If you want to try this extractor, you can download it here:

Download Customer Feedback Extractor

customer-feedback-extractor.json

How do I import extractors?

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Document Input Examples

Here are some examples of the types of documents that this extractor can process.

Customer Feedback Data (PDF or Spreadsheets)

Perform some sentiment analysis on some data you already have. This extractor can help you extract feedback data from PDFs or spreadsheets.

Scanned Feedback Forms

Paper-based feedback forms collected in-person can be scanned and processed to digitize customer opinions and suggestions.

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Example Output

This extractor will produce JSON data that looks like the following:

{
    "formType": "Customer Feedback",
    "submissionDate": "2024-09-08",
    "customerName": "Jane Doe",
    "email": "[email protected]",
    "feedbackText": "The service was excellent, and the staff were very friendly. I especially appreciated the quick response time to my inquiry.",
    "rating": 5,
    "suggestions": "Perhaps offer more variety in your product catalog."
}

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Extractor

Here’s a template for a customer feedback form extractor with specific settings recommendations.

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JSON Schema

Here’s a tailored JSON schema for customer feedback forms. It focuses on capturing key feedback elements such as customer details, ratings, and textual feedback.

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Extraction Strategy

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Strategy: simple

For customer feedback forms, the simple strategy is generally sufficient. Feedback forms are typically short and focused, making them suitable for single-pass extraction.

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LLM Recommendation: google/gemini-2.0-flash-lite

google/gemini-2.0-flash-lite provides a good balance of cost-effectiveness and performance for processing customer feedback forms. Its vision capabilities are beneficial if handling scanned forms with potentially varied handwriting.

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Context Settings

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Chunk Size: 25k-50k

A chunk size of 25.000 to 50.000 tokens should comfortably accommodate most customer feedback forms.

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Include Text: true

Essential for capturing the textual feedback, customer names, and other text-based fields.

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Include Embedded Images: false

Embedded images are unlikely to be relevant in standard feedback forms and can be excluded.

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Include Page Screenshots: true

Page screenshots are recommended, especially for scanned forms. They help the LLM understand the layout and context of different fields, improving accuracy in extracting data from potentially less structured forms.

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Mark Images with IDs: false

Not needed for typical customer feedback extraction.




Next Steps

Learn how to extract some data

Step by step guide to extract data from documents using Data Wizard.

Extractors

Learn how to define and configure data extraction tasks.

Strategies

Understand different data processing strategies.

LLM Provider Configuration

Set up your Large Language Model API keys.

Integration

Embed Data Wizard into other applications using iFrames or APIs.