aterhim / codanalyzer

Simple Africa COD Market Analysis Dashboard

Africa COD Market Analysis Dashboard

Solution Name: CODAnalyzer

CODAnalyzer is a simple Streamlit app designed to empower e-commerce strategists in selecting the ideal African market for Cash On Delivery (COD) strategies. By leveraging specific country-level data, users can explore and analyze various metrics to identify markets with the most significant potential for COD implementation.

Note: The app provides initial features to analyze about the african countries that influences the choice of the suitable target market for COD.

Key Features:

• Dynamic Metric Selection: Choose from a range of economic and demographic metrics to focus your analysis such as:

  • Population: A larger population offers a broader customer base for e-commerce businesses. High population areas, especially urban centers, often have better logistics and delivery infrastructure, making COD more feasible and efficient.
  • Average Age: The average age can signal the potential market segment for e-commerce. Younger populations might be more tech-savvy and open to online shopping, while the preferences of older demographics could influence the type of products sold and the COD services offered.
  • GDP per Capita (in $): it's a measure of a country's economic strength and individual purchasing power. Higher GDP per capita suggests more disposable income and potentially greater demand for e-commerce, making COD a viable payment option.
  • Merchant Marine: A strong merchant marine can enhance a country's logistics and shipping capabilities, crucial for e-commerce. Efficient shipping networks can lower delivery costs and times, benefiting COD operations by making them more reliable and appealing to customers.
  • Internet Users (%): This metric helps gauge the digital penetration of a country. Higher internet penetration rates can lead to increased e-commerce activity, creating a conducive environment for COD by ensuring a wider reach of potential online shoppers.
  • Unemployment Rate (%): The unemployment rate can influence consumer spending behavior. Higher unemployment may reduce disposable income and affect e-commerce growth negatively. However, understanding this metric helps tailor COD services to match the economic conditions and consumer capability to pay upon delivery.

• Interactive Sliders: Adjust criteria thresholds to filter countries based on selected metrics.

• Comprehensive Visualization: View a multi-bar plot displaying selected metrics for each country, enabling easy comparison and decision-making.

• Data-Driven Insights: Utilize cached, up-to-date data for speedy and informed market analysis.

Getting Started

To run CODAnalyzer on your local machine, follow these steps:

1. Clone the Repository

   git clone https://github.com/AterhiM/CODAnalyzer.git
   cd CODAnalyzer
   

2. Set Up Your Environment

   Ensure you have Python 3.6+ installed on your system. It's recommended to use a virtual environment:

   python -m venv venv
   source venv/bin/activate # On Windows, use `venv\Scripts\activate`
   

3. Install Requirements

   Install the required Python packages using the requirements.txt file:

   pip install -r requirements.txt
   

4. Run the App

   Launch CODAnalyzer by running:

   streamlit run ./code/app.py
   

5. Explore the Dashboard

   Use the sidebar to select metrics and set your criteria. The dashboard will dynamically update to show you the filtered countries and plot their metrics for easy comparison.

Data Source

The app uses a dataset containing various economic and demographic metrics for African countries from multiple sources ( statista.com and cia.gov).

Contributing

We welcome contributions and suggestions to make CODAnalyzer more useful for e-commerce strategists. Feel free to fork the repository, make your changes, and submit a pull request.

License

See the LICENSE file for details.

Cheers! made by @therealaterhi