Niche Serviced Apartments + Una: 24/7 Guest Care Case Study

It was around 11:30 PM. A guest had arrived after a long journey from the Far East, and it was raining heavily.

They couldn't find the key safe. When they finally located it, the standard code didn't work.

The guest was tired, frustrated, and standing outside the apartment they had booked for approximately three weeks.

At many serviced apartment properties, this is the moment someone on the management team gets an emergency call.

But at Niche Serviced Apartments, the team stayed asleep.

Una, the company's AI Digital Employee, guided the guest to the key safe, helped them use the backup access option, and got them inside.

No overnight employee intervention was needed.

For Niche, this was much more than a successful automated conversation. A problem that could have become a serious service failure was resolved before it disrupted the stay or the team.

That's what valuable hospitality automation looks like: the guest gets help when they need it, and the team doesn't have to be available for every routine problem.

For Niche Serviced Apartments, a UK operator managing a portfolio of approximately 100–200 units at the time of the case study, Una has become part of a larger effort to provide 24/7 guest care while protecting the people responsible for delivering it.

The Challenge: Guests Want Independence, but They Still Expect Someone to Be There

Serviced apartments offer something many travelers value: more space, greater flexibility, and independence.

Guests don't necessarily want to interact with reception whenever they enter or leave the property.

But independence doesn't remove the operator's responsibility.

A traveler arriving late still needs working access instructions. A guest struggling with the heating needs help. Someone dealing with a Wi-Fi problem expects a response even when the office is closed.

For Martyn Cooper, Managing Director of Niche Serviced Apartments, this was the central challenge.

Guests might not need continuous personal attention, but they expect assistance to be available whenever something goes wrong.

Niche already had the technology commonly used by professional accommodation operators: a channel manager, automated messaging, a unified inbox, WhatsApp, email, telephone calls, and booking channels including Airbnb and Booking.com.

The missing piece wasn't another communication tool.

It was the capacity to respond consistently across all those interactions without keeping the human team permanently on alert.

The Hidden Work Behind a Simple Arrival

From the guest's perspective, checking into a serviced apartment should be straightforward.

Find the building. Retrieve the key. Enter the property.

For the operator, a successful arrival depends on several things going right.

The accommodation must be ready. Payments and reservation details need to be correct. Access information must be available to the right guest. Changes need to reach the relevant systems. Backup arrangements must exist for unexpected problems.

If one step fails, an apparently simple arrival can become an urgent operational issue.

And for a guest who has traveled internationally, arrived late, or booked a long stay, that first experience can shape their confidence in the entire property.

The commercial consequences are easy to recognize: additional staff intervention, potential compensation requests, negative reviews, and the risk of damaging an otherwise valuable booking.

Not every arrival problem causes a financial loss. But leaving guests without timely assistance creates unnecessary exposure.

Niche needed a way to handle those moments before they became bigger problems.

Why Niche Chose Una Instead of Another Chatbot

Martyn and his team had already seen AI chatbot products.

They approached Una with understandable skepticism.

A tool that answers common questions might reduce a few repetitive messages, but it wouldn't necessarily solve the interruptions, coordination, and after-hours pressure affecting the business.

The team tested Una and deliberately challenged her with difficult situations.

According to Martyn's account, the testing impressed them. The turning point came when Una handled a real guest conversation outside working hours, and the guest believed they were dealing with someone from the team.

Martyn described the experience simply:

“This wasn’t a chatbot. This was a team member.”

The significance wasn't whether the conversation sounded convincingly human.

It was whether Una could provide useful assistance without requiring an employee to step in.

For Niche, that distinction mattered because the company didn't need more generated replies.

It needed dependable first-line guest care.

Today, Una supports Niche with routine guest communication, access and arrival questions, straightforward booking requests, and appropriate escalation to employees.

The exact workflows depend on the configured systems, operating rules, and permissions.

But the business objective has remained consistent: help guests promptly while allowing staff to concentrate on situations that actually require them.

The Moment That Proved 24/7 Guest Care Was Working

The late-night arrival in the rain became one of Niche's clearest examples of Una's value.

The guest had traveled from the Far East and reached the accommodation around 11:30 PM.

First, they couldn't locate the key safe.

Then the normal code failed.

Instead of leaving the guest to wait for the team, Una helped them work through the situation and use the available backup access arrangement.

The guest entered the property.

The human team wasn't woken up.

Consider what this meant operationally.

The guest received assistance during a stressful moment. The business maintained service coverage outside regular working hours. The employees weren't interrupted by an issue that could be resolved through the approved process.

For an operator overseeing many serviced apartments, those outcomes matter more than the number of messages handled.

A single successful resolution doesn't prove every lockout or after-hours emergency can be automated.

Some access problems require physical assistance, security intervention, or a manager's decision.

But this incident demonstrated the value of reliable first-line support in a real situation, not a controlled sales demonstration.

The result wasn't simply a faster response. It was an overnight problem resolved without creating an overnight staffing problem.

Keeping the Human Touch Where It Matters Most

Speed wasn't Niche's only concern.

Serviced apartment guests can be tired, anxious, or dealing with circumstances the operator knows little about.

An efficient response that feels impersonal may still leave the guest dissatisfied.

Martyn described another interaction involving a traveler visiting for a personal and emotionally difficult reason.

The guest encountered a Wi-Fi problem and became frustrated.

Una responded with sensitivity to the conversation, guided the guest through troubleshooting, and helped resolve the problem without requiring human intervention.

The example mattered to Niche because the response addressed both the practical issue and the guest's circumstances.

Martyn's feedback specifically highlighted Una's understanding and empathetic communication.

But this doesn't mean AI replaces human empathy or professional judgment.

The operating principle is the opposite.

When routine questions and straightforward troubleshooting don't constantly interrupt employees, the team has more capacity for situations requiring personal attention.

That might mean handling a serious complaint, discussing compensation, resolving an exceptional booking issue, or supporting a guest in distress.

Protecting the human touch doesn't require humans to answer every question. It requires them to be available when their involvement makes the greatest difference.

What Niche's Team No Longer Has to Handle Manually

Before Una, everyday communication created constant background pressure.

Guest messages arrived through multiple channels. Check-ins overlapped. Cleaners arrived. Some guests had not checked out on time. Calls interrupted other work.

Individually, many of these situations were manageable.

Together, they made it difficult for the team to concentrate.

Una now provides first-line assistance for supported requests involving:

Arrival and access instructions.
Check-in information.
Heating and Wi-Fi guidance.
Routine questions about a stay.
Guidance related to ID verification.
Straightforward booking inquiries and reservations.
Supported payment-link steps.
General guest-service requests.

More complicated situations are directed to the human team.

These include longer or repeat-booking inquiries requiring judgment, compensation decisions, serious complaints, safety issues, and unusual exceptions.

This division of responsibility helps Niche avoid two common problems.

First, employees don't need to personally handle every predictable guest question.

Second, the AI doesn't need to make decisions outside its authority to be useful.

The ability to recognize when human assistance is appropriate is part of what gives Niche confidence in the system.

For a professional operator, that means automation can support everyday service without surrendering control over sensitive decisions.

The Results: Time Back, Lower Pressure, and Revenue Support

Niche's feedback provides several measures of the impact Una has had on its operation.

The company reported:

3–5 staff-hours saved per day, based on its estimate.
$1,000–$3,000 in estimated monthly cost reduction, primarily associated with overtime and after-hours coverage.
1–2% of monthly revenue influenced or generated by Una, according to the operator's assessment.
Significantly faster responses to guest inquiries.
Fewer missed calls and lost booking opportunities, as reported by the client.
5/5 overall satisfaction with Una.
5/5 likelihood of recommending Una to another hospitality business.

These are Niche's customer-reported outcomes, not independently audited savings, incremental revenue, or controlled estimates of financial return.

The 1–2% figure includes revenue described as influenced or generated, which should not be interpreted as a verified increase in total revenue.

Likewise, the estimated staff-hours saved should not automatically be converted into payroll savings.

The most important finding is how consistently the feedback points toward the same operational benefit.

Una reduced the pressure of being constantly available.

Martyn summarized the change in a few words:

“It removes so much background stress.”

That statement captures something conventional AI performance metrics often overlook.

The business benefit isn't limited to how quickly guests receive answers.

It's the confidence employees gain from knowing that routine issues can receive attention even when they are not monitoring every inbox or telephone call.

Why This Matters More as a Serviced Apartment Portfolio Grows

A small portfolio may be able to rely on a few experienced employees who know every property.

As the number of units increases, that becomes harder.

Different apartments have different access arrangements, heating systems, parking instructions, and operational exceptions.

Guest communication may increase without a corresponding increase in the complexity of each individual request.

The questions are still familiar.

Where is the key?

How does the heating work?

Can I extend my stay?

I can't connect to the Wi-Fi.

But the cumulative workload grows.

For an operator, the challenge is providing dependable service without having to add human coverage for every incremental unit.

Niche's experience illustrates how an AI Digital Employee can support that goal.

Una provides a consistent first point of contact for eligible requests, while the human team remains responsible for matters requiring discretion, complex operational judgment, or physical action.

That separation becomes increasingly valuable as the portfolio expands.

It allows the company to think about growth in terms of operating capacity rather than simply the number of additional messages employees must answer.

The Implementation Lesson: Trust Is Earned in Real Operations

Martyn's experience also offers a useful lesson for operators considering AI.

A convincing demonstration is not enough.

Niche built confidence through testing and early live interactions.

The team challenged Una, observed how she handled actual guest situations, and learned when to rely on automation and when human involvement remained essential.

That reflects an important principle: hospitality AI needs careful implementation.

Property information must be accurate. Operational boundaries must be clear. Employees need to know how escalation works. Guest-facing workflows should be tested before they become part of everyday service.

Niche also described onboarding as easy, while emphasizing the importance of introducing AI thoroughly and carefully.

Those observations aren't contradictory.

A system can feel approachable to employees while still requiring serious attention to configuration and operational testing.

For hotels and serviced apartment operators, that's a useful purchasing distinction.

The objective isn't to launch the most automation on day one.

It's to build enough confidence in the initial workflows that the team can genuinely depend on them.

What Other Hospitality Operators Can Learn From Niche

Niche's case is distinctive because the strongest proof is not a complex technical integration or a theoretical productivity model.

It's the effect on the day-to-day experience of running the business.

Three lessons stand out.

First, Solve the Availability Problem

Guests don't stop needing assistance when the office closes.

For operators with limited overnight coverage, consistent first-line communication can protect the guest experience without requiring staff to personally answer every eligible inquiry.

Second, Value Employee Attention

The workload that wears down a team isn't always dramatic.

It may be the endless accumulation of straightforward questions, interrupted tasks, and calls that arrive just as employees are handling something else.

Reducing that background pressure creates more room for meaningful service.

Third, Keep Human Judgment in the Operating Model

An AI employee should have defined boundaries.

The objective isn't to resolve every situation autonomously.

It's to handle repeatable work reliably and bring employees into the conversation when their judgment, authority, or personal involvement is genuinely necessary.

For Niche, that balance made Una a useful member of the guest-care operation rather than another tool competing for the team's attention.

The Best 24/7 Guest Service Doesn't Require a 24/7 Human Shift

Return to the guest outside the apartment at 11:30 PM.

They didn't need a sophisticated explanation of the property's technology.

They needed to get inside.

Una helped them do that.

The guest received support, the stay could continue, and Niche's human team didn't have to wake up to resolve an issue that could be handled through the available process.

That is the business case at the center of this story.

For Niche Serviced Apartments, Una helped make guest care more consistently available while reducing the burden on employees.

The company reported time savings, lower after-hours pressure, estimated cost reductions, and a positive contribution to booking-related revenue.

Just as importantly, Martyn's team felt more confident stepping away from constant communication monitoring.

Niche didn't use Una to take people out of hospitality. It used Una to make human attention available where it mattered most.

Hear Niche's Experience and Explore Una for Your Portfolio

For another perspective on how Una works in everyday serviced apartment operations, watch the full interview with Martyn Cooper in the original customer story.

If you're managing a growing portfolio and your team is still carrying the pressure of constant guest availability, we can help you examine where first-line automation could make a practical difference.

Bring us your common overnight inquiries, arrival problems, or recurring guest requests. We'll discuss which workflows Una can support through your existing systems and when your employees would remain involved.

Book a quick call with the Polydom team to explore how Una could support your serviced apartment operation.