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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] => 216.73.216.24 [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] => 216.73.216.24 [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 )
Utilizing web data has become essential for travel companies to attract and retain customers. By harnessing the power of web data, these companies can gain valuable insights into the travel market, including regional dynamics, pricing trends, inventory availability, supply chain information, and consumer behavior. This data not only reveals what customers are currently doing but also uncovers crucial trends and even enables companies to anticipate their competitors' next moves.
In this blog, we will explore the following topics:
By understanding the challenges associated with data collection in the travel industry and learning how successful companies are leveraging web data, readers will gain valuable insights into the strategies and tactics that can drive success in the ever-evolving travel market.
The travel industry poses unique challenges when collecting data, particularly in the context of competitor intelligence. Two primary challenges arise when attempting to gather real-time travel data, such as pricing and bundled offerings, from target websites:
Competitor sites implementing rate limitations: When a single IP address generates a high traffic volume, competitor websites may detect this as data scraping activity and block or restrict access. These rate limitations hinder the collection of comprehensive and up-to-date data.
Accessing GEO-specific information: Many travel websites tailor their information based on the user's geographical location. This presents challenges for businesses operating in different regions as they may encounter distorted or restricted access to data when trying to gather information from websites in other geographies. For example, a hotel in New York may face difficulties accessing and analyzing pricing information from Japanese online travel agencies (OTAs) to understand how prices are displayed to Japanese consumers.
Overcoming these challenges requires innovative solutions and techniques to bypass rate limitations and access GEO-specific information effectively. By overcoming these obstacles, travel companies can acquire accurate and comprehensive data to inform their strategies and stay competitive.
Using an API for data collection, both in general and specifically in the travel industry, presents several challenges that need to be addressed:
Stale Data: One of the common challenges is retrieving stale data, which refers to obtaining information that is not the most up-to-date version available on the target site. This can be problematic for travel companies offering the most competitive deals based on the latest information. Relying on outdated data may result in missed opportunities or inaccurate pricing.
Concurrent Requests: Many APIs limit the number of active sessions a user can run simultaneously. These limitations can become a significant constraint for online travel agencies (OTAs) that need to scan numerous industry sites concurrently to stay competitive. It hinders their ability to efficiently gather comprehensive and real-time data across multiple sources.
API Call Limitations: Another challenge is restricting the number of API calls that can be made within a specific timeframe. Travel sites must carefully select the target data to retrieve and calculate precise batch sizes to optimize usage. Such limitations can hinder the company's ability to freely monitor the web for emerging travel trends and consumer behavior, limiting their data-driven opportunities.
Batch Size Limitations: Some target sites may limit the batch size for data requests. For instance, if a target site allows only 100 records per request, retrieving a significant amount of data will take multiple requests. This results in slower data retrieval, making it more challenging for companies to quickly pivot, react, and proactively respond to market shifts.
Addressing these API-related challenges requires companies to implement efficient strategies and techniques. They may need to optimize their data collection processes, carefully manage API call limits, and find ways to overcome stale data issues. By overcoming these obstacles, travel companies can effectively leverage web data to make informed decisions, identify market trends, and gain a competitive edge.
Company Profile: The hotel chain is a mid-sized establishment located in the US, primarily serving leisure customers. Their business heavily relies on online travel agencies (OTAs) for room bookings.
The Challenge: The hotel chain faces a common issue with OTAs adjusting prices without their knowledge, potentially impacting its brand reputation. To address this, they must collect accurate data from various third-party sites to gather evidence and enforce their operating agreement.
The Solution: The company has adopted a data collection network that utilizes a Rotating Residential IP network. This network assigns real individuals' IP addresses globally, ensuring unlimited concurrent requests. By routing each request through different devices, they can bypass rate limitations and obtain real-time data directly from the live target sites.
Key Benefits: With this solution in place, the hotel chain can now accurately monitor third-party vendors' pricing practices. They can identify instances where rates fall below their pre-defined and agreed-upon thresholds, enabling them to take appropriate actions to maintain pricing integrity.
By leveraging web data effectively, companies can overcome operational challenges and make informed decisions to optimize their performance in the competitive market landscape.
travel bundles, including flights, rental cars, and accommodations. They face numerous market competitors operating in a highly competitive and dynamic industry.
The Challenge: The OTA needs to gather real-time data on how their competitors present similar offers to diverse target audiences across geolocations. However, their head office being in Germany, poses difficulties in accessing specific sites due to IP blacklisting and regional restrictions.
The Solution: The company has implemented a Web Unlocker tool to overcome these challenges. This tool automates IP rotation and incorporates Machine Learning (ML) algorithms to overcome target site blocks and restrictions. It allows the OTA to access competitor sites without triggering rate limitations or encountering geographical restrictions.
Key Benefits: By leveraging the Web Unlocker tool, the OTA can stay competitive and tailor their travel bundles to their specific ecosystem. They receive real-time updates on changes in competitor offers, enabling them to strategically adapt and pivot their bundle offerings accordingly.
With enhanced access to web data and the ability to analyze competitive offers, the OTA gains a competitive edge. It can make data-driven decisions to optimize its services and meet the evolving needs of its target audience.
In conclusion, the travel industry faces various challenges when effectively collecting and utilizing web data. Issues such as stale data, concurrent requests, and limited access to competitor information in real-time can hinder a company's ability to gain a competitive advantage and increase market share.
However, companies can overcome these challenges by leveraging advanced solutions and technologies. A reliable network can enhance data collection capabilities and success rates. By accessing real-time and accurate information, companies can make informed decisions, stay ahead of the competition, and thrive in the crowded travel market.
Embracing data-driven strategies and utilizing web data effectively can empower travel companies to optimize operations, improve customer satisfaction, and drive business growth. With the right tools and insights, companies can make strategic moves, offer competitive pricing, optimize inventory, and cater to customer preferences, ultimately leading to success in the dynamic travel industry.
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