Case study

How The Social Hub runs 15,000 hybrid rooms on Campus Pilot

Hybrid student and long-stay housing across Europe, with locations of 600–700+ rooms across multiple buildings, running on Campus Pilot alongside Mews.

The operation, in numbers

89

89 cleaning rules

at a single property, every guest type, rate code and floor handled automatically

Monthly student cleans

scheduled by floor, week and cluster, staff know exactly which rooms, which day

Demand-forecast staffing

peak cleaning days predicted ahead, so teams are never caught short

Millions of euros

recovered and protected across the portfolio through costed check-out damage tracking

Why hybrid student and long-stay housing is hard

The Social Hub runs a hybrid model: student residents on long stays alongside hotel guests, extended-stay guests and groups, often in the same building. That means one platform has to serve completely different rhythms at once. Hotel guests turn over daily; extended-stay guests get a lighter weekly clean; students follow a semester rota that changes by floor and by week of the year.

Traditional hotel PMSs treat every reservation the same way. Spreadsheets can flex, but they collapse under the load of 15,000 rooms and hundreds of housekeepers. What the operation actually needed was a rules engine that understood every segment and generated the right work automatically.

Cleanings that follow the reservation, not the room

A single room at The Social Hub can host a student one month, an extended-stay guest the next and a hotel booking the week after. Campus Pilot attaches cleaning rules to the reservation, not to the room, so behaviour switches automatically as new bookings arrive. Housekeepers see one clear schedule; managers stop policing exceptions.

89 rules at a single property

At one Social Hub location, 89 distinct cleaning rules run in parallel, driven by segment, rate code and group name. Rules cover everything from monthly student refreshes to weekly extended-stay cleans to daily hotel turndowns, plus one-off group arrivals. All of them fire from the same rules engine, so operations teams stop rebuilding schedules every Monday.

Forecasting peak days, staffing ahead

Because Campus Pilot knows what cleans are coming, it can forecast peak demand days weeks in advance. Managers see a clear demand curve, plan staff levels against it, and stop absorbing the cost of last-minute overtime, or worse, missed cleans.

Recovering damages, at portfolio scale

Check-in and check-out checklists capture photo evidence of the room condition on both ends of the stay. Damages and missing items get costed and pushed back through the PMS deposit or invoiced with an operational mark-up. Across the portfolio, that discipline has protected millions of euros that would otherwise have been absorbed as operating cost.

Student and long-stay cleanings are auto-scheduled by building, floor and cluster across our 600+ room locations. Maintenance routes itself to the right worker. Labour is planned from forecast demand, not guesswork.

, The Social Hub · 15,000 rooms · running with Mews

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