One answer to this clear-and-present problem is automation. You need strong workflows to free up your already harried team’s time so that they can be in the moment with onsite guests. Let tech handle as much as possible so that your staff can put the ‘high touch’ back into hospitality and smooth out any perceived slights with personalized error recovery and genuine service.

Always remember during all this to evaluate your property from the customer’s perspective. They don’t care about your back-of-house issues – that is, the overworked and ‘clopening’ team members. They just want to have a great front-of-house hotel experience. So, for them, housekeeping cleaning delays, front desk lineups or nonfunctional in-room WiFi are all perceived as emotional pain, with no logical explanation of labor shortages able to suffice.

This is as a preamble, here are seven things to look for in a hotel review automation system to help guide your decision-making process:

  • Programming in-stay surveys and setting team notifications, so that hoteliers can act quickly to provide onsite service recovery when needed.

  • Consolidating requests from any digital platform – whether it’s an email, texting app or social media – so nothing gets missed and the team isn’t burdened with checking every single channel.

  • Bringing all online reviews into a single unified platform for managers to efficiently answer with thanks and acknowledgements, and for prospective guests to see that the hotel is responsive and caring.

  • Perfecting the pre-arrival and post-departure automated communications to set the tone for a great onsite experience and maintain the brand relationship after check-out.

  • Employing a hospitality specific chatbot to help automate the more repetitive aspects of inbound inquiries, whether it’s for guests currently on-premises or those yet to book a room.

  • Offering comp set review benchmarks to give a sense of where a property needs to improve compared to other brands.

  • Analyzing the specific words in each review – otherwise known as semantic analysis – where you can use AI-driven tools to evaluate performance not just on star rating changes but on guests’ sentiments and ‘soft’ suggestions.

By Adam And Larry Mogelonsky