Category-wise packs with monthly refresh; export as CSV, ISON, or Parquet.
Choose your region, and we’ll deliver clean, accurate store location datasets.
Launch instantly with ready-made scrapers tailored for popular platforms. Extract clean, structured data without building from scratch.
Access real-time, structured data through scalable REST APIs. Integrate seamlessly into your workflows for faster insights and automation.
Download sample datasets with product titles, price, stock, and reviews data. Explore Q4-ready insights to test, analyze, and power smarter business strategies.
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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] => 216.73.216.150 [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 ( [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] => 216.73.216.150 [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 )
Scalable fashion product data extraction from H&M, Zara, SHEIN & Myntra, enabling real-time trend insights, pricing analytics, and competitive benchmarking.
Note: You’ll receive it via email shortly after submitting the form.
The modern fashion industry moves at lightning speed, driven by rapidly evolving customer preferences, dynamic pricing shifts, and the constant introduction of fresh designs. To remain competitive, brands and market intelligence companies must access accurate, current, and structured product data across multiple platforms. The client partnered with Actowiz Solutions to transform raw retail product feeds into actionable insights delivered at scale. With our expertise, the customer gained an automated solution for centralized analysis, enabling data-backed trend recognition and strategic pricing decisions. Our system delivered complete visibility across fashion retail leaders, backed by advanced crawling logic and robust Fashion Product Data Extraction capabilities.
The client is an emerging fashion analytics enterprise focused on building intelligence dashboards for global fast-fashion markets. Their platform helps apparel brands, retailers, e-commerce sellers, and merchandisers detect trends, identify pricing gaps, and benchmark assortments from leading fashion retailers. Operating in a highly competitive industry, the client depends on accurate, continuously updated datasets for apparel categories, variants, colors, sizes, and pricing movements. They sought a partner capable of precise, scalable, and compliant Fashion Product Data Scraping From H&M, Zara, SHEIN & Myntra to strengthen their product discovery models and support real-time decision-making for fashion-driven product teams worldwide.
Multiple fashion platforms update styles and inventories daily, making structured parsing difficult.
The client needed accurate pricing for different countries in real time.
Tens of thousands of listings required scalable data pipelines and stable crawlers.
High-frequency tracking was essential to detect short-lived fashion spikes using Web Scraping H&M product data.
Consolidate all apparel data into a unified analytical structure.
Track discounts, promotions, and MSRP changes across platforms.
Enable designers and merchants to predict which styles gain momentum.
Eliminate manual data collection and improve feed refresh cycles.
Our architecture was engineered to extract, classify, and normalize high-volume product records from multiple storefronts simultaneously. Through layered spider logic, scalable clusters, and distributed schedulers, the system managed millions of product pages without downtime. Advanced HTML parsing techniques, product attribute mapping, and taxonomical alignment ensured consistency across diverse catalog layouts. Seamless export capabilities enabled dynamic feed creation formats, aligning with business intelligence dashboards while maintaining high reliability. This robust approach supported automated SHEIN Product Data Extraction workflows across regions and fashion collections.
We enriched raw data with metadata attributes—including brand hierarchy, pattern, fabric, seasonality, and discount windows—to uncover actionable insights. Our transformation pipelines integrated directly with the client’s analytical layer, enabling sentiment mining, pricing comparison dashboards, and category-level visibility. The system empowered stakeholders to improve stock decisions and capitalize on micro-trends.
Many retail platforms load products through scripts rather than static HTML. We implemented headless browser orchestrations to accurately capture catalogs and solve this issue linked to Myntra fashion product data scraping.
Frequent request throttling prevented scaling. We applied rotating proxies, intelligent request timing, and signature bypass mechanisms.
Parsing color, size, label, and fit data required custom extraction logic. Deep XPaths and OCR-based text recognition achieved structured accuracy.
Actowiz Solutions deployed an enterprise-grade extraction engine capable of parallel crawling, resilient data ingestion, and high-level enrichment workflows. Customized spiders tracked every category—from tops and dresses to accessories—while extracting product attributes, stock availability, material composition, and promotional offers. The platform monitored retail changes hourly, synced feeds with BI dashboards, and generated structured datasets for seamless use across analytical tools. Our approach delivered unmatched accuracy in trend recognition and competitive intelligence. This robust solution helped the client continuously Scrape Zara product & pricing Data while automating multi-source consistency checks, ensuring error-free insights and rapid data turnaround for time-sensitive retail decisions.
Comprehensive catalog collection eliminated gaps, reducing manual data entry.
What previously took weeks was now processed and visualized in hours.
The system scaled effortlessly across new categories and brands.
Enabled near-instant business response to discounts and competitor promotions via Ecommerce Data Scraping.
The client’s product teams leveraged automated insights to plan product assortments, identify best-selling designs earlier, and optimize their pricing strategy in competitive markets. The platform empowered retail analysts to track microtrends, correlate fashion patterns across geographies, and reduce decision-making cycles drastically. Data teams gained operational independence from scraping complexities, and leadership gained confidence in deploying a prediction-led retail strategy powered by real-time competitive visibility.
“Actowiz Solutions transformed how we aggregate and analyze fashion product feeds. Their platform gave us consistent, accurate, real-time visibility into emerging style trends and dynamic pricing movements across multiple retailers. We are now able to plan assortments with confidence and respond to competitor shifts instantly. The speed, scalability, and attention to detail exceeded our expectations.”
— Head of Data Engineering, Fashion Analytics Platform
Our experience with retail intelligence enables faster deployment cycles.
High-performance pipelines ensure future-proof integrations.
Data quality checks and rapid issue resolution maintain operational continuity while we Scrape Product Data from Fashion Websites using advanced crawlers and scalable Fashion Product Data Extraction frameworks.
Actowiz Solutions successfully built a robust, scalable infrastructure that empowered the client to lead the market with intelligent retail decisions. The case proved that consistent and accurate Fashion Product Data Extraction can drive measurable business value when combined with automation and real-time data analytics. Whether brands require a Web scraping API, Custom Datasets, or an instant data scraper, Actowiz Solutions remains a trusted partner in turning raw retail signals into strategic insights that accelerate growth.
Real-time fashion data allows businesses to respond instantly to customer preferences, pricing changes, and seasonal demand. Without timely information, brands risk missing trends or mispricing inventory.
Yes. Our scalable infrastructure supports thousands of simultaneous requests, dynamic rendering logic, and concurrent data pipelines to monitor multiple fashion platforms without performance issues.
Absolutely. We capture every attribute required for analytics—product descriptions, inventory, catalog categories, and variants, which are crucial for forecasting and merchandising.
Depending on requirements, updates can occur hourly, daily, or weekly. Our refresh frequency ensures accurate visibility into promotional events, pricing shifts, and new arrivals.
Actowiz Solutions follows best practices, ethical sourcing, and region-specific data compliance frameworks. We respect robots.txt, rate limitations, and operate structured, lawfully aligned data pipelines.
Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.
Find Insights Use AI to connect data points and uncover market changes. Meanwhile.
Move Forward Predict demand, price shifts, and future opportunities across geographies.
Industry:
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
Coffee / Beverage / D2C
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
Real Estate
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×
Organic Grocery / FMCG
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
Quick Commerce
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
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
Beverage / D2C
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
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
Real results from real businesses using Actowiz Solutions
In Stock₹524
Price Drop + 12 minin 6 hrs across Lel.6
Price Drop −12 thr
Improved inventoryvisibility & planning
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
"Actowiz's helped us reduce out of stock incidents by 23% within 6 weeks"
✔ Scraped Data, SKU availability, delivery time
With hourly price monitoring, we aligned promotions with competitors, drove 17%
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Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.
City-Wise SKU Demand and Pricing Trends - E-Commerce & Q-Commerce multi-Platforms, insights to compare demand, pricing, and growth patterns across cities
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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.
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.
Actowiz Solutions adheres to the highest global standards of development, delivering exceptional solutions that consistently exceed industry expectations