Purpose-built AI for hospitality that drives more revenue, leaner operations, and guests who keep coming back.
STAIE is different
Every hotel software vendor is adding AI features. The result is tool overload, fragmented data, and teams that don't know how to use any of it.
STAIE is different. We're MetricMavens' hospitality-focused AI practice: senior strategists who audit your tech stack, redesign your workflows, train your teams, and integrate AI where it drives measurable results. Purpose-built for hospitality. Outcomes agreed upfront. Your team running it independently when we're done.
Where STAIE delivers
Three areas. Measurable impact in each.
AI FOR REVENUE DISCOVERY
Stop leaving money on the table. STAIE optimizes your pricing in real time, forecasts demand before it peaks, and surfaces ancillary revenue opportunities your current setup can't see.
OPERATIONAL EFFICIENCY
Your systems should work together. STAIE integrates your tech stack, automates the workflows eating your team's time, and gives your managers the visibility to make faster, smarter decisions.
GUEST SATISFACTION
Guests notice when a hotel knows them. STAIE unifies guest profiles, powers intelligent personalization, and enables the kind of service that turns first-time visitors into regulars.
A smarter day at your hotel
Less noise. Better numbers. Guests who come back.
Before the day starts Pricing across your properties updates automatically based on demand signals, local events and booking pace. No manual rate calls. No guesswork.
During the day Staff work from a single, connected view of each guest. Check-in is faster. Requests reach the right person without the back-and-forth. Housekeeping is scheduled around actual occupancy, not assumption.
In the background, always Systems talk to each other. Data flows without manual export. Reports generate themselves. Your managers spend their time acting on insight, not producing it.
At every guest touchpoint Returning guests are recognized. Preferences are anticipated. The right offer surfaces at the right moment. Ancillary revenue goes up. So does satisfaction.
At the end of the month Costs are lower where it matters. Conversion is higher where it counts. And your team has the capacity to focus on the thing no AI can replicate: genuine hospitality.
How we work
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Your team determines whether AI delivers or collects dust. We assess readiness, identify champions, design training programmes and build the capability your organization needs to keep compounding on the investment long after we're gone.
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Technology can only do so much if the workflows around it are broken. We map, redesign and optimize your processes first, so when AI comes in, it lands on solid ground.
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With the right people prepared and the right processes in place, we integrate and activate AI where it creates real, measurable impact. No tool overload. No fragmented stack. Just the right solution, built to last.
Three phases. Clear deliverables at each step. First results within 90 days.
Case study | Hospitality
Real-Time Guest Recognition at Scale
Client: The Social Hub
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"We couldn't recognize our own customers. Someone could book through Booking.com, check in at the hotel, join our community events, and we'd see them as three different people in three different systems. Our CRM was unreliable. We had valuable data everywhere but couldn't use it to actually improve the guest experience."
KEY ISSUES
No single customer view across booking platforms and physical locations
CRM data incomplete and inconsistent
Rich community activity data sitting unused
Staff couldn't personalize guest experiences even when data existed
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SOLUTION
Built customer identity model consolidating multiple data sources into single profiles
Implemented GA4 connected to central warehouse
Embedded data capability across organization
Enabled real-time guest recognition for personalized service
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CRM now reliably tracks guests across channels
Reduced data infrastructure costs
Staff can personalize experiences with real-time guest context
Digital and physical experiences connected through data
