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https://github.com/thekartikeyamishra/ai-customer-feedback-summarizer

The AI Customer Feedback Summarizer is a Python-based application that processes customer feedback, extracts insights, and summarizes reviews. This basic version uses extractive summarization techniques, and the advanced version integrates advanced sentiment analysis, visualization, and industry-specific fine-tuning.
https://github.com/thekartikeyamishra/ai-customer-feedback-summarizer

ai chatbot gpt machine-learning matplotlib nltk pandas python scikit-learn streamlit

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The AI Customer Feedback Summarizer is a Python-based application that processes customer feedback, extracts insights, and summarizes reviews. This basic version uses extractive summarization techniques, and the advanced version integrates advanced sentiment analysis, visualization, and industry-specific fine-tuning.

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README 

        
# AI Customer Feedback Summarizer



For the next 15 days, I'll be creating and sharing 15 projects – one per day! Free versions will be open to all on my GitHub, and a low-cost paid version will be available too. Can't wait to hear your thoughts!



The **AI Customer Feedback Summarizer** is a Python-based application that processes customer feedback, extracts insights, and summarizes reviews. This basic version uses extractive summarization techniques, and the advanced version integrates advanced sentiment analysis, visualization, and industry-specific fine-tuning.



---



## AI Customer Feedback Summarizer (Advanced Version)



### **Overview**



The **AI Customer Feedback Summarizer** is a powerful tool for analyzing customer reviews. The advanced version leverages **OpenAI's GPT-3/4**, integrates sentiment analysis, and provides data visualizations, making it indispensable for businesses aiming to improve customer satisfaction.



---



## **Upgrade to the Advanced AI Customer Feedback Summarizer with Enhanced Features for just INR 299 at https://topmate.io/kartikeyahere/1343902**



### **Use the code "aifeedback" at checkout to get 15% off instantly.**



---



## **What Is It? (Advanced Version)**



The **AI Customer Feedback Summarizer**:



- Processes large volumes of customer feedback in seconds.

- Summarizes key insights, highlighting positive and negative trends.

- Generates contextual, industry-specific summaries.

- Includes visualizations for deeper data insights.



---



## Why Use It? (Advanced Version) 



- **Improved Decision-Making**:

  Gain actionable insights from customer reviews.

- **Save Time**:

  Process thousands of reviews in seconds.

- **Enhanced Engagement**:

  Identify and address common customer pain points.

- **Easy-to-Use**:

  Both technical and non-technical users can benefit from its user-friendly interfaces.



---



## **How Does It Work? (Advanced Version)**



1. Upload customer feedback data (e.g., CSV file of reviews).

2. The application processes the feedback using:

   - Extractive summarization for the basic version.

   - Advanced LLMs (GPT-3/4) and sentiment analysis for the advanced version.

3. Generates summaries and insights.

4. (Advanced) Provides sentiment distribution and keyword frequency visualizations.



---



## **Key Features (Advanced Version)**



- **Real-Time Summarization**:

  Extracts key points from customer reviews instantly.

- **Sentiment Analysis**:

  Categorizes feedback into positive, neutral, or negative sentiment.

- **Data Visualizations**:

  Pie charts, bar graphs, and word clouds for better insights.

- **Industry-Specific Context**:

  Fine-tuned models for relevant and accurate summaries.

- **Export Capability**:

  Save summaries and sentiment reports to CSV or PDF.



---



## **Folder Structure (Advanced Version)**



```bash

AICustomerFeedbackSummarizer/

├── data/

│   ├── sample_reviews.csv          # Sample customer feedback data

├── gui/

│   ├── __init__.py                 # Initializes the GUI module

│   ├── summarizer_gui.py           # GUI implementation using Tkinter

├── streamlit_app/

│   ├── app.py                      # Streamlit-based advanced feedback summarizer

├── utils/

│   ├── __init__.py                 # Initializes the utils module

│   ├── sentiment_analysis.py       # Sentiment analysis logic

│   ├── summarization_logic.py      # Text summarization logic

│   ├── visualization.py            # Visualization functions (pie charts, bar graphs, word clouds)

│   ├── export_data.py              # Logic to export summaries and reports

├── main.py                         # Entry point to run the summarizer

├── requirements.txt                # Dependencies required for the project

├── README.md                       # Documentation for the project

```



---



## **Installation and Setup (Basic Version)**



### **Step 1: Prerequisites**



- Python 3.8+

- Internet connection for API access (if needed).



---



### **Step 2: Installation**



1. **Clone the Repository**

   ```bash

   git clone https://github.com/thekartikeyamishra/AI-Customer-Feedback-Summarizer.git

   cd AI-Customer-Feedback-Summarizer 

   ```



2. **Set Up Virtual Environment**

   ```bash

   python -m venv .venv

   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

   ```



3. **Install Dependencies**

   ```bash

   pip install -r requirements.txt

   ```



4. **Run the Application**

   ```bash

   python main.py

   ```



---



## **How to Use (Basic Version)**



1. Launch the application by running `main.py`.

2. Upload a CSV file containing customer feedback (e.g., reviews).

3. Click **"Summarize"** to generate summaries of the feedback.

4. View the summarized feedback in the output section.

5. Export the summarized feedback to a CSV file for further use.



---



## **Example Interaction**



**Input CSV**:

```csv

Review

"I love the product. The quality is amazing!"

"The service was terrible. I had to wait for hours."

"The website is user-friendly and easy to navigate."

```



**Summarized Output (Basic)**:

```

- Customers praise the product quality and website usability.

- Complaints about service delays are common.

```



---



## **Dependencies (Basic Version)**



- **pandas**: For data manipulation.

- **nltk**: For text processing and summarization.

- **matplotlib**: For visualizations (advanced version).

- **streamlit**: For the advanced web-based summarizer.



To install all dependencies, run:

```bash

pip install -r requirements.txt

```



---



## **Acknowledgments**



- **OpenAI GPT-3/4**: For advanced contextual summaries (advanced version).

- **Python Libraries**: pandas, nltk, matplotlib, streamlit, and more.

- **Community Feedback**: Inspired by real-world use cases.



---



## **Special Offer**



### **Want more features? Upgrade to the Advanced AI Customer Feedback Summarizer for just INR 299 at https://topmate.io/kartikeyahere/1343010**



### **Use the code "aifeedback" at checkout to get 15% off instantly.**



---



## **Folder Structure (Basic Version)**



```bash

AICustomerFeedbackSummarizer/

├── data/

│   ├── sample_reviews.csv          # Sample customer feedback data

├── gui/

│   ├── __init__.py                 # Initializes the GUI module

│   ├── summarizer_gui.py           # GUI implementation using Tkinter

├── utils/

│   ├── __init__.py                 # Initializes the utils module

│   ├── summarization_logic.py      # Text summarization logic

│   ├── export_data.py              # Logic to export summaries

├── main.py                         # Entry point to run the summarizer

├── requirements.txt                # Dependencies required for the project

├── README.md                       # Documentation for the project

```



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