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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 )
Case study on how we built automated hotel review data extraction from Goibibo and MakeMyTrip, enabling real-time insights for a global travel brand.
Note: You’ll receive it via email shortly after submitting the form.
In the digital-first travel industry, customer reviews play a crucial role in shaping booking decisions, brand perception, and service optimization. Online travel agencies host millions of reviews, making it difficult for brands to manually track and analyze customer sentiment at scale. Actowiz Solutions partnered with a global travel brand to automate the collection and analysis of hotel reviews across India’s leading travel platforms.
By implementing Hotel Review Data Extraction from Goibibo & MakeMyTrip, we enabled the client to capture real-time guest feedback, ratings, and experience trends across thousands of hotel listings. The solution transformed unstructured review data into structured, actionable insights, helping the brand improve hotel partnerships, enhance customer experience strategies, and monitor service quality consistently. This case study highlights how Actowiz Solutions delivered a scalable, accurate, and automated data extraction system to empower smarter, data-driven decisions in the hospitality ecosystem.
The client is a globally recognized travel and hospitality brand offering hotel bookings, travel packages, and destination-based services to millions of customers worldwide. Operating across multiple regions, the brand partners with hotels ranging from budget accommodations to premium properties. Their platform prioritizes customer experience, transparency, and service quality.
With a strong presence in the Indian travel market, the client relied heavily on customer reviews and ratings to assess hotel performance and traveler satisfaction. However, manually collecting insights from multiple platforms became increasingly inefficient. To overcome this challenge, the client sought a technology partner capable of Scrape Goibibo & MakeMyTrip Hotel Review Data at scale. Actowiz Solutions was selected for its expertise in travel data extraction, automation, and analytics-ready delivery, enabling the client to stay competitive and customer-centric.
We began by analyzing Goibibo and MakeMyTrip’s review structures, rating systems, and metadata formats. Each platform had unique layouts, review filters, and pagination logic. Our team designed custom data extraction flows to ensure consistent data capture while Scraping MakeMyTrip Hotel Review Data and Goibibo reviews. This approach ensured accurate extraction of review text, ratings, dates, traveler types, and hotel identifiers.
Actowiz Solutions implemented an automated scraping and processing pipeline that continuously collected new and updated reviews. Intelligent scheduling ensured optimal crawl frequency without impacting platform stability. Data validation and normalization layers cleaned the extracted content, enabling seamless integration with the client’s analytics dashboards. This strategy allowed the client to access fresh, reliable insights without manual intervention.
Both platforms used dynamically loaded reviews and infinite scrolling. We deployed headless browser automation and smart pagination handling to extract complete Web Scraping hotel customer feedback Data without loss.
To overcome detection mechanisms, we implemented adaptive request rotation, IP management, and behavioral simulation techniques to maintain uninterrupted data flow.
Reviews appeared in multiple languages and tones. We applied text preprocessing and tagging mechanisms to preserve sentiment accuracy and contextual relevance for downstream analytics.
Actowiz Solutions delivered a fully automated, scalable review extraction framework tailored to hospitality intelligence. Using Extract Goibibo Hotels Data, we collected verified guest reviews, ratings, timestamps, hotel metadata, and traveler categories. The solution standardized data across platforms, ensuring consistency and accuracy.
The system delivered structured datasets via APIs and cloud-based feeds, enabling the client to plug insights directly into BI tools and sentiment analysis engines. Automated workflows reduced manual effort, improved review coverage, and delivered near real-time updates. The solution was designed for scalability, allowing seamless onboarding of new hotels, cities, and future travel platforms.
“Actowiz Solutions helped us unlock the true value of hotel reviews across Goibibo and MakeMyTrip. Their automated extraction solution delivers accurate, timely insights that directly impact our service quality and partner strategy.”
— Director of Customer Experience, Global Travel Brand
Actowiz Solutions combines technical excellence with industry knowledge to deliver reliable travel intelligence solutions.
This case study demonstrates how Actowiz Solutions empowered a global travel brand with automated review intelligence using Web scraping API, Custom Datasets, and an instant data scraper. By transforming unstructured hotel reviews into actionable insights, the client enhanced customer satisfaction, improved hotel partnerships, and strengthened competitive positioning. Actowiz Solutions continues to help travel brands turn data into smarter decisions and measurable business growth.
We extract review text, ratings, dates, traveler types, hotel names, locations, and platform-specific metadata.
Update frequency can be customized—ranging from real-time to daily or weekly refresh cycles.
Yes, we follow ethical scraping practices and client-specific compliance requirements.
Absolutely. The architecture supports expansion to platforms like Booking.com, Agoda, and TripAdvisor.
Data is delivered via APIs, cloud storage, dashboards, or custom formats compatible with analytics tools.
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%
Actionable Blogs, Real Case Studies, and Visual Data Stories -All in One Place
Deep dive into the UAEs quick-commerce battle. Compare Noon Minutes and Talabat Mart pricing, speed, and market data with Actowiz Solutions.
Actowiz Solutions tracks hyperlocal Glovo prices in Barcelona using high-frequency q-commerce scraping to monitor pricing, promos, and availability.
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 delivers insights on pricing, availability, trends, and performance to optimize catalogs and growth.
Scraping spices product data from ecommerce helps track prices, availability, brands, and demand trends for smarter sourcing decisions.
Learn how Web Scraping Instacart Product Availability by Zip Code helps retailers track stock, optimize inventory, and improve delivery efficiency
Grab Rewards Data Scraping helps analyze reward points, offers, redemption trends, and user incentives to optimize loyalty and engagement strategies.
Web Scraping Grab Gift Card Data helps track demand, usage patterns, pricing trends, and consumer behavior across digital platforms.
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.
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 delivers insights on pricing, market share, competition, and consumer trends shaping retail.
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