Identify guest reviews sentiment
using AI
Below is a free classifier to identify guest reviews sentiment. Just input your text, and our AI will predict the sentiment of guest reviews - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("guest-reviews-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/guest-reviews-sentiment/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/guest-reviews-sentiment/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the sentiment of guest reviews.
This pretrained text model uses a Nyckel-created dataset and has 14 labels, including Disappointed, Dissatisfied, Enthusiastic, Favorable, Mixed, Negative, Neutral, Optimistic, Pessimistic and Positive.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of guest reviews).
Whether you're just curious or building guest reviews sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify guest reviews sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Feedback Analysis: The 'guest reviews sentiment' identifier can be used to automatically analyze customer reviews for hotels and restaurants. By classifying sentiments as positive, negative, or neutral, businesses can gauge overall guest satisfaction and identify areas for improvement.
- Reputation Management: Hotels can utilize the sentiment analysis to track and manage their online reputation. By understanding the sentiments expressed in reviews over time, they can proactively address issues and enhance their brand image.
- Service Improvement Insights: Businesses can aggregate sentiment data from guest reviews to uncover trends related to specific services or amenities. This data can inform management decisions, helping to improve service offerings and guest experiences.
- Competitive Analysis: The sentiment identifier can be employed to compare guest reviews across competing hotels or restaurants. This helps businesses identify what guests appreciate or dislike about their competitors, allowing them to differentiate their offerings strategically.
- Marketing Strategy Optimization: By analyzing sentiments in guest reviews about various aspects like pricing, services, and cleanliness, hotels can refine their marketing strategies. Positive feedback can be highlighted in promotions, while negative points can be addressed in targeted campaigns.
- Real-Time Alerts for Management: The sentiment analysis tool can be integrated into a real-time monitoring system to alert managers when reviews reflect negative sentiments. This proactive approach enables rapid response to guest complaints before they escalate or impact overall ratings.
- Employee Performance Evaluation: Guest reviews often include feedback on staff performance. By analyzing sentiments related to employee interactions, management can identify areas of strength and opportunities for training, thereby enhancing staff effectiveness and guest satisfaction.