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Actowiz Metrics Now Live!

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GeoIp2\Model\City Object
(
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                    [geoname_id] => 4509177
                    [names] => Array
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                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                            [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
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            [country] => Array
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                    [iso_code] => US
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                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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            [location] => Array
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                    [longitude] => -83.0061
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            [postal] => Array
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            [registered_country] => Array
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                            [fr] => États Unis
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                            [ru] => США
                            [zh-CN] => 美国
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                                    [es] => Ohio
                                    [fr] => Ohio
                                    [ja] => オハイオ州
                                    [pt-BR] => Ohio
                                    [ru] => Огайо
                                    [zh-CN] => 俄亥俄州
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            [traits] => Array
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        )

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

        )

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
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                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
                            [de] => USA
                            [en] => United States
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                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
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                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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            [validAttributes:protected] => Array
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                    [3] => isoCode
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                )

        )

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

        )

    [traits:protected] => GeoIp2\Record\Traits Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [ip_address] => 216.73.216.150
                    [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
                        (
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                            [en] => Columbus
                            [es] => Columbus
                            [fr] => Columbus
                            [ja] => コロンバス
                            [pt-BR] => Columbus
                            [ru] => Колумбус
                            [zh-CN] => 哥伦布
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                )

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

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

    [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
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                )

        )

)

 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

In today’s fast-moving retail environment, businesses can no longer rely on delayed updates or manual monitoring to stay competitive. Hardware and home-improvement retailers like Screwfix update their product catalogs, prices, and stock levels multiple times a day, making it increasingly difficult for competitors, suppliers, and analysts to keep up. This is where automation becomes a necessity rather than a luxury. With the help of a Screwfix Data Scraping API, businesses can collect accurate product information in real time and transform raw listings into actionable market intelligence.

From tracking thousands of SKUs across tools, electricals, plumbing supplies, and building materials to monitoring flash discounts and regional stock variations, data-driven decision-making now depends on speed and precision. Whether it’s optimizing pricing models, preventing stockouts, or launching timely promotions, access to structured Screwfix data empowers retailers to stay one step ahead. Solutions like those offered by Actowiz Solutions enable enterprises to extract, process, and analyze this data at scale, reducing dependency on manual tracking and improving operational efficiency. By implementing automated pipelines, businesses gain consistent visibility into product trends, category demand, and competitor movement — all essential for surviving in an increasingly competitive eCommerce ecosystem.

Turning Online Listings into Business Intelligence

In the digital retail ecosystem, product listings are more than just catalogs — they are dynamic indicators of market behavior. By using Scrape Screwfix Product Listings Data combined with Ecommerce Data Scraping, businesses can continuously monitor thousands of SKUs across multiple categories, transforming scattered product pages into structured intelligence. This approach helps retailers understand which items gain traction, how often listings change, and which products receive promotional boosts during peak seasons.

From 2020 to 2026, online hardware retail saw a sharp rise in digital-first purchasing. Between 2020 and 2022, product listing updates on major platforms increased by nearly 35%, driven by pandemic-era supply chain disruptions. By 2024, automated listing analysis became a core strategy for brands managing more than 50,000 SKUs. By 2026, over 70% of large retailers are expected to rely on automated extraction tools to maintain pricing accuracy and stock alignment across sales channels.

Businesses that adopt automated listing intelligence gain the ability to forecast demand, spot trending items early, and eliminate blind spots in competitor analysis. Instead of reacting to market changes days later, companies can act instantly—repositioning inventory, adjusting marketing campaigns, and refining supplier negotiations.

Market Trend Snapshot (2020–2026)

Year	Avg. Listing Updates per Month	Retailers Using Automation (%)
2020	8,000	28%
2021	10,500	36%
2022	12,800	45%
2023	15,200	54%
2024	18,600	63%
2025	21,000	69%
2026	24,500	74%

Unlocking Hidden Patterns Across Product Categories

Understanding category-level performance is critical for retailers managing diverse hardware inventories. With Screwfix Category-Level Data Extraction, businesses gain visibility into how tools, electricals, plumbing, and construction supplies perform independently and collectively. This structured view helps companies identify growth segments, declining categories, and seasonal fluctuations that impact purchasing behavior.

Between 2020 and 2026, category dynamics shifted significantly. DIY tools surged between 2020 and 2022 as home improvement spending increased. From 2023 onward, professional-grade equipment gained momentum as construction activity rebounded. Retailers leveraging automated category extraction could identify these shifts months earlier than competitors relying on manual analysis.

By aggregating category-level insights, sellers can refine product assortments, allocate marketing budgets more effectively, and adjust supply chain planning. For example, if data shows that power tools outperform plumbing accessories during spring, businesses can stock accordingly and design targeted campaigns. This level of granularity also improves cross-selling strategies by highlighting which categories are frequently purchased together.

Category Performance Trends (2020–2026)

Year	Top Performing Category	Avg. Category Growth
2020	DIY Tools	18%
2021	Electrical Supplies	21%
2022	Gardening Equipment	24%
2023	Power Tools	19%
2024	Safety Gear	17%
2025	Professional Hardware	22%
2026	Smart Tools	26%

Mastering Competitive Pricing in Real Time

Price fluctuations are one of the biggest challenges in hardware retail. Through Scraping Screwfix Product Pricing Data, businesses gain real-time visibility into how prices shift across regions, seasons, and promotional cycles. Automated pricing intelligence allows companies to benchmark competitors instantly and implement dynamic pricing strategies that protect margins while remaining competitive.

From 2020 to 2026, online price volatility increased by nearly 40%, largely due to raw material cost fluctuations and supply chain instability. In 2020–2021, price adjustments happened weekly. By 2024, major retailers were updating prices daily, especially for high-demand tools and consumables. Businesses using automated scraping tools could detect these changes within minutes rather than days.

With real-time pricing insights, organizations can prevent revenue leakage, respond quickly to competitor discounts, and optimize promotional timing. This capability is especially valuable during peak sales periods like Black Friday, end-of-season clearance, and trade-specific promotions.

Price Change Frequency Trends (2020–2026)

Year	Avg. Price Updates per SKU	Businesses Using Dynamic Pricing
2020	12/year	32%
2021	18/year	39%
2022	24/year	48%
2023	36/year	57%
2024	52/year	65%
2025	68/year	71%
2026	84/year	78%

Building a Unified Product Intelligence System

Centralized product intelligence is the backbone of efficient retail operations. With Screwfix Product Data Extraction, businesses consolidate product descriptions, specifications, images, and availability into a single, reliable database. This unified system supports marketing, operations, and customer experience teams alike.

From 2020 to 2026, product data complexity increased dramatically as retailers expanded omnichannel strategies. In 2020, most product datasets included basic attributes like price and SKU. By 2024, enriched datasets featured technical specs, compatibility notes, customer reviews, and multimedia content. Companies using automated extraction tools were able to scale these datasets without adding operational overhead.

Unified product intelligence enables faster onboarding of new items, smoother catalog synchronization across platforms, and more accurate search and recommendation systems. For marketplaces and aggregators, it also reduces listing errors that lead to customer dissatisfaction.

Product Data Growth Trends (2020–2026)

Year	Avg. Attributes per Product	Retailers Using Unified Data
2020	12	34%
2021	16	41%
2022	20	49%
2023	26	58%
2024	32	66%
2025	38	72%
2026	45	79%

Eliminating Stock Gaps with Automated Monitoring

Inventory accuracy directly affects revenue and customer trust. Using a Screwfix Inventory & Stock Tracking API, businesses can monitor stock levels across multiple locations and sales channels in real time. This prevents costly stockouts, reduces overstocking, and ensures timely replenishment.

Between 2020 and 2022, stock volatility increased as global supply chains faced disruptions. Retailers without automated tracking systems experienced average stock inaccuracies of 18–22%. By 2024, companies using real-time monitoring reduced this gap to under 6%. Looking ahead to 2026, predictive stock analytics combined with automation is expected to cut inventory errors by more than 70%.

Automated stock tracking also supports smarter fulfillment strategies, such as redirecting orders to the nearest warehouse with available inventory. For multi-channel retailers, this ensures consistent customer experience whether purchases occur online or in-store.

Inventory Accuracy Trends (2020–2026)

Year	Avg. Stock Accuracy	Retailers Using Automation
2020	78%	31%
2021	82%	38%
2022	85%	45%
2023	90%	54%
2024	94%	62%
2025	96%	69%
2026	98%	76%

Powering Advanced Market Research with Structured Datasets

For analysts, manufacturers, and distributors, access to a Screwfix Hardware Product Dataset enables deep market research and strategic forecasting. Structured datasets allow organizations to analyze long-term trends, regional demand patterns, and product lifecycle performance.

From 2020 to 2026, the value of structured retail datasets increased significantly as predictive analytics and AI-driven forecasting became mainstream. In 2020, fewer than 30% of hardware suppliers used advanced analytics. By 2024, this number crossed 55%, and by 2026 it is projected to exceed 70%. Businesses leveraging detailed product datasets can forecast demand more accurately, optimize production schedules, and align distribution strategies with real market needs.

These datasets also support supplier negotiations by providing factual evidence of product performance across different regions and time periods. For investors and market researchers, they serve as a foundation for industry benchmarking and competitive intelligence.

Analytics Adoption Trends (2020–2026)

Year	Companies Using Advanced Analytics	Forecast Accuracy
2020	29%	68%
2021	34%	72%
2022	41%	76%
2023	49%	81%
2024	57%	85%
2025	64%	88%
2026	72%	92%

How Actowiz Solutions Can Help?

Actowiz Solutions specializes in delivering scalable, reliable, and compliant data intelligence services tailored for the retail and hardware sectors. Through Web Scraping Screwfix Data and the powerful Screwfix Data Scraping API, Actowiz empowers businesses to automate product tracking, pricing analysis, and inventory monitoring with unmatched accuracy.

From building custom dashboards to integrating scraped data into ERP, CRM, and BI tools, Actowiz Solutions ensures seamless data flow across business operations. Their expertise in handling high-frequency updates, large datasets, and complex website structures enables clients to stay ahead in highly competitive markets. Whether you are a retailer, distributor, or market research firm, Actowiz Solutions provides end-to-end support—from data collection to actionable insights—helping you transform raw data into strategic advantage.

Conclusion

In an era where speed and precision define success, automated data intelligence is no longer optional—it is essential. Businesses that invest in Web Scraping, Mobile App Scraping, and access to a Real-time dataset gain the ability to respond instantly to market changes, optimize pricing strategies, and ensure accurate stock management. A Screwfix Data Scraping API bridges the gap between static information and dynamic decision-making, empowering organizations to operate with confidence and clarity.

By partnering with Actowiz Solutions, businesses unlock the full potential of real-time product tracking and analytics, ensuring they remain competitive in a rapidly evolving digital marketplace.

You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!By leveraging Actowiz Solutions, your business stays ahead of the competition, armed with actionable insights from every marketplace.

GeoIp2\Model\City Object
(
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                            [zh-CN] => 哥伦布
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                    [geoname_id] => 6255149
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                            [fr] => Amérique du Nord
                            [ja] => 北アメリカ
                            [pt-BR] => América do Norte
                            [ru] => Северная Америка
                            [zh-CN] => 北美洲
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                )

            [country] => Array
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            [postal] => Array
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                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [subdivisions] => Array
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                            [iso_code] => OH
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                                    [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] => 216.73.216.150
                    [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
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                )

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

    [country:protected] => GeoIp2\Record\Country Object
        (
            [record:GeoIp2\Record\AbstractRecord:private] => Array
                (
                    [geoname_id] => 6252001
                    [iso_code] => US
                    [names] => Array
                        (
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                            [fr] => États Unis
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                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [locales:GeoIp2\Record\AbstractPlaceRecord:private] => Array
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                    [0] => en
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            [validAttributes:protected] => Array
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                    [0] => confidence
                    [1] => geonameId
                    [2] => isInEuropeanUnion
                    [3] => isoCode
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                )

        )

    [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
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                            [en] => United States
                            [es] => Estados Unidos
                            [fr] => États Unis
                            [ja] => アメリカ
                            [pt-BR] => EUA
                            [ru] => США
                            [zh-CN] => 美国
                        )

                )

            [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
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            [validAttributes:protected] => Array
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                    [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] => 216.73.216.150
                    [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)

Project Timeline * Immediate 1–3 Months Planning Phase

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:

Fintech / Digital Payments

Result

Accurate daily voucher &

cashback visibility across platforms

★★★★★

“Actowiz Solutions helped us automate daily voucher and cashback data collection across PhonePe, Paytm, Flipkart, and Hubble. The API-driven delivery significantly improved offer accuracy and operational efficiency.”

Product Manager, Fintech Platform (India)

✓ Daily voucher & cashback tracking via Push & Pull APIs

View Case Studies

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

View Case Studies

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×

View Case Studies

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

View Case Studies

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

View Case Studies

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

View Case Studies

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

View Case Studies

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

View Case Studies

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

Feb 09, 2026

The Race for "Now": Noon Minutes vs. Talabat Mart for the UAE’s Quick-Commerce Crown

Deep dive into the UAEs quick-commerce battle. Compare Noon Minutes and Talabat Mart pricing, speed, and market data with Actowiz Solutions.

Glovo Quick Commerce Price Monitoring in Barcelona

Actowiz Solutions tracks hyperlocal Glovo prices in Barcelona using high-frequency q-commerce scraping to monitor pricing, promos, and availability.

10 Ways Data Scraping Drives Business Growth & Market Intelligence

Discover 10 powerful ways data scraping boosts business growth, from competitive price intelligence and demand forecasting to inventory tracking and market monitoring.

UAE E-Commerce & Quick Commerce SKU Data Analysis - Price, Stock & Demand Insights

UAE E-Commerce & Quick Commerce SKU Data Analysis delivers insights on pricing, availability, trends, and performance to optimize catalogs and growth.

Feb 09, 2026

The Race for "Now": Noon Minutes vs. Talabat Mart for the UAE’s Quick-Commerce Crown

Deep dive into the UAEs quick-commerce battle. Compare Noon Minutes and Talabat Mart pricing, speed, and market data with Actowiz Solutions.

Feb 09, 2026

How Scraping Spices Product Data From Ecommerce Improves Demand Forecasting And Inventory Planning?

Scraping spices product data from ecommerce helps track prices, availability, brands, and demand trends for smarter sourcing decisions.

Feb 08, 2026

How Web Scraping Instacart Product Availability by Zip Code Helps Retailers Optimize Inventory

Learn how Web Scraping Instacart Product Availability by Zip Code helps retailers track stock, optimize inventory, and improve delivery efficiency

Read More

Glovo Quick Commerce Price Monitoring in Barcelona

Actowiz Solutions tracks hyperlocal Glovo prices in Barcelona using high-frequency q-commerce scraping to monitor pricing, promos, and availability.

Optimizing Customer Loyalty with Grab Rewards Data Scraping - Points, Tiers, and Rewards Analysis

Grab Rewards Data Scraping helps analyze reward points, offers, redemption trends, and user incentives to optimize loyalty and engagement strategies.

Tracking Grab Gift Card Demand and Usage with Web Scraping Grab Gift Card Data

Web Scraping Grab Gift Card Data helps track demand, usage patterns, pricing trends, and consumer behavior across digital platforms.

Read More

10 Ways Data Scraping Drives Business Growth & Market Intelligence

Discover 10 powerful ways data scraping boosts business growth, from competitive price intelligence and demand forecasting to inventory tracking and market monitoring.

Grocery Price Movement Tracker – Walmart, Instacart & Target

Real-time grocery price changes across Walmart, Instacart and Target. Track top SKU drops, increases and hourly volatility with Actowiz Solutions.

Enhancing Deep Learning Models With Image Scraping

Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.

Read More

UAE E-Commerce & Quick Commerce SKU Data Analysis - Price, Stock & Demand Insights

UAE E-Commerce & Quick Commerce SKU Data Analysis delivers insights on pricing, availability, trends, and performance to optimize catalogs and growth.

City-Wise SKU Demand and Pricing Trends - E-Commerce & Q-Commerce multi-Platforms

City-Wise SKU Demand and Pricing Trends - E-Commerce & Q-Commerce multi-Platforms, insights to compare demand, pricing, and growth patterns across cities

UK Grocery Market Analysis 2026 - Tesco, Asda, Sainsbury’s & Morrisons

UK Grocery Market Analysis 2026 - Tesco, Asda, Sainsbury’s & Morrisons delivers insights on pricing, market share, competition, and consumer trends shaping retail.

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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