Identify buyer feedback sentiment
using AI
Below is a free classifier to identify buyer feedback sentiment. Just input your text, and our AI will predict the sentiment of buyer feedback - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("buyer-feedback-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/buyer-feedback-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/buyer-feedback-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 buyer feedback.
This pretrained text model uses a Nyckel-created dataset and has 16 labels, including Displeased, Dissatisfied, Great Experience, Happy, Mixed, Negative, Neutral, Not Recommended, Pleased and Poor Experience.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of buyer feedback).
Whether you're just curious or building buyer feedback sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify buyer feedback sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Satisfaction Analysis: This function can be used to analyze buyer feedback across various products, categorizing sentiments as positive, negative, or neutral. By identifying trends in customer sentiment, businesses can address areas of concern and enhance product offerings.
- Product Improvement Insights: Businesses can leverage sentiment analysis from buyer feedback to pinpoint specific features or aspects that customers appreciate or dislike. This information can drive product innovation and improvements based on real user experiences.
- Marketing Strategy Optimization: By integrating buyer feedback sentiment analysis, companies can refine their marketing campaigns to resonate more with customer emotions. Understanding what sentiments drive customer engagement can help tailor messages that improve conversion rates.
- Reputation Management: Companies can utilize the sentiment identifier to monitor and manage their brand reputation in real-time. By quickly identifying negative sentiments, businesses can take proactive measures to resolve issues and mitigate potential harm to their brand.
- Competitive Analysis: By analyzing feedback from competitors’ products, businesses can gauge market sentiment and evaluate where they stand in comparison. This insight can inform strategic decisions regarding product positioning and competitive advantages.
- Customer Support Enhancement: Analyzing the sentiment in buyer feedback can help organizations identify common pain points and improve customer support services. Understanding the emotional tone of feedback can guide the development of FAQs and help resources that directly address customer concerns.
- Trend Prediction: The sentiment identification function can analyze historical buyer feedback to identify emerging trends in consumer preferences or dissatisfaction. By anticipating changes in sentiment, businesses can be proactive in adjusting their strategies and product offerings.