customer_support · travel · workflow
Xanterra Travel Collection achieves 74% containment rate and $3.3M revenue lift with Cresta AI Agents
Xanterra's Central Reservations team faced extremely high inquiry volumes across multiple travel brands and four contact centers, making it difficult to maintain fast, consistent, and personal service at scale. QA was entirely manual and managers lacked the visibility and tools needed to coach agents effectively.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Guest inquiry via chat or voice
Guest inquiries arrive via chat or voice at the Central Reservations team.
Tools used
CrestaAI AgentAgent AssistConversational IntelligenceAI Analyst
Outcome
Xanterra achieved a 74% containment rate across AI Agents and a $3.3M revenue increase through reinforced sales behaviors, while avoiding hundreds of thousands in potential guest recovery costs.
Results
Volume74%
Cost replaced$3.3M
Grounding & classification
Source type: vendor customer story
39 fields verified against source quotes.
agent assistai agentconversational aisummarizationcall recordingchat transcripthuman review describedmetric backednamed customerproduction runtime claimedtools describedworkflow describedhospitalitytravelcost reductiondeflection rateemployee productivityrevenue increasevendor customer storycall center aicustomer supportquality assurancesales opsautonomous resolutionescalation workflow