TourRadar saves 780+ hours monthly and resolves 75%+ of customer inquiries with boost.ai generative AI
TourRadar's support team managed a high volume of diverse inquiries for a global customer base across multiple time zones and wanted to move beyond rules-based chatbots that provided rigid, templated responses, requiring instead a scalable solution capable of dynamic, contextually relevant answers without constant manual content updates.
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 · Customer submits support inquiry
The AI Agent handles inquiries covering booking and tour details, account support, cancellations, and payment issues on TourRadar's website.
Tools used
boost.aiGenerative Action
Outcome
The AI Agent handles 82% of all customer inquiries with 98% accuracy, live chat deflection improved from 50% to 80%, and the team saves 780+ hours per month—580 on live chat and 200 on written replies—with only 20% of conversations requiring escalation to a human agent.
What failed first
A rigid, keyword-based chatbot previously in use provided templated responses that could not handle the inherent complexity of travel booking inquiries.