Introduction

Hospitality marketer desired recommendation engine that provide Personalization and Intelligence to drive guest satisfaction.

• Tracking Brand Reputation

• Digitalizing Journey

• Employee Engagement

• Insight Into Departments

• White LabelingNLP complexity across multiple languages and dialects.

• Implemented Natural Language processing in different languages

• Built deep learning models to summarize and create appropriate weightage for recommendations

• Used model input to personalize recommendations

• Leveraged Lexical Analytics platform using Stanford NLP and custom algorithms

• Created Insights for hoteliers to improve revenue for hoteliers

 Technological Framework

Why these technologies?

They combine rule-based language understanding (Stanford NLP) with neural-network flexibility (PyTorch/TensorFlow), enabling accurate, domain-specific sentiment and topic extraction at scale. 

Why these tools?

Salesforce Exact Target and Cordial integrate marketing automation directly with the analytics platform — enabling behaviour-triggered campaigns fired in near real time based on customer segment and reputation signals.

Why this Setup?

Cross-platform review aggregation covering 51 countries and 1M+ monthly reviews feeds directly into the ML recommendation engine, ensuring insights are always current and regionally relevant.

Takeaway

Zapcom's hospitality reputation platform now operates across 51 countries, serving 4000+ customers with 5+ products, achieving 28% average conversion rate improvement and processing 1M+ monthly reviews.