+12%Revenue Per Available Room (RevPAR) vs. non-responsive hotels
+12%Monthly revenue growth from acting on guest feedback
+10%Increase in guest loyalty
+40%Previously unactionable negative reviews now surfaced and resolved
About The Client
Our client is a 5-star luxury hotel chain with 11 award-winning properties across key destinations in India. Guest feedback arrived scattered across online reviews, social media, and in-house feedback forms, with no way to centralize it, filter out noise, or tie it back to the performance of specific properties or business units. BigOhTech designed and built an AI-driven sentiment analysis platform to close that gap, from architecture through launch.Business Challenges
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Our Approach
Unified data ingestion We built APIs to pull reviews from every major source — online review platforms, social media, and feedback forms — and map them into a single database, replacing the fragmented, manual process the client relied on before.
Preprocessing at scale Pandas handled cleaning and preprocessing across large volumes of unstructured text, stripping out noise and irrelevant content before it reached the analysis layer.
NLP-based sentiment classification Google BERT was used to extract relevant keywords and classify each review as positive, negative, or neutral, giving the client a consistent, automated read on sentiment instead of manual tagging.
Deep learning for nuance A CNN was trained to learn patterns across different parts of each sentence, and deep learning models handled the non-linear relationships in the data — the kind of subtlety that keyword-matching alone misses (e.g., sarcasm, mixed sentiment within one review, or context-dependent complaints).
From insight to action The client used the classified data to identify concrete, fixable issues — slow service, outdated facilities, cleanliness gaps — and acted on them directly: staff training, facility renovations, and increased room-cleaning frequency. Positive sentiment was fed back into marketing to highlight genuine strengths and unique selling points.
One dashboard, two clicks All of this rolled up into a single unified dashboard giving business owners a full sentiment view of any property or vertical in just two clicks — replacing what had been a fragmented, multi-source manual review process.
CASE STUDY - AI/ML
AI & AR-powered Game Analytics for a Fantasy Sports Platform
Our customer here comes from a techno sports background. They provide services to various sports agencies and have entered the consumer market offering different products for the segment.
The Impact
+12% RevPAR compared to hotels in the chain that did not respond to reviews — directly tying responsiveness to revenue.
+12% monthly revenue increase attributable to acting on the feedback the platform surfaced.
+10% guest loyalty driven by visibly responding to and acting on guest feedback.
40%+ of previously unactionable negative reviews became a source of concrete operational fixes (staff training, renovations, cleaning frequency) instead of sitting unresolved.
