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PRESS - Revolutionizing Room Sales: Introducing GauVendi's Hyperpersonalized Inventory Management

Updated: Feb 16, 2023

Frankfurt, 15. February 2023 - GauVendi is leading the charge in the hospitality industry with their innovative approach to room sales: Hyper personalized Inventory Management. This differentiated approach appeals to diverse guest buying behaviors, segments, and willingness to pay, providing a better customer experience and driving revenue for hoteliers.


What sets GauVendi apart is their poly-dynamic and feature-based inventory management. This allows hoteliers to decouple the physical room from the product they sell, giving them the flexibility to sell the same room differently to different segments and channels.


With the term "poly-dynamic" GauVendi refers to the possibility of selling each room multiple times (i.e. "poly") and in different ways adapted to the corresponding guest profile. Thus, multiple possibilities arise to sell one and the same room dynamically.


GauVendi differentiates between four product types: Standardized Products, Feature-based Products, Combined Products, and Virtual Products.


Here are some practical examples of how this is put into practice:




· Corporate guests are often bound by travel policy to stay in specific room types. Hoteliers can sell these rooms under different name and price point that appeals to these segments.

· There is often a demand for more single rooms during the week. Double rooms can be sold as large singles at a different price point.

· The same rooms can be sold to third-party channels (e.g. OTAs) as standard rooms, while being sold hyper personalized directly to discerning travelers or returning customers seeking more customization. This approach can be seen as the next loyalty program, delivering personalization to guests instead of points.

· For families, hoteliers can sell combined products at a combined price point that meets their budget needs.


The pricing and product go hand-in-hand, providing greater transparency for guests and allowing hoteliers to be more flexible in their real estate usage. The biggest limitation of inventory sales in the hospitality industry today is the clustering in room categories. These categories lack transparency during the booking process for guests and have poor sales differentiation, resulting in idle assets that don't capture many room characteristics that guests would pay for.


To overcome these challenges, GauVendi employs innovative sales techniques in combination with poly-dynamic inventory management. They use machine learning based on travel profiles to put relevant products on the retail shelf, utilizing social proof and scarcity labeling tactics. The company also provides a dynamic room configurator, allowing guests to choose their preferred room characteristics and find the best match.


The results of this approach have been staggering. On average, average rates have increased by over 20%, with every third guest choosing a social proof-type of product, and 20% selecting their own preferences. This is a win for the guests, operators, and owners alike.


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About GauVendi

Founded in 2020 by experienced industry experts, GauVendi offers a comprehensive solution for sales, revenue, and automation with its groundbreaking AI-powered central sales system. The poly-dynamic and feature-based inventory management allows hoteliers to decouple the physical room from the product they sell, giving them the flexibility to sell the same room differently to different segments and channels. GauVendi's proprietary data structure enables hyper-personalized accommodation experiences, transparent booking processes, and higher returns. As the world's first system, GauVendi combines sales and distribution strategies with property management and channel management for a unique, cutting-edge solution.

Media Contact

CW-PR Kommunikation - Christina Wiedemann – Hasengasse 21 – 60311 Frankfurt am Main Tel: +49 172 6873371 - E-Mail: c.wiedemann@cw-pr.de

Company: GauVendi GmbH - Feuerwehrstrasse 10 - 60435 Frankfurt am Main


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