This project aims to analyze the e-commerce market in Brazil using the Olist dataset. The goal is to uncover valuable insights and trends within the data to support strategic decision-making.
The Olist dataset presents an opportunity to understand and analyze the e-commerce market in Brazil, aiming to uncover key insights and trends within the data. The primary objective was to gain actionable insights that could aid in strategic decision-making for Olist, identifying areas for improvement and potential growth opportunities.
The project began with data exploration, cleaning, and preprocessing to ensure data integrity. Exploratory Data Analysis (EDA) techniques were employed to uncover patterns, trends, and correlations within the dataset. Various visualization methods were used to illustrate these findings effectively. Additionally, machine learning models were applied to predict certain aspects or behaviors based on historical data.
- Geographic regions such as São Paulo and Rio de Janeiro showed higher sales volumes compared to other areas, indicating potential areas for targeted marketing or expansion.
- Product categories like electronics and home appliances were among the most purchased, signaling opportunities for inventory optimization or marketing focus.
- There were instances of delays in deliveries, which might be impacting customer satisfaction and retention rates. Investigating and improving logistics could be beneficial.
- Seasonal trends and peak purchase times were identified, offering insights for promotional strategies and resource allocation during high-demand periods.
- Implement targeted marketing strategies in high-performing regions to further capitalize on strong sales.
- Optimize inventory and logistics processes to minimize delivery delays, enhancing customer satisfaction.
- Develop personalized promotions or campaigns aligned with identified seasonal trends to boost sales during peak periods.
- Consider leveraging machine learning models for better demand forecasting and personalized customer experiences.
You can find the Tableau dashboard in this link: https://public.tableau.com/views/OlistProject_16964294509640/OlistDashboards?:language=en-US&:display_count=n&:origin=viz_share_link