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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] => 216.73.216.4 [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] => 216.73.216.4 [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 )
Apparel Color-Wise & Fabric-Wise Demand Analysis helps brands track trends, understand consumer preferences, and optimize inventory, design, and sales strategies.
Note: You’ll receive it via email shortly after submitting the form.
The fashion industry is increasingly driven by data as consumer preferences shift rapidly across seasons, regions, and demographics. Colors and fabrics play a critical role in influencing purchase decisions, making demand visibility essential for apparel brands and retailers. This case study highlights how Actowiz Solutions enabled Apparel Color-Wise & Fabric-Wise Demand Analysis using large-scale e-commerce data intelligence.
The client aimed to understand which colors and fabric types were trending, declining, or region-specific across multiple online marketplaces. However, fragmented data sources and inconsistent product attributes limited actionable insights. Actowiz Solutions delivered a robust data extraction and analytics framework that transformed raw e-commerce listings into structured demand intelligence. The result was improved forecasting accuracy, optimized inventory planning, and data-backed design decisions that aligned closely with real consumer demand.
The client is a mid-sized global apparel brand specializing in casual wear, seasonal fashion, and sustainable fabric collections. Operating across North America and Europe, the brand sells through its own e-commerce store as well as leading online marketplaces. Its target audience includes fashion-conscious millennials and Gen Z consumers who are highly influenced by trends, colors, and material preferences.
To remain competitive, the client needed advanced Apparel Demand Forecasting by Color & Fabric to align production volumes with real market demand. The brand’s merchandising and design teams required timely insights into color popularity, fabric performance, and category-wise demand shifts. Without centralized demand intelligence, the client faced excess inventory risks and missed trend opportunities, prompting the need for a data-driven solution.
Actowiz Solutions developed a comprehensive analytics framework centered on Apparel Color & Fabric Trend Analysis. Data was extracted from multiple e-commerce platforms and normalized to standardize color shades, fabric types, and product categories. This ensured accurate comparison and reliable demand signals across regions and platforms.
The second phase focused on automation and reporting. Scheduled data collection enabled continuous tracking of demand fluctuations, while custom dashboards visualized trends by season, geography, and category. These insights empowered stakeholders to respond quickly to changing fashion preferences.
One key challenge was inconsistent color naming conventions such as “off-white,” “ivory,” or “cream.” Actowiz resolved this by implementing intelligent mapping and clustering logic.
Another hurdle involved dynamically loaded product pages and anti-bot mechanisms. Advanced crawling techniques ensured uninterrupted data flow while maintaining compliance.
The third challenge was accurately identifying consumer interest signals. By designing systems to Scrape apparel color-wise demand data, Actowiz captured engagement indicators such as availability changes, listing frequency, and assortment depth to infer demand patterns.
Actowiz Solutions delivered a scalable data intelligence solution focused on Extract fabric-wise apparel demand data across multiple e-commerce platforms. The solution aggregated product-level data, categorized fabrics consistently, and linked demand indicators with seasonal and regional patterns.
Advanced analytics identified high-performing fabric-color combinations and early-stage trends, enabling proactive inventory and design decisions. Custom dashboards and data feeds integrated seamlessly with the client’s internal systems, ensuring usability across merchandising, supply chain, and marketing teams. The result was a unified, actionable view of apparel demand that supported faster decisions and reduced forecasting risk.
The client gained confidence in planning collections aligned with actual consumer demand.
“Actowiz Solutions gave us a clear understanding of how colors and fabrics perform in real markets. Their expertise in E-commerce Data Intelligence transformed our forecasting and design strategy.”
— Head of Merchandising, Global Apparel Brand
Actowiz Solutions bridges the gap between raw data and fashion intelligence.
This case study demonstrates how Actowiz Solutions empowered an apparel brand with actionable demand insights using Web scraping API, Custom Datasets, and instant data scraper technologies. By transforming e-commerce data into color-wise and fabric-wise intelligence, the client achieved smarter planning, reduced risk, and stronger market alignment.
Connect with Actowiz Solutions today to unlock data-driven success in fashion retail!
Actowiz extracts product listings, attributes, and availability data from e-commerce platforms and standardizes color and fabric classifications for accurate demand analysis.
Yes, historical and real-time data help identify seasonal shifts and recurring trends, improving seasonal assortment planning.
Absolutely. Datasets can be customized by geography, apparel type, gender, price range, and more.
The infrastructure supports millions of SKUs across multiple platforms, making it ideal for large and growing apparel brands.
With automated pipelines, clients receive updated insights frequently, enabling near real-time decision-making.
Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.
Find Insights Use AI to connect data points and uncover market changes. Meanwhile.
Move Forward Predict demand, price shifts, and future opportunities across geographies.
Industry:
Coffee / Beverage / D2C
Result
2x Faster
Smarter product targeting
“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”
Operations Manager, Beanly Coffee
✓ Competitive insights from multiple platforms
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%
Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place
Grab Experiences data scraping helps extract real-time activity listings, prices, locations, availability, and user ratings to analyze travel demand and experience trends accurately.
Scraping for Daily Pricing Integrity to ensure consistent brand pricing across Zepto and Instamart in every Delhi-NCR pincode with real-time accuracy.
Track tour assortment and new experiences in real time to optimize offerings, understand demand trends, and deliver unforgettable customer journeys.
Scraping Apparel Pricing & Discount Data helps brands track real-time prices, discounts, and offers across Ajio, Myntra, Nykaa Fashion, Flipkart, and TataCliq
Unlock consumer insights in SE Asia. Actowiz Solutions provides automated sentiment analysis scraping across Shopee, Lazada, and TikTok for retail market research.
Real-time grocery price changes across Walmart, Instacart and Target. Track top SKU drops, increases and hourly volatility with Actowiz Solutions.
Enhance deep learning performance with large-scale image scraping. Build diverse, high-quality training datasets to improve AI accuracy, object detection, and model generalization.
Uncover how data-driven strategies optimize dark store locations, boosting quick commerce efficiency, reducing costs, and improving delivery speed.
Analyze the MRP vs Selling Price Gap on Flipkart Minutes to uncover instant-commerce discounts, margin gaps, and real-time pricing behavior across categories.
Tracking New Supplier & Price Wars from IndiaMART – India to track emerging vendors, compare live prices, detect undercutting, and stay competitive.
Malaysia GrabFoods market analysis delivers insights into pricing trends, restaurant availability, demand patterns, and competitive dynamics
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