Global hotel brand scales support with agentic AI across 45+ brands and raises guest satisfaction — all without adding headcount.

Before Quiq, this hospitality brand’s customer service ran almost entirely on voice. The team identified four structural problems that no amount of hiring or training could fix.

Voice-based customer service created constant agent burnout. Phone interactions require agents to manage emotionally charged, real-time conversations with no pause — managing customer emotions, background noise, and interruptions simultaneously. There was no way to think before responding. The result was high stress, and high turnover. The company was spending heavily on hiring and training to replace agents who left, and the constant churn degraded service quality and team stability.

One agent at a time meant one customer at a time. A telephone agent can only help one person during a call. As call volume grew, the only answer was more agents. There was no way to improve efficiency.

When messaging launched via SMS, it proved guests wanted to text — but the channel hit a ceiling fast. Customers got messages from anonymous short codes with no branding. A guest had no way to tell the six-digit number was their hotel. There were no quick-reply buttons, no carousels, no way to self-serve. Completing a satisfaction survey meant typing out the word “five.” And as the team added Apple Messages for Business and WhatsApp, agents were managing parallel platforms with no shared context.

International guests had no digital option at all. Every month, transcripts from the company’s web and app showed the same theme: guests in other countries asking to get something done, receiving a phone number in response, and pushing back. One common phrase, read verbatim in the feedback: “I am on your website. I am in your app. Please do not make me call.”

The company needed something that could absorb volume across dozens of brands and dozens of countries, support agents without adding pressure, and give guests the digital experience they were already asking for.

Quiq rebuilt the company’s customer service communications from the channel layer up through the human agent experience. The deployment covered four interconnected areas.

The AI agent handles the high-volume, repeatable work. Quiq’s AI agent evaluates every incoming message within the context of the ongoing conversation, the active process guide, and information retrieved from integrated systems. Rather than following rigid, pre-built decision trees, it uses agentic reasoning to understand nuanced requests and manage multi-turn conversations. When a guest asks about room types, the AI agent queries the Properties API to pull real-time availability and generates a rich media carousel with room options tailored to their criteria. When a guest has a loyalty question, it retrieves account details and responds with specifics. When the request falls outside what the AI agent can resolve — a sensitive situation, a complaint requiring judgment, a booking that needs human discretion — it routes to a human agent with the full conversation history attached.

For complex interactions that involve humans, Quiq’s AI assistant monitors conversations as they happen and surfaces instant, personalized recommendations — room suggestions, policy details, relevant knowledge — based on what the guest has said and what the hotel has available. Human agents work from Quiq’s Digital Contact Center, a single interface that consolidates every channel. When a new agent picks up a conversation that was previously handled by someone else, Quiq generates an AI-powered summary of the interaction history. The agent does not scroll back through the transcript. They read the summary and continue.

The platform manages all channels in one place. RCS, Apple Messages for Business, WhatsApp, SMS, and web chat all surface in Quiq’s unified interface. Agents see a channel indicator but work identically regardless of where the guest is messaging from. Context follows the guest across channels: if a guest starts on WhatsApp and the next interaction comes via RCS, the history is there. Quiq also manages the lifecycle of every conversation automatically — moving inactive threads out of the active queue without requiring agent intervention, and restoring them instantly when the guest returns.

The deployment also addressed the company’s multilingual and multi-brand requirements. Quiq’s orchestration layer uses company-defined business logic alongside its AI to determine which brand’s voice and policies, which language to use, whether to route to service or sales, and when a human is required. For a company operating 45 or more distinct brands across more than 110 countries, this routing intelligence is a prerequisite for consistent quality at scale.

For guests, the most immediate change is access. A guest who previously had to call and wait on hold now has a branded messaging thread available whenever they need it — from a Google search result, from the phone tree when they call, from the hotel’s app, or from a link on the property’s website. No app download. No hold music.

The AI agent handles the most common questions without a human ever being involved. A guest asks about their rewards balance: the AI agent queries the loyalty system and responds with their specific account details. A guest wants to know if the room includes breakfast: the AI agent checks the property’s knowledge base and answers directly. A guest asks whether they can check in early: the AI agent looks up their reservation and the property’s policy and responds accordingly.

When the AI agent routes a conversation to a human, it transfers cleanly. The human agent receives the full conversation history, the context the AI gathered, and — from the AI assistant — an immediate suggested response or recommendation relevant to the guest’s situation. The guest doesn’t repeat themselves.

The way the Quiq platform works changes the guest experience in a way that turns out to matter a great deal. When a guest steps away mid-conversation — the doorbell rings, they get on a call, they simply set their phone down — the conversation doesn’t close. There is no timeout. There is no agent waiting and then ending the session. There is no starting over. The guest comes back and continues exactly where they left off. As the Director of Messaging described it directly: “There’s no disconnect button in a messaging interaction. That’s by design.”

The team is also actively building proactive outbound messaging flows. One example already underway: a guest arrives at a property early in the morning, before their room is ready. When the room becomes available ahead of check-in time, Quiq sends an outbound message notifying the guest — with a quick-reply button to confirm. The same flow can include an upsell: a slightly larger room available immediately for a modest upgrade, offered at the exact moment a travel-weary guest is most receptive.

The change in the agent experience was as significant as the change in the guest experience — and in some ways more measurable.

Zero agent turnover on the messaging team is the headline result from a workforce perspective. As they launched new AI agents, new messaging channels like Google RCS, the messaging team did not lose a single agent. Agents described the difference clearly: messaging gives them time to think before responding, rather than requiring an immediate verbal answer to an emotionally charged call. They can craft a response, check a policy, and send something they’re confident about. The pressure that drove burnout on the phone is structurally absent in messaging.

Agents moved from one conversation at a time to three to five simultaneously. This is the core efficiency shift that allows the company to handle more volume without proportional headcount growth. The asynchronous nature of messaging — the natural delays between a guest’s messages while they look something up or step away — creates working time. The Director of Messaging described it: “Those slices of delay where the agent’s waiting allow them to turn around and help the next customer. We don’t have to add headcount at the same rate that volume’s coming in.”

Quiq also gave human agents tools they didn’t have before: a built-in grammar checker, response templates for common scenarios, and the AI assistant surfacing relevant knowledge mid-conversation. These reduce errors, speed up resolution, and allow less experienced agents to perform at a higher level faster.

Channel management, which used to require agents to work across separate platforms for each messaging service, collapsed into one interface. An RCS conversation, a WhatsApp message, and an Apple Messages for Business thread all arrive in the same queue, handled the same way. Agents see which channel a message came from but otherwise work identically. The company’s routing logic — which brand, which language, which escalation path — runs in the background without requiring agents to manage it.

When a guest returns to a conversation that a different agent originally handled, Quiq’s AI conversation summary means the new agent is up to speed in seconds. The Director put it simply: “Quiq does this brilliant job of summarizing conversations. If another agent picks it up, they don’t have to go back and scroll up and down and read the entire transcript. They get this really beautiful AI summary of what the conversation was about.”

Quiq gave this hospitality group something it couldn’t build on voice: a customer service operation that scales with volume, not against it. 

• Zero agent turnover on the digital messaging team, and human agents reported significantly higher job satisfaction. The stressors that drove burnout on phone — real-time pressure, emotional intensity, no pause before responding — are absent in messaging.
• Human agents handle 3 to 5 conversations simultaneously, compared to one at a time on voice. This is the fundamental efficiency gain that breaks the linear relationship between volume and headcount.
• Response times improved by 40% during peak periods, as messaging eliminated the queuing pressure that made voice-only operations slow under load.
• 75% of guests preferred messaging to phone calls for its convenience and flexibility.
• CSAT scores on messaging run several percentage points above both voice and web chat — with the same pool of agents using the same policies. The lift comes from the channel and the experience, not a different workforce.
• 7 to 8% of callers choose messaging over voice when offered the option during the phone tree experience. Those conversations move to Quiq’s async model and are handled more efficiently than they would have been on the phone.
• 1.2 million messages handled on RCS alone last year, with a three-year forecast projecting significantly more. Messaging is now the fastest-growing customer service channel in the company’s portfolio.
• A unified agent interface across all messaging channels — RCS, Apple Messages for Business, WhatsApp, SMS, and web chat — reduced operational overhead and eliminated the context loss that came with managing parallel platforms.
• AI-generated conversation summaries eliminated the agent ramp-up time on handoffs. New human agents receive full context instantly, with no scrolling through transcripts.