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How Hotels are Putting Their Data into Action
By Jason Q. Freed
Sunday, 21st October 2018
 

Hoteliers are still in the infancy stages of using the troves of available data to better serve guests and value rooms properly, according to Balaji Krishnamurthy, Chief Strategy Officer with Sabre.

Sabre, with nearly 40,000 hotels using some combination of its CRS, PMS or booking engine, offers an interesting perspective on how hotels can collect, analyze and make decisions on the guest and transaction data available today.

“It’s a big opportunity, but there are big challenges,” Krishnamurthy said on a recent Sabre webinar, Leveraging Data Insights to Drive Profitable Growth.

He says that hospitality businesses had been solely focused on improving the guest experience until about 15 years ago, when electronic distribution and channel management forced hoteliers to start analyzing different types of demand data.

“Hospitality has been behind other travel sectors for about 10 years,” Krishnamurthy said. “There is a lot of catch-up to do, but the opportunity is big in hospitality.”

What are today’s challenges?

Today, one of the biggest issues preventing hoteliers from making their data actionable is technology integration. Nearly all of the different systems in a hotel tech stack are generating some sort of data, and the challenge for hoteliers is bringing all that data into somewhere safe where they can analyze it and get a more holistic view of the guest.

The data is not always clean, either. With hotels spreading their inventory across so many channels, the data that comes from each of those systems doesn’t always look the same. And when hoteliers use legacy, on-premise systems to ingest and analyze that data, many issues can boil to the surface.

Where should we be tomorrow?

Krishnamurthy says a good data integration platform in a modern cloud environment can wrangle, clean and harmonize the data.

This will pay immediate dividends, allowing hotels to see how each of their channels are performing beyond the surface-level metrics like RevPAR, ADR and occupancy.

To start, hotel operators must find and hire the people with the right mind-set: curious people who are great problem solvers, he said, adding, “Talent is critical to extract value out of the ecosystem.”

Krishnamurthy said there are three concrete examples of applying data analytics to solve hotelier challenges:

  • Distribution planning. Use available data and analytics to help determine where and how to spend your marketing budget. A good start is looking at where your customers came from last year.
  • Revenue leakage detection. Because many of today’s pricing tasks are manual, Krishnamurthy says, rates either stay static much of the time or are even lowered and never brought back up. Disconnects to important distribution channels often go undetected. Analytics and AI can help avoid that and close the gap on leakage.
  • Demand forecasting. Many hotels still over-rely on historical data to power their forecast and pricing strategy. Advanced revenue systems can aggregate all of your data – including data from outside hospitality like flight information and guest buying behavior – to formulate a recommendation from all the information that’s available.

“Hoteliers are now able to use AI and machine learning to gain greater insight from their data and start to drive dynamic personalization and next-gen retailing and merchandising,” Krishnamurthy said. “Last year, airlines sold $80 billion in ancillaries, mostly fees and bag revenue. Think of what hospitality can do. There is a huge opportunity with what you can retail based on your customer’s unique need, using the data you already have.”

Jason Q. Freed, Managing Editor at Duetto
Jason joined Duetto as Managing Editor in June 2015 after reporting, writing and editing hotel industry news for a decade at both print and online publications. He’s passionate about content marketing and hotel technology, which leads to unique perspectives on hotel distribution and revenue management best practices.

www.duettocloud.com

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