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Imlauer Hotels: a five-property, family-run hotel group
Imlauer’s story goes back more than three decades, to when the company’s owner first rented a single restaurant and hotel. Today the group runs five properties across Austria: three in Salzburg, one in Vienna, and one in Styria built around golf and wellness rather than city travel. Around 560 rooms in total, and still family-owned.
Johannes is hotel director at Imlauer, and over the past few years he has taken on much of the group’s technology evaluation. He guided the recent migration to Mews, and now researches and tests new tools before bringing a recommendation to ownership. Whatever the group adopts has been vetted by someone who runs a hotel every day.
How Imlauer Hotels managed reviews before MARA
Before MARA, Imlauer ran reviews through another reputation tool. There was no meaningful AI behind it, so responding to reviews was manual work spread across the group. Each hotel manager handled their own property’s reviews, and one person managed reviews across all five of Imlauer’s restaurants.
The switch was not triggered by a single bad experience. It came down to a straightforward comparison.
For a hotel group constantly evaluating its stack, that combination of value and capability is the entire decision.
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How MARA automates guest review responses at Imlauer Hotels
Every morning, Johannes opens MARA first. He reads through the previous day’s reviews directly, no reports needed, because the volume is manageable enough to scroll through. The reviews that need attention from him are the rare ones. MARA’s autopilot handles three to five star reviews automatically, the positive and neutral feedback that makes up the bulk of what comes in.
One or two star reviews still come to him personally, one or two a month, because those require context no AI has access to: what was actually said at the front desk, what the guest experienced that never made it into the review itself.
It’s a simple goal: not to add visible complexity, but to remove manual steps wherever a system can reliably take them over, so the time that’s freed up goes back to the guest standing in front of someone, or the team member who actually needs a conversation.
How Imlauer Hotels uses guest reviews to recognise and coach staff
The most distinctive part of how Imlauer uses MARA has nothing to do with responding to guests. It is about the team.
Because MARA is connected to Mews, every review Johannes reads can be traced back to the reservation behind it, and from there, to the staff who handled that guest’s stay. If a review names an employee negatively, Johannes can see exactly who checked that guest in and out.
What happens next is not what most people picture when they hear “staff performance tracking.” There is no formal review process, no scorecard. “We talk to them in person,” he says. “It’s not training, that’s a big word for it. It’s five to ten minutes on the job, because if someone is named negatively, there’s always a reason.” Often it is something simple: a guest annoyed that the city center was closed off for a marathon, and a team member who didn’t know to mention it. Easy to fix once you know it happened.
The positive side runs on its own rhythm. Every quarter, Imlauer compiles a table of staff named positively in reviews. Three or more mentions earns a gift card. At the yearly company party, the three most-mentioned employees across the group are recognised in front of everyone. One colleague from a restaurant team was named 65 times in a single year and walked away with a voucher for an overnight stay at one of the hotels.
Using guest review data to support investment decisions
Cross-property comparison happens formally once or twice a year, when the team member overseeing restaurant reviews puts together a short presentation tracking the most impacted scores across the group, positive and negative. But the real rhythm is weekly. Every Tuesday, Imlauer’s revenue meeting includes a discussion of review scores, because as Johannes puts it, a Booking.com score moving from an 8.3 to an 8.5 is the kind of shift that directly affects revenue.
Johannes also checks the other properties’ reviews himself once a week, focused mainly on the negative ones, to catch anything that points to a shared technical issue rather than a one-off complaint. A pattern of guests mentioning too many automated emails before check-in, for example. The kind of thing that is easy to miss at a single property level but obvious once you’re looking across all five.
For Johannes, the value of MARA’s data isn’t in surprises. It’s in confirmation. “It confirms what we’re already thinking,” he says. “For example, that the soundproofing in certain rooms isn’t good enough, or that some doors need replacing.”
It’s the difference between telling ownership “I think this needs fixing” and showing them exactly how many guests agree.
Why Imlauer Hotels integrates MARA with Mews and Flexkeeping
Ask Johannes how he evaluates a new tool and the answer is immediate: it has to connect to Mews. “The PMS is the heart of the hotel,” he says. “That’s where all the data is stored, where all the information comes from.” Every week brings a new pitch through LinkedIn or a sales call, and the first thing he checks is whether the tool shows up in the Mews Marketplace.
That filter is what led Imlauer to MARA’s Service Ticket AI, built on the existing Mews integration and rolled out to Flexkeeping just a couple of weeks before this conversation.
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Frequently Asked Questions:
Imlauer’s hotel director reads new reviews every morning directly in MARA, while the platform’s autopilot automatically handles three to five star reviews. Only the rare one or two star review needs personal attention, since those require context that isn’t visible in the review itself.
Because MARA is connected to Imlauer’s Mews property management system, every review is linked back to the original reservation. That makes it possible to see exactly which staff member handled a guest’s stay, which is what enables Imlauer’s staff recognition process. The same connection powers MARA’s Service Ticket AI, which routes maintenance issues mentioned in reviews automatically into Flexkeeping, removing the manual work of cross-checking the PMS by hand.
No, Imlauer’s setup runs on Mews and Flexkeeping, which is where the integration is most established today. MARA also integrates with other PMS & operations providers and is actively expanding Service Ticket AI to additional PMS and operations platforms beyond this pairing.
Imlauer tracks employees named positively in reviews each quarter, with three or more mentions earning a gift card. At the company’s yearly party, the three most-mentioned employees across the group are recognised in front of the whole team. Negative mentions lead to a short, informal conversation rather than formal discipline, focused on understanding what happened and fixing it going forward.
Patterns that show up repeatedly in guest reviews, such as soundproofing or door quality, give Imlauer’s team concrete evidence to bring to ownership when requesting investment. Rather than relying on a gut feeling about what needs fixing, the data shows ownership exactly how often guests are raising the same issue.
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