The Pricing Analysis and Optimization Web-Scraping Tool is designed to help businesses analyze and optimize product pricing using real-time market data and historical sales information. This tool provides insights into real-time market trends, price elasticity, and competitive positioning, enabling dynamic pricing strategies for maximized profitability and also with suggestions of improvemnets.
- Market Price Analysis: Fetches and analyzes real-time product prices from various sources.
- Price Elasticity Calculation: Determines the sensitivity of demand to price changes.
- Dynamic Pricing Recommendations: Provides actionable recommendations for pricing strategies.
- Visualizations: Generates graphical representations of price-demand relationships.
- Sentiment Analysis: Analyzes sentiment in user queries to tailor responses.
Before running the tool, ensure you have the following installed:
- Python 3.7+
- Required Python packages (listed in
requirements.txtor mentioned below)
- Clone the repository:
git clone https://github.com/yourusername/yourrepository.git cd yourrepository
Install dependencies: pip install -r requirements.txt import nltk nltk.download('punkt') nltk.download('vader_lexicon')
- Provide step-by-step instructions on how to set up the project on a local machine.
- Running the Tool:
To start the tool, run:
python main.py
- Analyzing Pricing:
When prompted, enter analyze pricing. Provide the path to your product dataset (in CSV or JSON format). Review the analysis summary and recommendations. Asking Questions:
Enter your question when prompted. The tool will analyze the sentiment and provide a relevant answer based on available data. Exiting the Tool: Type quit to exit the tool. Explain how to use the tool with clear examples of commands and expected inputs/outputs.
The tool works with datasets containing product names and their prices. Here’s an example:
| Product | Price |
|---|---|
| Carrot | 1.8 |
| Potato | 1.2 |
| Tomato | 2.5 |
| Onion | 1.5 |
| Spinach | 3.0 |
Ensure your dataset is formatted similarly to avoid errors during analysis. Provide an example dataset or structure that users should follow
The tool provides several outputs, including:
- Textual Summary: A summary of the pricing analysis, optimization suggestions, and dynamic recommendations.
- Visualizations: Graphs saved as PNG files showing the relationship between price and demand.
This project is licensed under the MIT License. See the LICENSE file for details.
Contributions are welcome! Please fork the repository and submit a pull request. For major changes, please open an issue first to discuss what you would like to change.
Products with Largest Positive Difference (Potentially Underpriced)
| Vegetable | Price | Real-Time Price | Predicted Price | Optimization Suggestion | Price Source |
|---|---|---|---|---|---|
| Potato | 1.2 | 6.866667 | 1.883552 | 0.683552 | Source |
| Carrot | 1.8 | 512.750000 | 2.339826 | 0.539826 | Source |
| Onion | 1.5 | 1.580000 | 1.628432 | 0.128432 | Source |
| Spinach | 3.0 | 9377.600000 | 2.835348 | -0.164652 | Source |
| Tomato | 2.5 | 150.000000 | 1.996394 | -0.503606 | Source |
| Products with Largest Negative Difference (Potentially Overpriced) |
| Vegetable | Price | Real-Time Price | Predicted Price | Optimization Suggestion | Price Source |
|---|---|---|---|---|---|
| Tomato | 2.5 | 150.000000 | 1.996394 | -0.503606 | Source |
| Spinach | 3.0 | 9377.600000 | 2.835348 | -0.164652 | Source |
| Onion | 1.5 | 1.580000 | 1.628432 | 0.128432 | Source |
| Carrot | 1.8 | 512.750000 | 2.339826 | 0.539826 | Source |
| Potato | 1.2 | 6.866667 | 1.883552 | 0.683552 | Source |
- The market appears to be highly price-sensitive. Consider small price adjustments and monitor demand closely.
- On average, your prices are 69450.07% lower than the market. Consider gradual price increases to align with market rates.
- Consider implementing dynamic pricing for high-demand products like Onion.
- Market insight for Spinach: Data Bridge Market Research analyses that the spinach market will project a compound annual growth rate (CAGR) of 6.70% during the forecast period of 2022-2029. The global spinach market overcame the negative effects of the pandemic to grow from $37.7B in 2019 to $39.6B in 2020. The spinach market presents promising opportunities driven by increasing health consciousness, plant-based dietary trends, and the demand for convenient and sustainable food options.
- Market insight for Tomato: The Tomato Market is expected to reach USD 207.17 billion in 2024 and grow at a CAGR of 4.76%. The global tomatoes market was valued at USD 194.52 billion in 2022. The market for organic and locally grown tomatoes has increased as a result of rising consumer demand.
- Market insight for Carrot: The US import of carrots by volume reached 240,927.0 metric tons in 2021. The rising consumption of carrots in the country is expected to boost the market's growth. The market for carrots and turnips is anticipated to register a CAGR of 4.1% during the forecast period of 2022-2027.