{"id":5458,"date":"2025-07-20T18:06:44","date_gmt":"2025-07-20T16:06:44","guid":{"rendered":"https:\/\/tragento.com\/?p=5458"},"modified":"2025-07-20T18:06:44","modified_gmt":"2025-07-20T16:06:44","slug":"hotel-mapping-key-challenge-in-accommodation-distribution-and-how-to-solve-it","status":"publish","type":"post","link":"https:\/\/tragento.com\/en\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\/","title":{"rendered":"Hotel mapping \u2013 the key challenge in accommodation distribution and how to solve it"},"content":{"rendered":"<p class=\"wp-block-paragraph\"><strong>Hotel Mapping<\/strong> is one of the most common challenges faced by travel agencies and OTA platforms in accommodation distribution. It involves the process of connecting and reconciling hotel data from various sources (wholesalers, OTAs, <strong>bedbankova<\/strong> etc.) into a unique record. Without quality <strong>Hotel mapping<\/strong>, Duplicate offers and inconsistent information can appear, confusing travellers and impacting the agency's business results. Below, we explain the problems that arise with hotel mapping, provide a specific example of how poor mapping affects users and revenue, and present the best-known tools for solving this problem (GIATA, Gimmonix, DataBindR, Vervotech, etc.). Finally, we highlight why quality mapping is crucial for agencies that aggregate multiple accommodation providers and want to offer the best prices on the market.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What is the problem with hotel mapping?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Hotel Mapping<\/strong> serves to merge multiple IDs for the same property (hotel) from different suppliers into a single, accurate record. The problem arises when this mapping is performed incorrectly or is not up-to-date \u2013 then the same hotel can appear multiple times under different names or information on the platform. Also, without mapping, there can be <em>Incorrect data<\/em> (e.g. wrong address, incorrect hotel name) and <em>poor room to object linking<\/em> (room mapping), where room categories do not align between systems. In practice, this causes a number of difficulties:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Duplicates on offer:<\/strong> The same hotel is displayed multiple times under different names or codes. This confuses the user, makes searching difficult, and can lead to booking abandonment. For example, a traveller on an OTA platform might see <em>two offers for the same hotel<\/em> \u2013 one with a slightly different name or address \u2013 so they aren\u2019t sure which one to choose, which erodes trust and often results in the booking being abandoned.<\/li>\n\n\n\n<li><strong>Inaccurate or incomplete information<\/strong> If the mapping isn't done well, it can lead to <strong>misidentification of the hotel<\/strong> \u2013 e.g. guests being shown the wrong location or outdated room availability. Errors can also occur, such as linking the wrong room to a hotel, leading to incorrect bookings. Such errors degrade the user experience, create dissatisfied guests, and increase the cancellation rate.<\/li>\n\n\n\n<li><strong>Higher operating costs<\/strong> Without an automated tool, agencies often try to combat duplicates manually. As the number of hotel suppliers and inventory grows, manual data reconciliation becomes unsustainable \u2013 it consumes a lot of working hours and money. Each mapping error can result in additional costs (e.g., covering an incorrectly booked hotel, compensating a guest, etc.), which according to some analyses can amount to as much as <strong>\u20ac1,500 per case<\/strong> for a major OTA agency.<\/li>\n\n\n\n<li><strong>Poor user experience and loss of trust:<\/strong> Passengers are expecting <strong>simple and accurate<\/strong> accommodation searches. If they encounter duplicate results, inconsistent descriptions, or booking errors on your platform, they will likely turn to competitors offering more reliable information. This means a loss of future customers and a lack of repeat bookings due to damaged trust.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The combination of these problems directly impacts the revenue of a tourism company. Fewer confirmed bookings, more cancellations, and additional operational costs due to poor mapping reduce profitability. The solution is the implementation of a robust, <strong>AI-assisted mapping system<\/strong> which will automatically identify and remove duplicates and reconcile hotel data from all sources into a single, accurate view.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Hotel mapping tools: how they work and what differentiates them<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Fortunately, there are several specialised solutions on the market that address the problem of hotel and room mapping. The most well-known tools use artificial intelligence and machine learning to compare data from multiple sources and automatically match the same entities. Some of them also include <em>manual checks<\/em> for greater accuracy. Below we present the main features of several current platforms <strong>Hotel mapping<\/strong> and their approaches.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>GIATA - the largest hotel database with hybrid mapping for superior accuracy<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>GIATA<\/strong> (German company founded in 1996.) is considered the market leader in hotel mapping with <strong>the world's largest hotel database<\/strong>. Their solution <strong>MultiCodes<\/strong> combines automated <strong>AI mapping<\/strong> with around 20\u201325% <strong>Handicrafts<\/strong> by a team of experts. Each hotel is assigned a unique <strong>GIATA ID code<\/strong>, which ensures that the object appears only once in the list and eliminates duplicates. This kind of <strong>Hybrid approach<\/strong> results in extremely high accuracy \u2013 GIATA states <strong>99,99962%<\/strong> precision in hotel matching. Such a high level is achieved by daily AI data comparison and manual correction of those cases that the algorithm cannot unambiguously resolve. GIATA maintains <strong>a constantly updated data network<\/strong> (more than 1.3 million unique objects and 180+ million supplier codes) and immediately corrects any identified errors. Their GIATA MultiCode identifiers have become <strong>Industrial standard<\/strong> used by leading OTAs, tour operators, bed banks and global distribution systems to easily exchange hotel data without additional mapping. In short, GIATA provides <strong>most comprehensive and most precise<\/strong> mapping with minimal possibility of error, which is ideal for large entities where data quality is crucial.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Gimmonix \u2013 fully automated mapping with fast data processing<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Gimmonix<\/strong> is an innovative company in the travel tech sector offering <strong>fully automated<\/strong> solution for mapping hotels and rooms. Their system known as <strong>Mapping.Works<\/strong> focuses on <strong>speed and accuracy<\/strong>according to the company, aligning large datasets takes them less than 24 hours, with about <strong>99% accuracy<\/strong> in object matching. Unlike GIATA, Gimmonix does not use manual labour \u2013 it relies exclusively on advanced machine learning algorithms and cloud infrastructure to automatically compare hotel names, addresses, coordinates and other attributes. In practice, Mapping.Works can process <strong>million objects<\/strong> and immediately connect them via API to the client's system network. Gimmonix often stands out for its capability <strong>personalisation and customisation<\/strong> for the client \u2013 integrations can be configured to the needs of the OTA or travel company to achieve the desired mapping and filtering criteria for inventory. In other words, Gimmonix offers <strong>brzu, \u201chands-off\u201d automatizaciju<\/strong>everything takes place in the background via API or their interface, without the need for operators to manually consolidate data. This approach reduces operational costs and enables agencies and travel platforms to scale their business \u2013 they can easily add new suppliers and accommodation sources, and the system ensures everything remains consistently and accurately mapped.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>DataBindR \u2013 Machine learning with a focus on integration flexibility and room details<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>DataBindR<\/strong> is a newer cloud platform specialised in <strong>Hotel and room mapping<\/strong> with application <strong>Machine processing of language<\/strong> and their own algorithms. Their emphasis is on <strong>flexible data integration<\/strong> \u2013 their system <strong>HotelMappR<\/strong> allows clients to simply import their hotel catalogue (e.g. CSV\/Excel file) and receive an automatically mapped output back. After initial mapping through HotelMappR, continuous maintenance is carried out via <strong>HotelBindR API<\/strong>, which merges new supplier data with the client's already mapped list and assigns a unique <strong>BindID<\/strong> to every object. This achieves unique hotel identification across all systems, similar to the GIATA ID. DataBindR prides itself <strong>detailed room-level mapping<\/strong>Their special module <strong>RoomMappR<\/strong> analyses and combines room descriptions (name, type, capacity, amenities, view, beds, etc.), assigning unique BindID tags to the rooms. The algorithms are designed to <strong>recognise spelling and syntactic variations<\/strong> in names (e.g. \u201cDeluxe King Room\u201d vs \u201cKing Deluxe\u201d) and automatically corrects mistakes or abbreviations to ensure data consistency. DataBindR does not use manual mapping \u2013 the system learns independently from new data and continuously <strong>cleans and checks<\/strong> information to maintain quality. This platform is often the choice for companies that have <strong>very diverse data sources and complex integration needs<\/strong>, as it offers high adaptability and the ability for operators to adjust mapping rules as needed through their interface.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Vervotech \u2013 AI solution for mapping with real-time data refreshing<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Vervotech<\/strong> is one of the newer players (founded in 2018) that has quickly established itself as a quality one <strong>AI hotel and room mapping<\/strong>. Their system uses <strong>deep learning<\/strong> How would you automatically normalise hotel data from multiple <strong>400+ integrated suppliers<\/strong> in real-time. Vervotech prides itself <em>almost complete market coverage<\/em> (according to their own data, they cover ~98% of available accommodation) and <strong>with an accuracy of 99.999%<\/strong>, processing new data within <strong>less than 24 hours<\/strong>. Their <strong>Hotel Mapping API<\/strong> intended for OTAs, aggregators and booking platforms that need <em>continuous synchronisation<\/em> \u2013 Vervotech continuously monitors price changes, availability, and content and updates the mapping so that all partners always have the latest data. It is particularly noteworthy that the platform operates <strong>Incremental updates<\/strong> several times a day, instead of occasional manual re-mapping, which means that, for example, a change in a hotel's name or the addition of a new room is immediately reflected across all connected systems. Vervotech also supports <strong>multilingual mapping<\/strong> \u2013 compares hotel names and descriptions in different languages to find matches, which is important for global agencies. In short, Vervotech represents <strong>modern, scalable<\/strong> SaaS mapping platform with a focus on <strong>automatic deduplication and data currency<\/strong> at any time. This helps larger OTAs and travel companies to maintain consistency of offering despite a large number of suppliers.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>(Note: In addition to those mentioned, there are other solutions and internal tools on the market \u2013 for example, some booking platforms like Juniper or TravelgateX offer their own mapping modules or integrate the mentioned services. When choosing a tool, it is crucial to consider the size of your own inventory, the number of sources you are connecting, and the level of accuracy and up-to-dateness you require.)<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Conclusion: Why Quality Hotel Mapping is Crucial for Successful Distribution<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In the world of accommodation distribution, where one agency can simultaneously use data from dozens <strong>wholesalers, OTA partners and bedbanks<\/strong>, <strong>quality mapping<\/strong> data is not a luxury but a necessity. Only with reliable mapping can all these different sources <strong>Unite into a single offer<\/strong> which the user will see on your pages \u2013 without duplicates, without contradictory information. This ensures that <em>one hotel is shown only once<\/em>, with all the best prices and room options consolidated in one place.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The key advantage of quality hotel mapping is the ability for the agency to always offer <strong>best price on the market<\/strong> for that property. When multiple suppliers offer the same hotel, their prices often vary. If the hotel is mapped correctly, the system can automatically <strong>Select the lowest available price<\/strong> and striking it is for the user, while at the same time removing duplicate entries. This way <strong>conversion increases<\/strong> \u2013 guests can more quickly find the best offer for their desired accommodation, without the confusion of multiple entries. At the same time, the agency can <strong>optimise your margins<\/strong> choosing supplier offers that give her better profit, safe in the knowledge that she is comparing \u201capples with apples\u201d thanks to unified data.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Another important item is <strong>user trust and reputation<\/strong> Brenda. When travellers know that your platform provides accurate, unique information (e.g. no risk of booking the \u201cwrong\u201d hotel due to name confusion), they are more likely to return and recommend the service to others. Conversely, poor mapping leading to mistakes damages reputation and trust, which directly harms long-term revenue.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Therefore, for agencies and tourism professionals who want <strong>Integrate numerous accommodation sources and always offer the widest selection at the lowest price.<\/strong>, Investing in a top-tier hotel mapping solution is proving to be key. Quality mapping eliminates manual work and errors, merges all available data into a coherent whole, and allows for business scaling without data chaos. Ultimately, this means <strong>better user experience, more bookings, and higher revenue<\/strong> \u2013 the goal that every modern tourism organisation strives for in the digital distribution of accommodation.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>","protected":false},"excerpt":{"rendered":"<p>Hotel mapping jedan je od naj\u010de\u0161\u0107ih izazova s kojima se susre\u0107u turisti\u010dke agencije i OTA platforme u distribuciji smje\u0161taja. Rije\u010d je o procesu povezivanja i uskla\u0111ivanja podataka o hotelima iz razli\u010ditih izvora (wholesalera, OTA-a, bedbankova itd.) u jedinstveni zapis. Bez kvalitetnog mapiranja hotela, mogu se&#8230;<\/p>","protected":false},"author":2,"featured_media":4410,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_tragento_display_category":0,"footnotes":""},"categories":[125,80,105,82,89],"tags":[152,153,91,72,154],"class_list":["post-5458","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hotel-resorts","category-izdvojeno","category-online","category-traveltech","category-vijesti","tag-giata","tag-gimmonix","tag-hotels","tag-traveltech","tag-vervotech"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v28.4 (Yoast SEO v28.4) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>Hotel mapping kako ga implementirati i za\u0161to je va\u017eno - Tragento<\/title>\n<meta name=\"description\" content=\"Hotel mapping: saznajte kako ga implementirati i za\u0161to je va\u017ean za izbjegavanje duplikata i pove\u0107anje prihoda.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/tragento.com\/en\/hotel-mapping-key-challenge-in-accommodation-distribution-and-how-to-solve-it\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Hotel mapping \u2013 klju\u010dni izazov u distribuciji smje\u0161taja i kako ga rije\u0161iti\" \/>\n<meta property=\"og:description\" content=\"Hotel mapping: saznajte kako ga implementirati i za\u0161to je va\u017ean za izbjegavanje duplikata i pove\u0107anje prihoda.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/tragento.com\/en\/hotel-mapping-key-challenge-in-accommodation-distribution-and-how-to-solve-it\/\" \/>\n<meta property=\"og:site_name\" content=\"Tragento\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/profile.php?id=61567461024345\" \/>\n<meta property=\"article:published_time\" content=\"2025-07-20T16:06:44+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/tragento.com\/wp-content\/uploads\/2025\/04\/pexels-tara-winstead-8386440-scaled-1.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1707\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"stipan.spaija\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"stipan.spaija\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"10 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/tragento.com\\\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/tragento.com\\\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\\\/\"},\"author\":{\"name\":\"stipan.spaija\",\"@id\":\"https:\\\/\\\/tragento.com\\\/#\\\/schema\\\/person\\\/90a4711289a0230e41987dc84e2a8f1f\"},\"headline\":\"Hotel mapping \u2013 klju\u010dni izazov u distribuciji smje\u0161taja i kako ga rije\u0161iti\",\"datePublished\":\"2025-07-20T16:06:44+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/tragento.com\\\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\\\/\"},\"wordCount\":1947,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/tragento.com\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/tragento.com\\\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/tragento.com\\\/wp-content\\\/uploads\\\/2025\\\/04\\\/pexels-tara-winstead-8386440-scaled-1.jpg\",\"keywords\":[\"giata\",\"gimmonix\",\"hotels\",\"Traveltech\",\"vervotech\"],\"articleSection\":[\"Hoteli &amp; Resorti\",\"Izdvojeno\",\"Online\",\"TravelTech\",\"Vijesti\"],\"inLanguage\":\"en-GB\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/tragento.com\\\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\\\/\",\"url\":\"https:\\\/\\\/tragento.com\\\/hotel-mapping-kljucni-izazov-u-distribuciji-smjestaja-i-kako-ga-rijesiti\\\/\",\"name\":\"Hotel mapping kako ga implementirati i za\u0161to je va\u017eno - 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