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Automating Sentiment Analysis for US based hotel with QuantumDataLytica
Table of Contents
For hotels, online reviews are a crucial factor influencing guest decisions and brand reputation. Google My Business (GMB) reviews offer direct customer feedback, but manually analyzing thousands of reviews across multiple locations is time-consuming and inefficient.
US Based Hotel needed a solution to automate review analysis, identify key sentiment trends, and respond proactively to customer concerns. Softqube Technologies, leveraging
QuantumDataLytica, designed a workflow that automatically gathers GMB reviews, processes them, and provides real-time sentiment insights—allowing hotel management to make data-driven decisions effortlessly.
The Challenge: Understanding Guest Sentiment at Scale
Client: US Based Hotel
Challenges Faced by the Hotel Management:
Manually analyzing hundreds of GMB reviews across different guest experiences (rooms, service, food,
cleanliness).
Delayed response to negative reviews, leading to missed opportunities for service recovery.
Difficulty in identifying recurring issues that impact guest satisfaction.
Lack of structured, data-driven insights to improve guest experiences and operational efficiency.
The hotel needed a fully automated solution to aggregate, analyze, and visualize guest sentiment trends—enabling faster decision-making and service enhancements.
The Solution: QuantumDataLytica’s No-Code Sentiment Analysis Workflow
Softqube Technologies developed a custom workflow in QuantumDataLytica to:
1. Extract Google My Business Reviews
Connects to the GMB API and gathers reviews from US Based Hotel in real-time.
2. Process and Clean Data
Standardizes review formats, remove duplicates, and organizes data for analysis.
3. Perform Sentiment Analysis
Uses Natural Language Processing (NLP) to categorize reviews as Positive, Negative, or Neutral based on guest feedback.
4. Generate Actionable Insights
Provides detailed reports on recurring issues (e.g., service delays, cleanliness concerns, breakfast quality).
5. Automate Alerts for Negative Reviews
Sends real-time notifications to hotel management, allowing immediate resolution of guest complaints.
Sample Data & Sentiment Analysis Outcome
Raw Google My Business Reviews Sample from US Based Hotel
| Reviewer UserName | Review Text |
|---|---|
| Nikki Land | We really enjoyed the pool area even in the dead of winter our room was clean modern and comfortable the breakfast was good as a whole its definitely a bargain for the price, staff can be better trained and polite otherwise its good |
| Natalie Mercer | We were only in town for one night but it was the best night sleep ive had in months |
| Destiney Brown | Took awile to checkin understaffed pool was freezing whirlpool was closed people where in it though lukewarm water kids pool area was nice again cold though largest and weird issue was parking lot lights were so bright and shined right into windows got up to close curtains and couldnt because thick curtain was just a small panel didnt shut all the way so poor sleep from both parents breakfast was alright did the job |
| Anonymous | We arrived very late from our travels check in was fast and easy we had a room with a hot tub that we enjoyed very much we did have to clean it before getting in it however as there was what appeared to be pubic hairs left behind |
| Esther V | Ill start off with positives the pool area the young man that worked at the front desk and the maintenance guy all real nice breakfast was decent with a lot of selections the beds were absolutely disgusting we looked at rooms stained hairs just nasty |
Topic-Based Sentiment Analysis
Example of Topics that can be provided for Sentiment Analysis:
| Room | Staff | Stay | Pool | Breakfast | |
|---|---|---|---|---|---|
| Very Negative | 10% | 5% | 8% | 6% | 3% |
| Negative | 9% | 8% | 7% | 7% | 6% | Neutral | 14% | 10% | 9% | 13% | 15% |
| Positive | 31% | 29% | 29% | 31% | 36% |
| Very Positive | 36% | 48% | 47% | 43% | 40% |
Sentiment Analysis Output
| Reviewer UserName | Review Text | Sentiment |
|---|---|---|
| Nikki Land | We really enjoyed the pool area even in the dead of winter our room was clean modern and comfortable the breakfast was good as a whole its definitely a bargain for the price, staff can be better trained and polite otherwise its good | Positive |
| Natalie Mercer | We were only in town for one night but it was the best night sleep ive had in months | Very Positive |
| Destiney Brown | Took awile to checkin understaffed pool was freezing whirlpool was closed people where in it though lukewarm water kids pool area was nice again cold though largest and weird issue was parking lot lights were so bright and shined right into windows got up to close curtains and couldnt because thick curtain was just a small panel didnt shut all the way so poor sleep from both parents breakfast was alright did the job | Negative |
| Anonymous | We arrived very late from our travels check in was fast and easy we had a room with a hot tub that we enjoyed very much we did have to clean it before getting in it however as there was what appeared to be pubic hairs left behind | Neutral |
| Esther V | Ill start off with positives the pool area the young man that worked at the front desk and the maintenance guy all real nice breakfast was decent with a lot of selections the beds were absolutely disgusting we looked at rooms stained hairs just nasty | Negative |
Key Insights Generated
82% of reviews were positive, highlighting cleanliness, room quality, and staff friendliness.
12% of reviews were negative, citing slow check-in, housekeeping issues, and limited breakfast variety.
Most negative reviews were related to staffing and amenities, leading to service delays and lower satisfaction.
Negative sentiment correlated with a 15% drop in repeat bookings during peak months.
The Impact: How US Based Hotel Benefited
Before QuantumDataLytica
❌ Manually reviewed guest feedback, leading to slow response times.
❌ Missed patterns in negative sentiment, resulting in recurring complaints.
❌ Lack of structured data, making it hard to prioritize improvements.
After Implementing QuantumDataLytica
âś… Automated Review Analysis: The hotel now processes guest reviews in real-time.
âś… Immediate Alerts for Negative Reviews: Faster issue resolution and improved guest satisfaction.
âś… Data-Driven Decisions: Insights on guest preferences helped optimize staffing, housekeeping, and breakfast options.
âś… Increased Customer Retention: Proactive improvements led to a 20% boost in repeat guests within three months.
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Client Testimonial
“QuantumDataLytica has revolutionized how we manage guest feedback. What once took weeks to analyze is now available instantly. With real-time sentiment insights, we’ve improved service quality, responded faster to guest concerns, and seen a direct impact on our ratings and repeat bookings. This platform is a must-have for hotels looking to optimize guest experience!”
– Jessica Morgan, General Manager, US Based HotelConclusion
By automating sentiment analysis, QuantumDataLytica helps hotels like US Based Hotel transform raw guest feedback into actionable strategies—ensuring continuous service improvements and a superior guest experience.
