Identify if customer complaint contains a profanity
using AI
Below is a free classifier to identify if customer complaint contains a profanity. Just input your text, and our AI will predict if the customer complaint contains a profanity - in just seconds.
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Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("if-customer-complaint-contains-a-profanity", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/if-customer-complaint-contains-a-profanity/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/if-customer-complaint-contains-a-profanity/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if the customer complaint contains a profanity.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including Clean and Contains Profanity.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the customer complaint contains a profanity).
Whether you're just curious or building if customer complaint contains a profanity detection into your application, we hope our classifier proves helpful.
Related Classifiers
Need to identify if customer complaint contains a profanity at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Support Prioritization: This use case involves automatically flagging complaints that contain profanity for immediate attention by customer support teams. By prioritizing these interactions, businesses can ensure that potentially volatile issues are addressed swiftly, enhancing customer satisfaction and retention.
- Sentiment Analysis Enhancement: Integrating profanity detection into existing sentiment analysis tools can improve the accuracy of understanding customer emotions. By identifying complaints with strong negative language, organizations can better gauge the severity of customer discontent and tailor their responses accordingly.
- Brand Protection and Reputation Management: Monitoring customer complaints for profanity helps businesses protect their brand image. By escalating these instances for review, companies can address public relations issues proactively and mitigate the spread of negativity related to their products or services.
- Training and Development Feedback: This function can analyze customer complaints to identify patterns of offensive language, which can be invaluable for training customer service representatives. Understanding the types of interactions that escalate to profanity can guide the development of better communication strategies and employee training programs.
- Automated Moderation in Online Platforms: For businesses operating online platforms or forums, detecting profanity in customer complaints can help maintain a respectful community environment. By automatically moderating such content, companies can foster a positive atmosphere and reduce the risk of harassment or toxic behavior within their channels.
- Customer Insights and Market Research: Profanity in customer complaints can signal deeper issues with a product or service. By analyzing these instances, companies can derive insights into customer pain points and preferences, allowing for better product adjustments or new feature development that directly addresses customer needs.
- Compliance and Risk Management: In regulated industries, monitoring for profanity in customer complaints can support compliance with industry standards regarding customer relations. By documenting and analyzing these complaints, businesses can ensure they are meeting regulations while also protecting themselves against potential legal repercussions stemming from abusive language.