Identify price feedback sentiment using AI

Below is a free classifier to identify price feedback sentiment. Just input your text, and our AI will predict the sentiment of customer feedback regarding product prices - in just seconds.

price feedback sentiment identifier

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Get started

    import nyckel
    
    credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
    nyckel.invoke("price-feedback-sentiment", "your_text_here", credentials)
                

    fetch('https://www.nyckel.com/v1/functions/price-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/price-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 customer feedback regarding product prices.

This pretrained text model uses a Nyckel-created dataset and has 18 labels, including Content, Discontent, Dissatisfied, Enthusiastic, Mixed, Negative, Neutral, Optimistic, Pessimistic and Positive.

We'll also show a confidence score (the higher the number, the more confident the AI model is around the sentiment of customer feedback regarding product prices).

Whether you're just curious or building price feedback sentiment detection into your application, we hope our classifier proves helpful.

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Need to identify price feedback sentiment at scale?

Get API or Zapier access to this classifier for free. It's perfect for:



  • Customer Service Improvement: By integrating the 'price feedback sentiment' identifier, businesses can analyze customer feedback regarding product prices to gauge overall satisfaction. This can help identify common pain points related to pricing, allowing companies to make data-driven adjustments to their pricing strategies.

  • Pricing Strategy Optimization: Companies can utilize sentiment analysis on price-related feedback to understand how price changes impact customer perception. This insight enables businesses to refine their pricing models, potentially leading to better sales performance and improved customer retention.

  • Product Launch Assessment: During product launches, the function can analyze sentiment around pricing feedback for new products. Understanding whether customers perceive the price as fair or excessive can inform future marketing and pricing decisions.

  • Competitive Analysis: The 'price feedback sentiment' identifier can provide valuable insights into how your pricing compares to competitors. By analyzing sentiment data related to competitor prices, businesses can identify areas to improve their offerings or adjust positioning in the market.

  • Targeted Marketing Campaigns: By evaluating sentiment around pricing, businesses can tailor their marketing campaigns to address customer concerns. If feedback shows negative sentiment due to pricing, targeted promotions or discounts can be developed to mitigate customer dissatisfaction.

  • Inventory Management: The function can help businesses understand the sentiment around pricing to inform their inventory decisions. If customers are unhappy with prices, it might indicate a need for adjusting stock levels or finding alternative pricing models to enhance sales.

  • Customer Segmentation: Analyzing sentiment regarding pricing feedback can assist in segmenting customers based on their price sensitivity. Businesses can use this data to create personalized offers and improve customer engagement strategies by addressing the needs of different segments more effectively.

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