Identify support request repeated
using AI
Below is a free classifier to identify support request repeated. Just input your text, and our AI will predict if the support request is repeated - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("support-request-repeated", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/support-request-repeated/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/support-request-repeated/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict if the support request is repeated.
This pretrained text model uses a Nyckel-created dataset and has 2 labels, including New Support Request and Repeated Support Request.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the support request is repeated).
Whether you're just curious or building support request repeated detection into your application, we hope our classifier proves helpful.
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Need to identify support request repeated at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Customer Service Optimization: This use case focuses on improving customer service efficiency by identifying repeated support requests. By flagging these requests, teams can prioritize addressing the underlying issues, reducing overall workload and enhancing customer satisfaction.
- Knowledge Base Enhancement: By analyzing support requests that are frequently repeated, organizations can identify gaps in their knowledge base. This enables them to create or update articles that address common issues, empowering customers to find solutions independently and decreasing the number of repetitive inquiries.
- Predictive Resource Allocation: Organizations can leverage the 'support request repeated' identifier to predict and allocate resources effectively for support teams. Understanding the frequency and types of repeated requests helps management anticipate peak periods and ensure sufficient staffing and expertise are available.
- Quality Control Improvement: Identifying repeated support requests can signal potential problems with products or services. This information can guide quality assurance teams to investigate and resolve root causes, improving overall service quality and customer experience.
- Customer Retention Strategy: By recognizing patterns in repeated support requests, businesses can proactively reach out to customers at risk of dissatisfaction. Offering tailored support or solutions can enhance customer loyalty and prevent churn caused by unresolved issues.
- Accountability Metrics for Team Performance: The 'support request repeated' identifier can be utilized as a metric for evaluating team performance. It highlights areas where team members may need additional training or support, allowing for targeted professional development and improved service delivery.
- Automated Escalation Process: Implementing automated workflows based on repeated support requests can streamline escalation processes. By automatically elevating unresolved issues after a certain threshold, businesses can ensure that critical problems are addressed promptly, maintaining customer trust and confidence.