-70% Reduction in average wait times
+90%Increase in customer satisfaction with support
+85%Improvement in team efficiency
3,000+Distinct complaint types handled across the hotel portfolio
About The Client
The client is a leading hospitality group operating a diverse portfolio of hotels, looking to modernize customer support, requests, and complaint handling, while also using the same channel to upsell and cross-sell. BigOhTech designed and launched an NLU-powered chatbot on both the website and WhatsApp to handle the full range of hotel-related questions, concerns, and bookings. The Challenge
Together, these operational hurdles led to slower response times, increased staff workload, and inconsistent guest experiences, directly impacting customer satisfaction and overall loyalty.
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Our Approach
NLU built on a proprietary GPT-3 engine BigOhTech used its own GPT-3-based NLU engine, trained under supervision to accurately identify user intent — including nuanced complaints, not just simple FAQ-style questions — so conversations felt context-aware rather than scripted.
Meeting guests where they already are: WhatsApp Rather than requiring guests to use a separate app or web portal, the bot was integrated directly into WhatsApp, letting guests book, order, or resolve issues on the platform they already use daily.
Intent-driven workflows Machine learning-based intent recognition routed each guest through the right process, booking, food ordering, issue resolution, with step-by-step guidance rather than a single flat menu of options.
24/7 coverage The bot provided round-the-clock support, directly targeting the wait-time problem: guests got an immediate response regardless of when they reached out, instead of waiting on staffed support hours.
Case Study
Dynamic Pricing Revolutionizes Hotel Revenue with AI and Machine Learning
Boost hotel revenue with AI-powered dynamic pricing. Discover how BigOhTech automated rate optimization across OTAs, increased revenue by 60%, reduced manual effort by 35%, and drove 75% more bookings through real-time market analysis and machine learning.Learn how predictive analytics and automated pricing decisions helped maximize occupancy and profitability in a competitive hospitality market.
The Impact
70% reduction in average wait times, the direct result of 24/7 automated coverage replacing hours-limited human response.
90% increase in customer satisfaction, tracking closely with faster resolution and a more natural, context-aware conversation experience.
85% improvement in team efficiency, as routine requests were handled by the bot and human agents were freed for complex, high-value interactions.
Support team load reduced at scale, given the bot's ability to handle a meaningful share of the 3,000+ complaint types the group was fielding.
A more cost-effective support model, automation absorbed routine volume, while still preserving a personalized tone for guests.
