In the world of hospitality, a hotel’s reputation is often defined by the bold, public statements made on review sites. But what about the quiet, unspoken experiences that truly shape a guest’s stay? We sat down with Katarina Railko, a seasoned expert in hospitality and guest experience, to explore the critical gap between public perception and private reality. We’ll delve into why relying solely on third-party reviews creates operational blind spots, how proactive feedback can transform service recovery, and the way integrated technology is empowering hotels to move from simply managing their reputation to actively managing the entire guest journey.
The article argues that third-party reviews have “blind spots” because they are often reactive and unstructured. Could you give a specific example of a common operational issue, like a “fine enough” check-in, that hotels typically miss and explain how a targeted survey question could uncover it?
Absolutely. The “fine enough” check-in is a perfect example of a silent loyalty killer. Imagine a guest arrives after a long flight. The front desk agent is efficient—they find the reservation, take the credit card, and hand over the keycard. The process is technically flawless, but it’s cold and transactional. There’s no warm welcome, no eye contact, no mention of the restaurant’s dinner special or the pool hours. The guest isn’t going to write a scathing one-star review on Google over it, because nothing was truly wrong. But that first impression sets a mediocre tone for the entire stay. That feeling of being processed rather than welcomed is exactly what gets missed in public feedback. Instead of asking a generic post-stay question like “How was your check-in?”, a targeted on-site survey could ask, “On a scale of 1-10, how personally welcomed did you feel upon your arrival?” This shifts the focus from procedural correctness to emotional connection, giving you data on the hospitality itself, which is where the real magic happens.
You make a distinction between “reputation management” and “experience management.” Can you walk us through how an on-site survey helps a hotel team catch a small issue in real-time? Please detail the step-by-step process from receiving the feedback to resolving it before the guest leaves.
This is where hospitality becomes proactive instead of reactive. Let’s picture this: a guest has just settled into their room and receives an automated text message with a simple, two-question survey: “Is everything in your room to your satisfaction?” They reply that the room is lovely, but the air conditioning seems to be making a strange rattling noise. In a traditional model, they might tolerate it for a night or two before finally getting frustrated enough to call down, or worse, they say nothing and just leave a three-star review mentioning the noisy AC. With an experience management approach, that survey response instantly triggers an alert on the hotel operations dashboard. The front office manager sees it, immediately identifies the guest and room number, and calls the guest directly. The conversation is one of immediate care: “Mrs. Davis, this is the manager at the front desk. I just saw your note about the air conditioning, and I am so sorry for that disturbance. I’ve already dispatched an engineer to your room—they’ll be there in five minutes. Would it be alright if we sent up a complimentary pot of coffee for the inconvenience?” In that single interaction, you’ve turned a potential negative review into a story about incredible, attentive service. The guest feels heard and valued, and the problem is solved long before it has a chance to sour their stay. That is the essence of managing the experience, not just the review that comes after.
The TrustYou platform is positioned as a single source of truth, unifying public reviews and private surveys. How does seeing a guest’s candid survey feedback alongside their more public Google review in one inbox change a manager’s decision-making process? Please share a practical scenario to illustrate.
It’s a complete game-changer because it adds context and clarity, turning vague complaints into actionable projects. For instance, a hotel manager sees a new 3-star Google review that just says, “The location was great, but the breakfast was a letdown for the price.” On its own, that feedback is frustratingly generic. What was wrong with it? The food? The service? The variety? The manager might be tempted to dismiss it as a one-off picky guest. However, with a unified platform, they can see that this same guest also submitted a private post-stay survey. In that survey, the guest was far more specific: “The scrambled eggs were cold by 8:30 a.m., and there were no non-dairy milk alternatives for my coffee. I had to ask three different staff members before someone could find soy milk.” Suddenly, the manager doesn’t have a vague “breakfast problem.” They have two specific, solvable issues: a food warming process that’s failing mid-service and a supply chain gap for non-dairy milk. They can now go to their food and beverage director with a concrete plan, not just a complaint. This transforms decision-making from reactive guessing to data-driven improvement.
It’s mentioned that AI-powered tools can save up to 80% on response time. Beyond pure speed, how does this technology help a hotel group maintain a consistent, on-brand, yet human-sounding voice when responding to hundreds of varied reviews and survey comments each month?
The 80% time saving is a massive operational win, but the real strategic value is in brand consistency and quality control. For a hotel group with multiple properties, ensuring every single review response reflects the brand’s unique voice is a huge challenge. You might have one general manager who is wonderfully eloquent and another who is very direct and brief. This creates a disjointed brand personality online. AI-powered response tools solve this by being trained on the brand’s specific communication guidelines. The AI can analyze the sentiment of a review, identify the key topics mentioned—like praise for the clean rooms but a complaint about parking—and then draft a response that is empathetic, addresses each point specifically, and does it all in the hotel’s pre-defined tone. The manager’s job then shifts from writing from scratch to simply reviewing and personalizing the AI’s draft, adding a human touch before hitting send. This ensures that whether a guest is staying in Miami or Seattle, the brand voice they encounter online is consistently warm, professional, and attentive, which builds trust at a much larger scale.
The article calls private feedback “operational gold” because guests aren’t “performing for an audience.” Could you share an anecdote where a piece of candid feedback from a private survey led to a significant operational improvement that had never been mentioned in public reviews?
I worked with a boutique hotel that was very proud of its modern, minimalist room design, and their public reviews were generally fantastic. However, in their private post-stay surveys, a subtle but consistent theme started to emerge. Guests would make comments like, “The room was beautiful, but I couldn’t find a convenient place to charge my phone near the bed,” or “I had to unplug the lamp to charge my laptop at the desk.” No one was ever angry enough to put this in a TripAdvisor review—it was a minor annoyance, not a deal-breaker. But internally, this feedback was pure gold. The management team realized that in their quest for aesthetic perfection, they had overlooked a fundamental modern travel need. Based solely on this private feedback, they invested in retrofitting every room with bedside USB ports and adding power strips to the desks. It was an operational change that was never prompted by a public firestorm but made a tangible difference in the convenience and comfort of the stay, which was then reflected in even higher satisfaction scores on subsequent surveys.
What is your forecast for the future of AI in managing guest feedback? How will platforms evolve beyond just analyzing and responding to proactively shaping the entire guest journey, perhaps even before a potential issue arises?
My forecast is that we are moving from a reactive to a predictive and prescriptive model of guest experience management. The future isn’t just about AI understanding what a guest wrote; it’s about it understanding the guest themselves and anticipating their needs in real time. Imagine an AI platform integrated with the hotel’s property management system. It knows a guest is arriving who, on their last private survey, mentioned they found the gym a bit crowded in the morning. The AI can proactively trigger a personalized welcome message upon check-in: “Welcome back, Ms. Chen! We know you enjoy an early workout, so we wanted to let you know the quietest times for the fitness center are typically before 7 a.m. or after 9 a.m.” It’s about using data from past feedback to preemptively solve a problem before it even exists for this specific stay. The evolution is moving from analyzing feedback to shaping the journey, using AI to deliver hyper-personalized, thoughtful touches at scale that make every single guest feel seen and uniquely cared for. That’s the future of hospitality.
