Aiosell Uses AI and ML to Calculate Rates and Distribute It Real-Time Across All Channels

Aiosell Uses AI and ML to Calculate Rates andDistribute It Real Time Across All Channels
Originally published: http://www.hospitalitybizindia.com/detailNews.aspx?aid=34429&sid=10

Aiosell is a unique B2B product that uses Artificial Intelligence and Machine Learning to do dynamic pricing and revenue optimization for hotels, resulting in improved occupancy and higher rates and reduction of operational costs and overheads. Aiosell integrates with several PMS and Channel Managers across the world to offer a fully automated, all-in-one hotel technology solution that can increase business for hotels. Launched in June 2019 by Siddharth Goenka, a Computer Engineer-turned-hotelier, who set up Octave Hotels in Bangalore after his stint with Microsoft Seattle as Computer Engineer and later on as Management Consultant at Accenture & Carlson Marketing in Mumbai, Aiosell has so far on-boarded over 140 hotels in 10 countries. Hospitality Biz spoke to Goenka about the product and its novel features…

Q What is the sense of the technology gap that exists in hotels when it comes to attaining efficiencies on the revenue side?

Revenue management is done manually using either excel sheets or analytics systems. Most rate updates are still done manually by a revenue manager, which leaves money on the table because the nature of the industry has become very dynamic and now there is need to change rates several times an hour or day. Most revenue management systems only recommend rates but do not push rates real-time because their algorithms do not take real-time and contextual parameters into account like time of day/week/booking window, and hence they refrain from taking responsibility for their recommendations. This is the technology gap because 95% of hotels around the world still change rates manually by human intervention.

Q How Aiosell fills that gap and how does it help in increasing the revenue?

Aiosell is an automated revenue management system that uses artificial intelligence to update rates on all online channels real-time. The system has two-way connectivity and is connected both to the hotel and to the live online channels. The system gets real-time inventory availability information from Property Management System (PMS), and combines it with real-time market information like demand, competition, and lead time and then optimizes the rates for a hotel. The hotel rates are updated using automated technology and channel managers in real-time. Since hotel room is a perishable commodity, if dynamic revenue management is done optimally, it will help hotels maximize revenues, because it will increase rates during high demand periods, and reduce rates during low demand periods. Automated rate optimization for hotels directly impacts the bottom line for hotels by increasing revenues and reducing costs.
Hotel Revenue management Software
Q What is the technological upper-hand that Aiosell claims over the existing technology tools used by hotels?

Existing systems mostly do the analysis of old data and recommend rates. This is usually not enough in today’s dynamic context because the market changes every season, and demand changes every hour. Aiosell’s technology uses artificial intelligence and machine learning to calculate rates real-time and integrates with all distribution channels to update those rates in real-time to maximize the results. The system uses several internal and external factors like real-time occupancy, lead time, time of day, demand, competition, weekday, etc. to make these pricing decisions which existing technologies do not do.

Q Could you briefly share the details of the company, its inception, the current customer base in the hotel sector?

Aiosell Technologies Pvt Ltd was launched in June 2019 but has been under research and development for 2 years prior. 140 hotels in 10+ countries are our customers. Clients include chain hotels like Summit Hotels, Fern Hotels, Leisure Hotels, Sun n Sand Group. Countries, where have our clients, including India, Thailand, Malaysia, Philippines, Singapore, Russia, Czech Republic, UAE, Kenya, UK, Norway, USA.

Q Whom are you largely targeting with your solutions – established players/ independent owner-driven hotels?

The solution is relevant for all categories of hotels and homestays, 5-star, 4-star, 3-star, and smaller apartment owners and Airbnb homestays.

Q What is the kind of savings that the solution brings to the table for hoteliers in terms of manpower, etc.?

Hotels have seen an increase in revenues of 20-50%, increase in occupancy by 10% and increase in Average Rates by up to 25%.

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