Abbondanza Marketing / Lavori Selezionati / Caso 001
Caso 001

Un gruppo di hotel boutique in Lombardia ha dimezzato il carico della reception aumentando i direct booking.

Hospitality AI Multi-proprietà
−50%Carico reception recuperato
+30%Quota di direct booking
<2 minTempo medio di prima risposta
Il Brief

Un piccolo gruppo di hotel boutique con tre proprietà in Lombardia — scala boutique, standard alti, e un front desk che annegava in richieste ripetitive. La maggior parte non erano chiamate di prenotazione. Erano le stesse dodici domande, fatte da ogni canale, in tre lingue, tutto il giorno.

La Sfida

La reception rispondeva alle stesse domande trecento volte al mese.

Tipologie di camera. Parcheggio. Late check-in. Orari colazione. Spa. Allergies. Pet policy. Each property routed enquiries through a different inbox, a different phone line, and a chat widget that nobody answered consistently. The team was burned out, OTA dependence was creeping up, and direct booking rate sat well below industry benchmarks.

The brief: stop the bleed on reception time. Convert more enquiries directly. Don't compromise the warm, hands-on guest experience that defines the brand.

L'Approccio

Four moves, executed in sequence.

01

Channel audit

Mapped every guest touchpoint — calls, email, chat, social DMs, OTA messaging — and classified six months of enquiries by intent and language.

02

Multilingual AI agent

Deployed an AI concierge across web chat, booking widget, and email — trained on property data, policies, and tone. Italian, English, German.

03

Direct-booking flow

Wired the agent into the PMS with a dynamic rate-quote handoff. Soft incentives for direct bookings (early check-in, room upgrade) surfaced contextually.

04

Property-page SEO

Refreshed each property page, schema, and Google Business Profile. Local search visibility on 'boutique hotel + village' terms rebuilt from scratch.

I Risultati

What changed, measurably.

−50% reception hrsRecurring enquiries handled by the agent freed half of the front-desk team's daily load.
+30% direct shareDirect bookings grew as a share of total reservations, reducing OTA fee exposure.
<2 min responseAverage first-response time on web enquiries collapsed from hours to under two minutes, 24/7.
Stable CSATGuest-satisfaction scores held steady — AI handled the rote work; humans kept the warmth.
Stack & ingaggio

What we used.

AItempo OpenAI Hotel PMS Google Business Profile Astro · Cloudflare Pages
Engagement: 6 months · Hospitality · 3 boutique properties · Lombardy
I Numeri

L'impatto, in barre.

Dodici mesi dopo il go-live, misurati rispetto alla baseline pre-engagement.

−50%
Ore di reception recuperate
Prima
40 ore / settimana
Dopo
20 ore / settimana
Ore-persona settimanali assorbite dall'AI concierge sulle richieste ricorrenti.
+30 pt
Quota di booking diretto
Prima
20%
Dopo
50%
Quota di prenotazioni sul canale diretto — minore esposizione alle commissioni OTA.
<2 min
Tempo di prima risposta
Prima
~3 ore
Dopo
<2 minuti
Tempo medio tra la richiesta web e la prima risposta, 24/7, nella lingua dell'ospite.
FAQ

Domande, risposte.

How was reception workload halved? +
A multilingual concierge AI took over the recurring enquiry load across web chat, booking widget, and email — the same twelve questions asked through every channel in three languages — freeing roughly half of the front-desk team's daily load.
Did direct bookings really increase? +
Yes. Wiring the agent into the PMS with a dynamic rate-quote handoff and contextual direct-booking incentives grew direct bookings as a share of total reservations, reducing OTA fee exposure.
Did guest experience suffer? +
No — guest-satisfaction scores held steady. The AI handled the rote work while humans kept the warm, hands-on experience that defines the brand.

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