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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] => 216.73.216.101
                    [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
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            [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] => 216.73.216.101
                    [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 ▼

Vrbo Travel Datasets: Web Scraping Hotel, Flight Data

Vrbo travel datasets obtained through web scraping include hotel and flight data such as prices, reviews, ratings, locations, and availability. These datasets are valuable for analyzing travel trends, customer preferences, and competitive landscapes in the travel industry. Uncover:

  • Hotel Name
  • Location
  • Airline & Route
  • Departure Time
Get Started

Vrbo Travel Datasets

Vrbo Travel Datasets provide web-scraped hotel and flight data from multiple countries, including the USA, Italy, Germany, Canada, Australia, the UK, UAE, Spain, China, India, Japan, Switzerland, Qatar, Singapore, Ireland, Macao SAR, Luxembourg, Austria, Denmark, and Norway. This data encompasses flights, accommodations, transportation, and attractions, offering valuable insights into travel patterns and preferences for businesses. This includes flight itineraries, hotel bookings, car rentals, and expenses. By leveraging Vrbo travel data scraping, businesses can optimize routes, manage costs, and offer personalized recommendations. Additionally, Vrbo travel booking scraping allows for deeper insights into booking behaviors. Through Vrbo travel destination data extraction, businesses gain a comprehensive view of popular destinations and activities. Furthermore, Vrbo travel price monitoring helps businesses make informed decisions and enhance their services in the competitive travel industry.

Vrbo Datasets Explained

Vrbo datasets encompass information on hotels, flights, restaurants, and attractions, including prices, ratings, reviews, and locations. These datasets are valuable for analyzing travel trends, customer preferences, and competitive landscapes. Vrbo tourist attractions data scraping provides insights into popular destinations, pricing strategies, and traveler experiences, aiding businesses and researchers in the travel industry. We ensure accurate and up-to-date information on:

  • Destination
  • Departure Date
  • Return Date
  • Price
  • Location
  • Accommodation Type
  • Transport Type
  • Amenities
  • User Ratings
  • Reviews
  • Flight Number
  • Airline
  • Hotel Name
  • Check-in Date
  • Check-out Date
  • Room Type
  • Car Rental Company
  • Pickup Location
  • Drop-off Location
  • Attraction Name
  • Opening Hours
  • Tour Duration
  • Travel Package Name
  • Baggage Allowance
  • Route
Datasets-Explained
property_idtitlelocationcountryproperty_typebedroomsbathroomsmax_guestsprice_per_nightratingreview_countamenitiescancellation_policyavailabilitycheck_in_timecheck_out_timehost_namelisting_urlscraped_datelanguage_supportedcleaning_feemin_stayinstant_bookingpet_friendlywifi_availableair_conditioningparking_availableproperty_area
1Oceanfront Villa with Private PoolMaui, HawaiiUSAVilla438590 USD4.9120Pool, Kitchen, WiFi, Ocean ViewFree cancellationYear-round3:00 PM11:00 AMAloha Rentalshttps://www.vrbo.com/500110-07-2025English100 USD3 nightsYesYesYesYesYes3200 sq ft
2Cozy Cabin in the Smoky MountainsGatlinburg, TNUSACabin225210 USD4.884Fireplace, Hot Tub, DeckFlexibleAll seasons4:00 PM10:00 AMBear Lodge Co.https://www.vrbo.com/500210-07-2025English75 USD2 nightsNoNoYesNoYes1100 sq ft
Download
Flexible-Data-Delivery

Flexible Data Delivery

Tailored to your Vrbo hotel data extraction needs, we provide flexibility in selecting output formats, storage options, and delivery schedules:

  • Access food datasets in JSON, CSV, and other preferred formats;
  • Retrieve data through SFTP or integrate directly with cloud storage solutions like Google Cloud Storage, AWS S3, and more;
  • Choose one-time, monthly, quarterly, or bi-annually extract food datasets frequencies to suit your requirements.
Get Started

Secure Premium Industry Data with Ease

Premium-Industry-Datasets-on-Demand
Premium Industry Datasets on Demand

Access Actowiz's curated enterprise datasets for precise data insights, sourced by top web data specialists.

Efficiency Meets Expertise
Efficiency Meets Expertise

Save time; our team expertly extracts data for analysis, aligning with strategic business goals cost-effectively.

Tailored Data Solutions for Your Enterprise
Tailored Data Solutions for Your Enterprise

Receive tailored industry datasets; our flexible methods align with unique business needs for optimal decisions.

Commitment-to-Ethical-Data-Practices
Commitment to Ethical Data Practices

Actowiz leads Ethical Web Data Collection, upholding GDPR and CCPA, setting standards for responsible data practices./p>

Pricing Overview

Standard-Pricing

Standard Pricing

  • Standardized Data Offerings with readily accessible datasets.
  • Consistent Data Framework that ensures clarity and consistency.
  • Top-tier Data Integrity from the most intricate data channels.

Flexible Delivery Options:

  • Monthly Updates
  • Quarterly Deliveries
  • One-off Purchases
Get Started
Recommended
Custom-Pricing

Custom Pricing

  • Tailored Data Retrieval precisely aligned with your business needs.
  • Adaptable Data Framework crafted to fit your unique needs.
  • Scalable & Dynamic Offerings to ensure flexibility and scalability.
  • Streamlined Communication ensures smooth and instant communication.

Varied Delivery Options:

  • Daily Updates
  • Weekly Snapshots
  • Monthly Insights
  • Quarterly Reports
  • Customized Frequencies to Suit You
Get Started

Inclusive Benefits Across All Plans:

Get Started
  • Expert Data Extraction
  • Regulatory Assurance
  • Personalized Support
  • Broad Data Coverage

Why Choose Actowiz Solutions’ Datasets?

Assessing-Your-Data-Requirements

Assessing Your Data Requirements:

Our first step is to delve into your company's specifics and business goals, ensuring we align perfectly with your data aspirations.

Crafting-Tailored-Data-Solutions

Crafting Tailored Data Solutions

Leveraging our robust in-house web scraping tools, we design a bespoke strategy tailored to your data extraction needs.

Sample-Data-Preview

Sample Data Preview

Experience firsthand with a sample of our company data. Gauge its quality and familiarize yourself with our seamless data delivery mechanism.

Steadfast-Data-Streamlining

Steadfast Data Streamlining

Once aligned, we initiate regular data dispatches based on the frequency and specifications we've mutually agreed upon.

Frequently Asked Questions

Vrbo datasets are collections of data sourced from the Vrbo platform, encompassing information on various travel-related services such as hotels, flights, restaurants, and attractions. Vrbo flight data scraping typically includes details like prices, customer ratings, reviews, locations, amenities, and traveler types. They are used to analyze travel trends, customer preferences, and competitive landscapes. Researchers and businesses leverage Vrbo vacation rental data scraping to gain insights into popular destinations, pricing strategies, and traveler experiences. By examining this data, stakeholders can make informed decisions, enhance service offerings, and improve overall customer satisfaction in the travel and hospitality industry.
Choosing Vrbo datasets over web scraping offers significant benefits for businesses, researchers, and analysts. These datasets, sourced directly from Vrbo, ensure high accuracy and integrity, providing consistent and reliable information. Unlike Vrbo travel itinerary data scraping, which is prone to errors and can be affected by changes in website structure, official datasets maintain data quality and comprehensiveness. Moreover, using Vrbo datasets ensures legal and ethical compliance, avoiding potential issues associated with unauthorized scraping. Accessing pre-compiled datasets also saves considerable time and resources that would otherwise be spent on developing and maintaining scraping scripts. Additionally, Vrbo datasets often include valuable metadata and insights, such as sales trends, customer demographics, and detailed product attributes, which enhance the depth of analysis. Overall, leveraging Vrbo datasets provides a more efficient, legal, and thorough approach to obtaining high-quality data for market analysis, research, and strategic decision-making.
Obtaining Vrbo data through Actowiz Solutions sources involves leveraging various platforms and services that aggregate and provide detailed e-commerce information. Market research firms like Nielsen, Euromonitor, and Statista offer comprehensive reports and datasets on e-commerce trends, including Vrbo-specific data. Using our Vrbo travel reviews scraping services ensures access to accurate, up-to-date information, aiding in strategic decision-making and market analysis while maintaining compliance with legal and ethical standards.

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:

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

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×

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

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

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

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

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

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 Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
Product Image
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.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
Product Image
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!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
Product Image
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 icon

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
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Case Studies
Infographics
Report
Aug 25, 2025

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Getaround Vehicle Availability API Improved Chicago Car Access by 30%

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Top 10 Cities with the Most McDonald’s Locations in 2025

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Price Optimization vs Price Monitoring - 20% Margin Boost Revealed in 2025 Market Insights

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Starbucks Menu Price Fluctuation - Price Analysis of Starbucks Items in New York and LA

Track Starbucks Menu Price Fluctuation in New York and LA. Analyze latte, frappuccino, and cappuccino prices from 2020–2025 for smarter pricing and promotions.

Aug 24, 2025

Trending Discounts on Personal Care Products in Australia - Weekly Woolworths vs Coles Price Comparison

Compare weekly discounts on personal care products in Australia with our Woolworths vs Coles Price Comparison—stay updated, save money, and shop smart every week!

Aug 23, 2025

Benefits of Monthly Angi and Zillow Scraping for Service Aggregators

Unlock actionable insights with monthly Angi and Zillow scraping, helping service aggregators track trends, analyze competitors, and optimize business strategies.

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Getaround Vehicle Availability API Improved Chicago Car Access by 30%

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D2C Fashion Inventory Optimization Using Demand Data from Naver

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Cosmetic Pricing Intelligence in Daejeon Using Naver Product Scraping

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Top 10 Cities with the Most McDonald’s Locations in 2025

Discover the top 10 global cities with the highest number of McDonald’s locations in 2025 and explore trends in fast-food expansion worldwide.

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Monthly Tourism Flow Analysis via Hotel Booking Scraping in Sharjah

Monthly tourism flow in Sharjah analyzed via hotel booking scraping reveals visitor trends, occupancy rates, and booking patterns for data-driven tourism insights.

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India's Holiday Travel Surge Raksha Bandhan to Independence Day 2025

Explore India's holiday travel trends during the 2025 festive season—from Raksha Bandhan to Independence Day. Discover top destinations, travel tips, and booking insights.

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Price Optimization vs Price Monitoring - 20% Margin Boost Revealed in 2025 Market Insights

Price Optimization vs Price Monitoring reveals a 20% margin boost in 2025, offering insights to maximize profitability and pricing strategy.
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Skin Type-Based Skincare Insights in Korea Using Naver Beauty Categories

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AI-Powered Web Scraping Market Analysis 2025–2035 – Forecasts, Competitors & Use Cases

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