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Pick cities/countries and fields; we deliver a tailored extract with OA.
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] => 216.73.216.115 [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] => 216.73.216.115 [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 )
Actowiz Solutions specializes in Extract Flipkart API Product Data through advanced Web Scraping Flipkart APIs. Our expertise allows clients to scrape Flipkart product data efficiently across multiple countries, including the USA, UK, India, UAE, Japan, Italy, Germany, Canada, Australia, China, Switzerland, Qatar, Singapore, Ireland, Macao SAR, Luxembourg, Austria, Denmark, and Norway. We provide seamless Flipkart API Integration and utilize the Flipkart Scraping API for comprehensive Flipkart Product Scraping, ensuring that businesses have real-time access to critical product information. Additionally, our solutions encompass the Flipkart Order Data API, enabling clients to optimize inventory management and enhance customer experience. With our focus on ecommerce product data scraping, we empower businesses to make informed decisions based on accurate and timely data, maximizing their competitive advantage. Our commitment to ecommerce product data scraping ensures that clients stay ahead in a rapidly evolving market landscape.
Access product data from multiple countries effortlessly and efficiently.
Receive immediate notifications on product changes and pricing fluctuations.
Tailor scraping parameters to fit specific business needs and goals.
Analyze product performance and customer insights for informed decision-making.
Easily integrate with existing systems for smooth data management.
Navigate and manage scraped data through an intuitive dashboard.
Generate regular reports for tracking performance and market trends.
Ensure protection and confidentiality of sensitive ecommerce data at all times.
Integrate the Flipkart API to obtain real-time updates on product listings, availability, and pricing changes seamlessly.
Utilize the Flipkart Order Data API to streamline order processing, tracking, and fulfillment for efficient e-commerce operations.
Leverage comprehensive API data to analyze sales performance metrics, identify trends, and drive informed strategic decision-making processes.
Use customer behavior data from the API to enhance personalized product recommendations, thereby increasing customer engagement and boosting sales.
Implement the API to effectively monitor competitors’ products, pricing strategies, and market positioning for informed competitive advantage insights.
Description: Fetch detailed product information based on various criteria.
keyword (string): Search term to find products.
category (string): Filter by specific product categories.
sort (string): Sorting options (e.g., price, popularity).
page (int): Pagination for large datasets.
Response: JSON object containing product name, ID, price, rating, and description.
Description: Retrieve detailed information for a specific product using its unique ID.
product_id (string): Unique ID for the product.
Response: JSON object with product details including title, price, features, and customer reviews.
Description: Fetch customer reviews and ratings for a specific product.
Response: JSON object containing reviewer names, ratings, review texts, and helpfulness votes.
Description: Retrieve current offers, discounts, and availability for a specific product.
Response: JSON object with offer details, including price, discount percentages, and stock availability.
Description: Get recommendations for related products based on a specific product.
Response: JSON object containing a list of related product IDs and names.
Description: Retrieve a list of available product categories on Flipkart.
Response: JSON object containing category names and IDs for filtering products.
Description: Search for products based on various criteria like keywords and filters.
query (string): Search term to find products.
sort (string): Sorting options (e.g., price, rating).
Response: JSON object with a list of products matching the search criteria.
Description: Retrieve historical pricing data for a specific product.
Response: JSON object containing price changes over time, including dates and corresponding prices.
All responses are returned in JSON format for easy integration into your application.
from flask import Flask, jsonify, request app = Flask(__name__) # Mock data for demonstration products = { "1": { "name": "Wireless Headphones", "price": 59.99, "rating": 4.5, "description": "High-quality wireless headphones with noise cancellation.", "reviews": [ {"name": "Alice", "rating": 5, "text": "Great sound quality!"}, {"name": "Bob", "rating": 4, "text": "Comfortable and good battery life."} ], "offers": {"price": 49.99, "discount": 20, "available": True} }, "2": { "name": "Bluetooth Speaker", "price": 29.99, "rating": 4.0, "description": "Portable Bluetooth speaker with great sound.", "reviews": [], "offers": {"price": 25.99, "discount": 13, "available": True} } } @app.route('/products', methods=['GET']) def get_products(): keyword = request.args.get('keyword', '') category = request.args.get('category', '') sort = request.args.get('sort', 'price') page = int(request.args.get('page', 1)) # Filtering and sorting logic would go here (mock data only) return jsonify(products), 200 @app.route('/product/', methods=['GET']) def get_product(product_id): product = products.get(product_id) if not product: return jsonify({"error": "Product not found"}), 404 return jsonify(product), 200 @app.route('/reviews', methods=['GET']) def get_reviews(): product_id = request.args.get('product_id') product = products.get(product_id) if not product: return jsonify({"error": "Product not found"}), 404 return jsonify(product['reviews']), 200 @app.route('/offers', methods=['GET']) def get_offers(): product_id = request.args.get('product_id') product = products.get(product_id) if not product: return jsonify({"error": "Product not found"}), 404 return jsonify(product['offers']), 200 @app.route('/related', methods=['GET']) def get_related(): product_id = request.args.get('product_id') # Logic to find related products would go here (mock example) related_products = {"related": ["3", "4", "5"]} return jsonify(related_products), 200 @app.route('/categories', methods=['GET']) def get_categories(): # Mock category data categories = ["Electronics", "Books", "Home Appliances"] return jsonify(categories), 200 @app.route('/search', methods=['GET']) def search_products(): query = request.args.get('query', '') sort = request.args.get('sort', 'price') page = int(request.args.get('page', 1)) # Mock response for search (replace with actual search logic) search_results = {"results": products} return jsonify(search_results), 200 @app.route('/price-history', methods=['GET']) def get_price_history(): product_id = request.args.get('product_id') # Mock price history data price_history = [ {"date": "2024-01-01", "price": 59.99}, {"date": "2024-02-01", "price": 49.99}, ] return jsonify(price_history), 200 if __name__ == '__main__': app.run(debug=True)
Optimize your product data with our Flipkart Scraping API designed for seamless Flipkart API Integration. Our solution enables you to scrape Flipkart product data efficiently, providing accurate and comprehensive insights into product listings, pricing, and availability. With advanced features like Flipkart Product Scraping and Flipkart Customer Reviews Scraping, you can enhance your competitive edge and make informed decisions. Leverage the Flipkart Product Data API for real-time data retrieval, ensuring your inventory management is always up-to-date. Our Flipkart Order Data API streamlines order processing, while Automated Flipkart Data Extraction simplifies the entire data collection process, saving you valuable time and resources.
✨ "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"
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
Build and analyze Historical Real Estate Price Datasets to forecast housing trends, track decade-long price fluctuations, and make data-driven investment decisions.
Actowiz Solutions scraped 50,000+ listings to scrape Diwali real estate discounts, compare festive property prices, and deliver data-driven developer insights.
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.
Discover how Competitive Product Pricing on Tesco & Argos using data scraping uncovers 30% weekly price fluctuations in UK market for smarter retail decisions.
Discover how Italian travel agencies use Trenitalia Data Scraping for Route Optimization to improve scheduling, efficiency, and enhance the overall customer experience.
Discover where Indians are flying this Diwali 2025. Actowiz Solutions shares real travel data, price scraping insights, and booking predictions for top festive destinations.
Actowiz Solutions used scraping of 250K restaurant menus to reveal Diwali dining trends, top cuisines, festive discounts, and delivery insights across India.
Actowiz Solutions tracked Diwali Barbie resale prices and scarcity trends across Walmart, eBay, and Amazon to uncover collector insights and cross-market analytics.
Score big this Navratri 2025! Discover the top 5 brands offering the biggest clothing discounts and grab stylish festive outfits at unbeatable prices.
Discover the top 10 most ordered grocery items during Navratri 2025. Explore popular festive essentials for fasting, cooking, and celebrations.
Discover how Scrape Airline Ticket Price Trend uncovers 20–35% market volatility in U.S. & EU, helping airlines analyze seasonal fare fluctuations effectively.
Quick Commerce Trend Analysis Using Data Scraping reveals insights from Nana Direct & HungerStation in Saudi Arabia for market growth and strategy.
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