Pitching one AI solution against next

March 11, 2016 // By Julien Happich
According to Artificial Intelligence software solutions provider Dato, apps of the future will all run a form of machine learning or another to better serve their users.

One of the company's early customers, LodgIQ plans to revamp today's hospitality industry with smarter real-time pricing strategies based on big-data analysis. Founded last December, the New-York based startup was quick to convince investors, securing $5 million in funding from investors Highgate Ventures and Trilantic Partner while signing its first customer, Highgate Hotels.

The company has just launched its first products, LodgIQ RM and LodgIQ Mobile RM (for Revenue Management). The LodgIQ RM platform incorporates machine learning and artificial intelligence to adapt to evolving demand patterns in real-time. One application could be to help hotel managers adjust their commercial and pricing strategies continuously, based on multiple factors such as flights patterns, weather forecast, city events (trade-fairs, concerts, sporting events), online reviews, or anything that may affect travellers' destinations and booking patterns.

Talking to EETimes Europe , LodgIQ 's CTO Somnath Banerjee explained his ambition to apply modern scientific mathematical techniques to price hotel rooms.

As a hotel manager, the tool could help you find out dynamically who are your savviest competitors in particular segments, or within a given distance.

"We use historical data, but also large data sets from flight reservations, weather forecast, city-events, or even text-based hotel reviews, and quantify their impact on reservation patterns. We use machine learning to identify patterns in data that we can use for our predictions in order to suggest the best room prices for a given market condition".

Today, hotel managers typically list out their competitors' prices manually, but this would no longer be possible with dynamic pricing, and they may not optimise their room prices based on statistically accurate demand.

"There are many things in life that are subjective, for example online hotel reviews are very important, but they are often text-based. We want to take them and run AI across them to mathematically quantify their impact on revenue, putting an objective number on them so hotel managers can find out what