One such challenge is managing the vast amounts of guest feedback available to hotels today – from online reviews, guest surveys, messaging and other channels.

 

There’s a great deal of hype around artificial intelligence (AI) today. For the hotel industry, the most immediate benefits come not from building humanoid robots to deliver towels to guestrooms, but from using AI to solve concrete business challenges. 

 

One such challenge is managing the vast amounts of guest feedback available to hotels today – from online reviews, guest surveys, messaging and other channels.

 

Using Guest Surveys to Prioritize Resources 

Hotel staff are prone to overreact to negative feedback and make rash decisions, whereas computers aren’t influenced by emotions and biases. A machine-learning solution can help staff distinguish between one-off comments that can be disregarded and patterns that require attention.

 

Using a process called impact analysis, hotels can categorize ratings from guest survey questions into four areas, each with recommended actions:

 

1. Maintain (good score, low impact)

2. Amplify (good score, high impact)

3. Monitor (low score, low impact)

4. Prioritize (low score, high impact)

 

Impact analysis can identify broad problems such as room quality or specific problems such as service in the hotel bar. In the graph pictured here, areas that fall into the fourth quadrant, like breakfast and value, must be given the highest priority because survey ratings are low and the impact on overall guest satisfaction is high. 

 

The second quadrant is important, too. For example, the hotel may advertise oversized guestrooms as its most distinguishing feature, but impact analysis reveals that it’s actually the hotel’s location that guests love the most. By changing sales and marketing messaging to highlight its location, the hotel can increase room demand. 

 

Responding to reviews and surveys is a time-consuming task that many hoteliers would happily delegate. To allow bots to communicate directly with guests is a risky proposition, but supervised machine-learning algorithms are capable of choosing appropriate response templates and, with employee oversight, dispatching replies. 

 

With the explosive popularity of messaging, guest expectations of a quick response to inquiries are higher than ever. Generally, humans perform much better than computers at customer-facing tasks that require empathy, judgement and creativity, whereas simple rule-based bots can provide basic information such as directions, breakfast hours and check-out procedures. 

 

Moreover, bots can automate internal workflows, alerting appropriate staff of guest inquiries and complaints and ensuring that tasks are fulfilled promptly and thoroughly.

 

Looking to the Future

In the coming years, an increasing amount of guest feedback will be processed, analyzed and acted upon using artificial intelligence models, helping hotel staff understand their guests, make data-driven decisions and improve the guest experience. 

 

For hoteliers wishing to keep pace with the trends, as a starting point identify a key business challenge that can potentially be solved with artificial intelligence and look for existing B2B solutions in the hospitality industry.