximize profitability during the critical sales window.

Web Scraping API & Ecommerce & Marketplace Scraping

The Web Scraping API is a powerful tool that automates the collection of pricing, inventory, and promotion data from multiple eCommerce platforms. When combined with Ecommerce & Marketplace Scraping, retailers gain a comprehensive view of market dynamics, competitor behavior, and pricing trends during Black Friday.

From 2020 to 2025, the number of platforms monitored by top retailers grew from 5 to 18, while manual tracking efforts decreased by 65%, demonstrating the efficiency of automated scraping.

Year	Platforms Monitored	Manual Tracking Reduction (%)	Data Accuracy (%)
2020	5	0%	68%
2021	8	25%	73%
2022	11	40%	78%
2023	14	50%	83%
2024	16	60%	88%
2025*	18	65%	92%

By leveraging these APIs, retailers can monitor competitors at scale, analyze trends across multiple marketplaces, and make data-driven pricing decisions with speed and precision. Automated scraping reduces human error, saves time, and ensures data consistency, which is critical during high-volume Black Friday events.

Ecommerce & Marketplace Scraping also enables segmentation by region, category, and consumer demand, allowing for localized and targeted pricing strategies. This leads to better conversion rates, higher average order values, and improved ROI.

In conclusion, the combination of Web Scraping API and Ecommerce & Marketplace Scraping equips retailers with the tools to track competitors, optimize pricing, and implement agile strategies that maximize revenue and minimize risk during Black Friday.

Unlock competitive advantage with Web Scraping API & Ecommerce & Marketplace Scraping — monitor prices, analyze trends, and optimize sales effectively!

Contact Us Today!

Quick Commerce Data Scraping for Fast Black Friday Decisions

Quick Commerce Data Scraping allows retailers to capture real-time pricing, promotions, and inventory updates in high-velocity markets such as instant grocery or on-demand retail. Black Friday requires 50% faster pricing decisions, which only automated scraping solutions can deliver.

Between 2020 and 2025, adoption of Quick Commerce Data Scraping grew from 20% to 68%, while decision-making speed improved by 50%, directly influencing conversion rates and revenue outcomes.

Year	Adoption of Quick Commerce Scraping (%)	Decision Speed Improvement (%)	Revenue Impact (%)
2020	20%	0%	5%
2021	30%	15%	8%
2022	42%	25%	12%
2023	53%	35%	16%
2024	61%	45%	20%
2025*	68%	50%	25%

By automating quick commerce data collection, retailers gain the ability to monitor competitor pricing, adjust discounts dynamically, and react to real-time inventory changes. This ensures that high-demand products are competitively priced and available, maximizing sales during peak shopping hours.

Quick commerce scraping also feeds analytics platforms with up-to-date data, enabling predictive modeling for Black Friday trends. Retailers can forecast which SKUs will perform best, identify promotional opportunities, and optimize stock allocation to prevent stockouts or overstocking.

In conclusion, Quick Commerce Data Scraping empowers retailers with real-time intelligence, faster pricing decisions, and optimized operations during Black Friday, providing a significant competitive advantage in fast-paced retail environments.

How Actowiz Solutions Can Help?

Actowiz Solutions offers enterprise-grade Real-Time Retailer Price Tracking APIs for Black Friday, along with specialized solutions like Data Scraping API for Black Friday deals and discounts, Web Scraping API, and Quick Commerce Data Scraping. Our APIs deliver accurate, real-time insights into competitor pricing, promotions, and stock availability, enabling retailers to make faster and smarter pricing decisions.

Our solutions integrate seamlessly with analytics platforms, CRMs, and eCommerce dashboards, helping businesses implement Retail pricing analytics during Black Friday and monitor performance in real time. With Actowiz Solutions, companies can extract actionable intelligence, benchmark competitors, and optimize promotions to maximize ROI during peak sales events.

Whether you are a retailer, marketplace, or quick commerce provider, our APIs ensure agility, accuracy, and competitive advantage. By automating price tracking, data collection, and analytics, Actowiz empowers teams to act instantly and capitalize on Black Friday opportunities without manual delays.

Conclusion

Black Friday is a high-stakes sales period where every second counts. Retailers leveraging Real-Time Retailer Price Tracking APIs for Black Friday can make pricing decisions 50% faster, respond instantly to competitors, and maximize profit margins. Automated tools like Data Scraping API for Black Friday deals and discounts, Web Scraping API, and Quick Commerce Data Scraping provide the actionable insights needed to stay ahead in a competitive market.

From dynamic pricing to competitor benchmarking, these APIs transform decision-making by delivering real-time, accurate data across multiple platforms. Retailers adopting these solutions can optimize promotions, forecast demand, and increase revenue while minimizing errors.

Actowiz Solutions enables businesses to harness the power of real-time APIs and analytics for Black Friday and beyond. Contact Actowiz Solutions today to implement robust, automated price tracking and maximize your seasonal sales potential!

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
(
    [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] => 216.73.216.126
                    [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] => 216.73.216.126
                    [prefix_len] => 22
                    [network] => 216.73.216.0/22
                )

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

        )

    [city:protected] => GeoIp2\Record\City Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 4509177
                    [names] => Array
                        (
                            [de] => Columbus
                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
                        )

                )

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

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

        )

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

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

        )

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

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

        )

    [subdivisions:protected] => Array
        (
            [0] => GeoIp2\Record\Subdivision Object
                (
                    [record:GeoIp2\Record\AbstractRecord:private] => Array
                        (
                            [geoname_id] => 5165418
                            [iso_code] => OH
                            [names] => Array
                                (
                                    [de] => Ohio
                                    [en] => Ohio
                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
                                )

                        )

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

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

                )

        )

)

 country : United States

 city : Columbus

US

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

Start Your Project

+1 ▼

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

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

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

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

Additional Trust Elements

✨ "1000+ Projects Delivered Globally"

⭐ "Rated 4.9/5 on Google & G2"

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

💬 "Average Response Time: Under 12 hours"

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize

Explore Solutions Get a Custom Demo

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

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

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

Ecommerce

Q-Commerce

Travel & OTA

Food Delivery

Real Estate

Social Media

Trusted by Global Leaders – Secured by International Standards

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

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

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

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

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

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

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

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

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

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

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

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

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

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

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★

'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"

Thomas Galido

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

2 min

★★★★★

“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”

Iulen Ibanez

CEO / Datacy.es

1 min

★★★★★

“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”

Febbin Chacko

-Fin, Small Business Owner

1 min

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

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

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

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & planning

Monitor Prices, Availability & Trends -Live Across Regions

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

✔ Scraped Data: Price Insights Top-selling SKUs

Request Demo Access

Our Data Drives Impact - Real Client Stories

Blinkit | India (Retail Partner)

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

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

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

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

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

✔ Scraped Data, SKU availability, delivery time

Actowiz Insights Hub

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

All

Blog

Case Studies

Infographics

Report

Nov 06, 2025

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Scraping Top Electronics Discount Insights to reveal 10 key trends from Amazon, Walmart & Best Buy. Discover real-time data on deals, prices & savings.

Scrape Consumer Electronics D2C: Festival Price Trend Analysis

Scrape Consumer Electronics D2C: Festival Price Trend Analysis. Track Diwali & Independence Day price drops for phones, wearables & accessories with Actowiz Solutions

Dark Store Location Optimization - Data-Driven Strategy Explained

Uncover how data-driven strategies optimize dark store locations, boosting quick commerce efficiency, reducing costs, and improving delivery speed.

2025 Real Estate Trends: Rising Prices in Top Indian Cities with Real Estate Prices Data Insights from Magicbricks

Explore rising real estate prices in top Indian cities with Real Estate Prices Data Insights from Magicbricks for informed investment decisions.

Nov 06, 2025

Scraping Top Electronics Discount Insights - 10 Key Trends from Amazon, Walmart & Best Buy Data

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Nov 06, 2025

Scraping Noon Data for Track Prices, Ratings & Discounts — Get 99% Accurate Results in Real-Time

Scraping Noon Data for Track Prices, Ratings & Discounts with automated tools. Get real-time insights, 99% accuracy, and 3x faster price tracking.

Nov 05, 2025

How Real-Time Zepto Data Scraping API (95% Faster & 80% More Accurate) Helps Compare Grocery Prices Across Quick Commerce Platforms?

Compare grocery prices 95% faster and 80% more accurately using the Real-Time Zepto Data Scraping API for instant insights across quick commerce platforms.

Read More

Scrape Consumer Electronics D2C: Festival Price Trend Analysis

Scrape Consumer Electronics D2C: Festival Price Trend Analysis. Track Diwali & Independence Day price drops for phones, wearables & accessories with Actowiz Solutions

D2C Beauty Brand: Price & Discount Tracking on Nykaa and Amazon | Case Study by Actowiz Solutions

See how Actowiz Solutions helped a D2C beauty brand monitor 15K SKUs across Nykaa, Amazon & Myntra, boosting festive ROI by 36% with price intelligence.

Tracking Product Availability & Price Drops on Black Friday 2025 Across E-Commerce Platforms

Monitor product availability and price drops on Black Friday 2025 with real-time insights, helping retailers optimize inventory, pricing, and maximize sales effectively.

Read More

Dark Store Location Optimization - Data-Driven Strategy Explained

Uncover how data-driven strategies optimize dark store locations, boosting quick commerce efficiency, reducing costs, and improving delivery speed.

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

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

Top 5 Brands Offering Deepest Discounts on Clothes This Navratri

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

Read More

2025 Real Estate Trends: Rising Prices in Top Indian Cities with Real Estate Prices Data Insights from Magicbricks

Explore rising real estate prices in top Indian cities with Real Estate Prices Data Insights from Magicbricks for informed investment decisions.

Top 10 Grocery Chains Locations in Florida 2025 – Dominating by Store Reach and Coverage

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Adidas Price Discounts Analysis 2025 - Global Black Friday Trends and Consumer Insights from Data Scraping

Explore the Adidas Price Discounts Analysis 2025, uncovering global Black Friday trends, price fluctuations, and consumer insights through advanced data scraping techniques.

Read More

Our perks are irreplaceable

Time Zone Flexibility

Benefit from the ease of collaboration with Actowiz Solutions, as our team is aligned with your preferred time zone, ensuring smooth communication and timely delivery.

Clear Communication

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

Uncompromising Quality

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

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