Identify customer sentiment
using AI
Below is a free classifier to identify customer sentiment. Just input your text, and our AI will predict customer sentiment for various product categories - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("customer-sentiment", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/customer-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/customer-sentiment/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict customer sentiment for various product categories.
This pretrained text model uses a Nyckel-created dataset and has 8 labels, including Mixed, Negative, Neutral, Positive, Somewhat Negative, Somewhat Positive, Very Negative and Very Positive.
We'll also show a confidence score (the higher the number, the more confident the AI model is around customer sentiment for various product categories).
Whether you're just curious or building customer sentiment detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify customer sentiment at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Product Feedback Analysis: This use case involves the automatic classification of customer sentiment from product reviews and feedback forms. By assessing whether the sentiment is positive, negative, or neutral, businesses can gain insights into customer satisfaction and product performance, enabling them to make informed decisions regarding product improvements.
- Social Media Monitoring: Companies can utilize sentiment analysis on social media platforms to gauge public opinion about their brand, products, and campaigns. This allows businesses to proactively address negative sentiments, engage with satisfied customers, and adapt marketing strategies based on real-time feedback.
- Customer Support Optimization: By integrating sentiment classification into customer support interactions—such as emails, chat logs, and support tickets—businesses can prioritize responses. Identifying frustrated customers enables faster resolutions, leading to improved customer satisfaction and retention.
- Market Research Insights: Businesses can analyze sentiment in survey responses and focus group discussions to understand consumer perspectives on market trends. This information is valuable for strategic planning, helping organizations align their products and services with customer preferences.
- Brand Reputation Management: Companies can monitor sentiment across various digital channels to protect and enhance their brand reputation. By identifying and addressing negative sentiments swiftly, organizations can mitigate potential PR crises and reinforce positive brand perceptions.
- Advertising Campaign Evaluation: Marketers can use sentiment analysis to assess the effectiveness of advertising campaigns by analyzing customer reactions across different platforms. Understanding sentiment dynamics allows for the optimization of future campaigns and better-targeted advertising strategies.
- E-commerce Personalization: In e-commerce platforms, sentiment classification can help tailor the shopping experience by analyzing reviews and customer interactions. By recommending products based on positive sentiment toward similar items, businesses can enhance customer engagement and drive sales.