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https://github.com/thekartikeyamishra/aipoweredmarketingassistant

AI-Powered Marketing Assistant, an advanced tool designed to enhance your digital marketing campaigns using the power of machine learning (ML) and large language models (LLMs). This project empowers small businesses and MSMEs to create compelling content, analyze campaigns, and strategize effectively.
https://github.com/thekartikeyamishra/aipoweredmarketingassistant

artificial-intelligence llm matplotlib numpy openai pandas python scikit-learn streamlit

Last synced: 1 day ago
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Host: GitHub
URL: https://github.com/thekartikeyamishra/aipoweredmarketingassistant
Owner: thekartikeyamishra
Created: 2024-12-24T14:25:50.000Z (3 days ago)
Default Branch: main
Last Pushed: 2024-12-24T14:31:10.000Z (3 days ago)
Last Synced: 2024-12-24T15:36:43.221Z (3 days ago)
Topics: artificial-intelligence, llm, matplotlib, numpy, openai, pandas, python, scikit-learn, streamlit
Language: Python
Homepage:
Size: 9.77 KB
Stars: 0
Watchers: 2
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

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README

# AIPoweredMarketingAssistant
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!

---

## **Features of the Advanced Version**

### **1. Content Generation**
- Generate **social media captions**, **blog posts**, and **email marketing content** using LLMs (e.g., OpenAI's GPT).

### **2. Campaign Analytics**
- Analyze campaign performance metrics like **CTR**, **impressions**, and **engagement rates**.

### **3. Audience Segmentation**
- Segment audiences based on **engagement** and **demographic data** using clustering algorithms.

### **4. Custom Strategy Recommendations**
- Use LLMs to provide actionable insights and strategies to improve marketing campaigns.

### **5. Interactive Dashboard**
- Built with **Streamlit**, allowing users to:
- Input campaign data.
- Generate marketing content.
- Visualize campaign analytics.

---

## **File and Folder Structure**

```bash
AIPoweredMarketingAssistant/
├── data/
│ ├── campaign_data.csv # Sample campaign performance data
│ ├── audience_data.csv # Sample audience demographic data
├── output/
│ ├── generated_content/ # Folder for saving generated marketing content
│ ├── analytics_reports/ # Folder for saving campaign analytics reports
├── streamlit_dashboard/
│ ├── app.py # Streamlit dashboard for marketing assistant
├── utils/
│ ├── __init__.py # Initializes the utils module
│ ├── content_generation.py # Logic for generating marketing content using LLMs
│ ├── campaign_analysis.py # Analyzes campaign performance data
│ ├── audience_segmentation.py # Segments audience for targeting
│ ├── visualization.py # Generates visualizations for analytics
│ ├── strategy_recommendation.py # Generates marketing strategies using LLMs
├── requirements.txt # Dependencies required for the project
├── README.md # Documentation for the project
```

---

## How It Works

### **1. Content Generation**
Generate marketing content by entering a prompt and selecting the content type (e.g., social media, blog, email).

### **2. Campaign Analytics**
Upload campaign performance data to calculate metrics like:
- Average CTR.
- Impressions.
- Engagement rates.

### **3. Audience Segmentation**
Upload audience demographic data to segment audiences using clustering techniques.

### **4. Strategy Recommendations**
Provide campaign performance metrics to generate actionable insights for improving results.

### **5. Interactive Dashboard**
All features are accessible through a user-friendly **Streamlit interface**.

---

## **Installation and Execution**

### **1. Clone the Repository**
```bash
git clone https://github.com/thekartikeyamishra/AIPoweredMarketingAssistant.git
cd AIPoweredMarketingAssistant
```

### **2. Set Up a 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 Dashboard**
```bash
streamlit run streamlit_dashboard/app.py
```

## **Dependencies**

Install the required libraries with:
```bash
pip install -r requirements.txt
```

Dependencies include:
- `pandas`
- `numpy`
- `scikit-learn`
- `matplotlib`
- `streamlit`
- `openai`

---

## **Future Enhancements**
- Add support for social media platform integrations (e.g., Facebook Ads, Google Analytics).
- Include advanced ML models for enhanced audience segmentation.
- Provide downloadable campaign insights in PDF/Excel formats.

---

## **Contributions**
Contributions are welcome! Fork the repository, submit pull requests, or raise issues to improve this project.

---

## **Support**
If you find this project helpful, please ⭐ the repository on GitHub.
Your feedback is invaluable in making this tool better!

[Star the Repository](https://github.com/thekartikeyamishra/AIPoweredMarketingAssistant)

Let’s revolutionize digital marketing together! 🚀