Abstract-based Sentiment Analysis System for the Hospitality Industry
Abstract-based Sentiment Analysis System for the Hospitality Industry
- Technology: Power BI, Artificial Intelligence, Deep Learning, Natural Language Processing
- Industry: Restaurant, E-Commerce
Business Objectives
Hospitality owners often miss out on valuable insights hidden in customer feedback, reviews, and social media conversations.
Without a clear way to identify brand promoters versus detractors, they struggle to understand how their brand is truly perceived. Manual sentiment analysis is too slow and inconsistent to keep pace with the scale of customer interactions.
They also lack a benchmark to compare performance against industry peers, making it harder to measure where they stand. The objective was to extract meaningful insights from unstructured data and turn them into actionable intelligence that could improve decision-making and guest experience.
Solution
We built a robust natural language processing (NLP) model capable of capturing nuanced sentiments, even when text included sarcasm, irony, or mixed emotions.
The model was designed for high accuracy and scalability, ensuring it could generalize across diverse inputs and contexts. It was then integrated into an interactive dashboard that combined data ingestion, processing, and visualization in a single user-friendly interface.
Hospitality owners could now accurately classify sentiments—positive, negative, or neutral—in real time. Customizable sentiment scoring was added so businesses could align analysis with their unique goals.
By embedding NPS tracking, the system not only monitored customer sentiment but also benchmarked performance against industry peers and highlighted operational challenges that needed immediate action.
Benefits
The solution gave businesses a detailed understanding of customer perceptions, turning sentiment insights into a foundation for decision-making.
Hospitality owners were able to proactively resolve issues, leading to improved customer satisfaction, stronger loyalty, and higher repeat business.
Operations became more efficient as manual effort was replaced with automated, real-time sentiment analysis. The system also adapts seamlessly to multiple languages and domains, ensuring consistency across regions.
With continuous updates driven by user feedback, the model’s accuracy keeps improving over time. This future-proofed the solution and allowed the business to maintain a competitive edge through better guest experiences, higher retention, and smarter data-driven strategies.
In Our Customers’ Words
Real pleasure consulting with Kenexai to set up our company’s entire data warehouse and dashboards on AWS. I will definitely be reaching out to them for future work to be done. Our project was effective and 100% achieved what I planned to do in the beginning, in a shorter time frame and with less effort than I expected.
Hans
United States
CCR Data perform complex data migrations, we needed and extra pair of hands to restore an Oracle database and transfer the data to a Microsoft SQL database ready for our migration analysts to do their stuff. We would not hesitate in recommending or using Kenexai again and would be happy to outsource bigger projects to them in the future.
Henry Sykes
Director - CCR Data
I have used RA on numerous occasions over the past 2 years, specifically with Nitesh Solanki for the delivery on PDI ETL jobs. I am very happy with him and the high level of quality work he has provided. He seems to be available all the time and works extremely hard to deliver high quality solutions.
Mark Scriven
Technical Director - Value Ad