Sauti East Africa request for a segmentation analysis on all of their user's behavior. Sauti wishes to better optimize their menu design and explore the feasibility of smart menus based on user predicted behavior.
# **Market Segmentation Clustering Analysis**
A non-profit social enterprise is focused on improving the livelihoods of traders and farmers, and particularly women, in East Africa. They provide them with realtime market data through access to online digital resources. They collect demographic data on these traders solutions and develop visuals for researchers.
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## π **Table of Contents**
- π **Project Description**
- π **Requirements**
- βοΈ **Installation**
- **Procedure**
- **Project Structure**
- **Results**
- π **License**
- π©βπ» **Acknowledgements**
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# π **Project Description**
This project performs limited aggregate analysis of all their user's behavior - on a project evaluation basis. Better understanding our user's interactions will allow for better optimization of their menu design and explore the feasibility of smart menus based on user predicted behavior.
## **Cluster Segmentation Model**
The setup and structure of the clustering segmentation model was used in this project to identify distinct user segments based on demographic data and interaction behavior sourced from the non-profit platform. They offer a range of information services to users in Kenya, Uganda, Rwanda, and Tanzania via a cellular network. Users access these services by dialing a shortcode and navigating through numbered menus. The platform, available in multiple languages, updates hourly with current information covering:
- Market Prices
- Virtual Marketplace
- Currency Exchange Rates
- Weather Forecasts
- Trade and Tax Information
- Financial Management Services
- Agricultural Services
- Business Operations Information
- Legal and Anti-Corruption Information
- COVID-19 Updates
- Health Information
- Corruption Reporting
This project's goal is to bridge information gaps for micro, small, and medium enterprises (MSMEs), enhancing access to timely information. A clustering segmentation model can allow teams to better understand their diverse user base and tailoring services t β¦