SaaS Development Company in Barcelona

Hospitality / Travel Technology

A Barcelona-based boutique hotel group (8 properties across Barcelona, Madrid, and Seville — 680 rooms total, €42 million annual revenue) was operating with a legacy PMS (Property Management System) that couldn't support their growth strategy. Problems: no guest intelligence (the PMS stored reservation data but had no understanding of guest preferences, behaviour, or value — a guest who stayed 5 times was treated the same as a first-time visitor), fragmented operations (each property used different tools for housekeeping, maintenance, and F&B — no unified operations view across the group), poor revenue management (pricing was set manually by property managers based on intuition — no dynamic pricing based on demand, competition, and events), and tourist communication (80% of guests were international tourists speaking English, French, German, or other languages — the PMS supported only Spanish, and staff communication with guests was inconsistent). The hotel group estimated that better technology could increase RevPAR (Revenue Per Available Room) by 12% and improve guest satisfaction from 4.2 to 4.6 on TripAdvisor.

We built a modern hospitality operations SaaS with guest intelligence, unified operations, AI-driven revenue management, and multilingual guest communication. (1) Guest intelligence platform: understanding each guest. Unified guest profile: combining data from PMS reservations, restaurant visits, spa bookings, and staff notes into a single guest profile. A returning guest's profile shows: stay history across all 8 properties, room preferences (high floor, quiet room, extra pillows), dietary requirements, birthday and anniversary dates, and staff notes ("Prefers late checkout, always asks about local restaurant recommendations"). Pre-arrival personalisation: 48 hours before arrival, the front desk receives a guest brief — returning guests are greeted by name with their preferences pre-configured. New guests receive a welcome email asking about preferences — building the profile from the first interaction. Guest value scoring: classifying guests by lifetime value — one-time tourists, repeat visitors, high-value regulars, and corporate accounts — enabling differentiated service levels. High-value guests receive automatic upgrades when available, personalised welcome amenities, and proactive outreach for future visits. (2) Unified operations: one platform for all property operations. Housekeeping: digital room status (dirty, being cleaned, inspected, ready), cleaning checklists with photo verification, and minibar inventory tracking. Staff receive assignments on mobile devices with priority ordering based on expected guest arrival times. Maintenance: issue reporting, work order management, and preventive maintenance scheduling — a front desk agent reports a broken AC in room 304, a maintenance ticket is created, assigned, and tracked to resolution with the guest automatically notified. F&B operations: restaurant POS integration, room service ordering via guest app, and inventory management — connecting restaurant operations with the guest profile (dietary requirements, wine preferences). Cross-property coordination: when a guest staying at the Barcelona property mentions wanting to visit Madrid next month, the Madrid property receives the guest profile with preferences and a warm introduction. (3) AI revenue management: dynamic pricing that maximises RevPAR. Demand forecasting: predicting occupancy 90 days ahead based on: historical patterns (seasonal, day-of-week), Barcelona event calendar (Mobile World Congress, La Mercè, FC Barcelona matches), competitive pricing (monitoring competitor rates through rate shopping), and booking pace (comparing current bookings against historical pace to detect demand above or below normal). Dynamic pricing: room rates adjusted automatically based on demand forecasts — higher rates during high-demand periods, promotional rates during soft periods. The AI optimises for total revenue (rooms + F&B + spa), not just room revenue — a lower room rate that drives high-spending guests can generate more total revenue. Length-of-stay optimisation: pricing incentives for longer stays during soft periods — "Stay 3 nights, save 15%" — smoothing occupancy across the week. Channel management: optimising rate distribution across OTAs (Booking.com, Expedia), direct booking (website), and wholesale channels — with the direct booking channel receiving the best rate to incentivise direct relationships. (4) Multilingual guest communication: serving international tourists. Guest app: a multilingual mobile app (English, Spanish, Catalan, French, German, Italian, Portuguese, Japanese, Chinese) providing: digital check-in, room key, service requests, restaurant reservations, local recommendations, and direct messaging with staff. AI translation: staff messages to guests are automatically translated — a Spanish-speaking housekeeper can respond to a German guest's request for extra towels with the message automatically translated to German. City recommendations: curated Barcelona, Madrid, and Seville recommendations from the concierge team — restaurants, cultural sites, local experiences — presented in the guest's language with map integration and booking links.

RevPAR improvement: 16% increase across the 8-property portfolio (exceeding the 12% target). Revenue impact: the RevPAR increase translated to €6.7 million in additional annual revenue. Dynamic pricing: the AI revenue management was the primary driver — rates automatically increased during high-demand periods that human managers had underpriced (Mobile World Congress week, for example, was priced 35% higher than the previous year's manual rates, with no decrease in occupancy). Direct booking: the guest app and direct booking incentives increased direct bookings from 28% to 44% of total — reducing OTA commission costs by €1.2 million annually. Guest satisfaction: TripAdvisor average rating improved from 4.2 to 4.7 (exceeding the 4.6 target). Key drivers: pre-arrival personalisation (guests are amazed to be greeted by name with preferences remembered), the multilingual guest app (eliminating language barriers), and faster issue resolution (maintenance requests resolved in average 22 minutes, from 3.5 hours). Returning guests: repeat visit rate increased from 12% to 21% — the guest intelligence and personalised service created loyalty. Returning guests spend 34% more per stay than first-time visitors and book direct 78% of the time (vs. 44% for first-time). Operational efficiency: housekeeping time per room reduced 15% through optimised assignment routing. Maintenance issue resolution: 22 minutes average (from 3.5 hours). Staff satisfaction improved — staff report that the mobile tools reduce administrative burden and let them focus on guest interaction. Guest app adoption: 62% of guests download and use the app. AI translation: 14,000 translated messages in year one — enabling staff-guest communication that would have been impossible otherwise. The most popular app feature: local recommendations (used by 78% of app users) — the digital concierge drives off-property experiences that guests rate highly. Development investment: €380,000 over 16 weeks.