Remove occupancy-rate-prediction
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New York Leads US Hotel Occupancy – First Time Since March 2020

Business Traveler USA

As the Big Apple turned on its holiday charms, visitors flocked back to the city, pushing New York to the highest occupancy level in the nation (81 percent) for the week ending Dec. That’s the first time in 85 weeks that New York has led the nation in occupancy, according to hotel industry analysts STR.

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Travel Analytics: Data Sources, Use Cases, and Real-Life Examples

AltexSoft Travel

Social media and travel blogs contain valuable information about travelers’ experiences, recommendations, preferences, and popular upcoming events. They can be indicators of inflation, exchange rates, unemployment, and consumer spending. This approach culminates in inventory optimization and competitive pricing strategies.

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Closed User Groups in Travel: Benefits, Examples, and Best Practices to Enable a CUG Strategy

AltexSoft Travel

By creating exclusive travel experiences for a select group of clients, you can increase customer loyalty, repeat purchase rate, and revenue. In this blog post, we’ll show you how to implement and take advantage of a closed user group strategy. A way for hotels to evade rate parity restrictions. Group travelers.

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Hotel Price Prediction: Hands-On Experience of ADR Forecasting

AltexSoft Travel

Hotel price prediction is a critical aspect of the travel industry, and with the rise of machine learning , it has become more precise and accurate. This blog post will delve into the challenges, approaches, and algorithms involved in hotel price prediction. What is hotel price prediction?

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Hotelbeds API Integration: Hands-on Experience with a Leading Bed Bank

AltexSoft Travel

As a bed bank, it operates in the B2B realm, procuring rooms from accommodation providers in bulk at discounted rates and then offering them to various businesses like OTAs , travel agents, and airlines. The API provides a comprehensive list of hotels detailing room types, board variations, and rate lists. Content synchronization.

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ChatGPT Implementation in Travel: Unleashing the Potential of GPT Models in Real-World Projects

AltexSoft Travel

They predict the next appropriate word based on text context, essentially learning how humans use language. Of course, there are other possibilities, such as “cake” or “tart,” but “pie” is an everyday culinary use for apples, making it a likely prediction.

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