Identify seller feedback sentiment
using AI
Below is a free classifier to identify seller feedback sentiment. Just input your text, and our AI will predict the sentiment of seller feedback - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("seller-feedback-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/seller-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/seller-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 seller feedback.
This pretrained text model uses a Nyckel-created dataset and has 20 labels, including Bad, Commendable, Dissatisfied, Excellent, Fair, Frustrated, Good, Happy, Mixed and Negative.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of seller feedback).
Whether you're just curious or building seller feedback sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify seller feedback sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- E-commerce Platform Improvement: This function can analyze seller feedback to determine overall customer sentiment, enabling e-commerce platforms to identify high-performing sellers and those needing support. By gaining insights into customer perceptions, the platform can implement training programs or improve seller guidelines to enhance user experience.
- Product Development Insights: Businesses can leverage sentiment analysis of seller feedback to inform product development decisions. By identifying common themes in positive and negative feedback, companies can prioritize product features or resolve issues that are affecting customer satisfaction.
- Market Reputation Management: Companies can monitor seller feedback sentiment to manage their market reputation proactively. By detecting negative sentiment early, they can take corrective actions to prevent long-term brand damage and maintain customer trust.
- Vendor Selection and Performance Evaluation: Retailers can utilize sentiment analysis to evaluate the performance of their vendors based on seller feedback. By comparing sentiment scores, they can make informed decisions about which vendors to continue partnerships with or consider alternatives.
- Targeted Marketing Strategies: Businesses can tailor their marketing strategies based on the sentiment of seller feedback. Positive feedback can be highlighted in promotional materials, while strategies can be adjusted to address concerns raised in negative sentiment analysis, thereby driving more effective marketing campaigns.
- Customer Support Enhancement: By analyzing seller feedback sentiment, companies can identify recurring issues or common complaints. This insight enables businesses to enhance their customer support functions by addressing specific problem areas, thus improving overall customer satisfaction.
- Training and Development for Sellers: E-commerce platforms can use sentiment analysis to identify training needs for sellers. By understanding feedback trends, they can design targeted training programs to help sellers improve their service quality, leading to better customer experiences and higher sales.