Data-driven insights from Brazilian e-commerce transactions
View Full Analysis on GitHubThis analysis explores an e-commerce dataset from Brazil, containing information about orders, customers, payments, and deliveries. The goal is to derive actionable insights to improve business operations and customer experience.
Time Range: September 4, 2016 to October 17, 2018 (772 days)
Data Source: Brazilian E-commerce Public Dataset by Olist
Analysis Tools: SQL for querying, JavaScript/HTML for visualization
Understanding where customers are located helps in optimizing logistics and marketing strategies.
Key Insight: Brazilian customers mostly place their orders in the afternoon (1 PM - 6 PM), followed by night and morning times.
Analyzing how order patterns change over time helps in inventory planning and marketing campaigns.
Significant growth in cost of orders from 2017 to 2018 for the first eight months of each year.
No strong monthly seasonality observed, but slight uptrend in orders during mid-months (May-August) and downtrend toward year-end.
Analyzing delivery times helps identify operational efficiencies and customer satisfaction opportunities.
Key Insight: São Paulo (SP) has the fastest average delivery time at 8.3 days, while Roraima (RR) has the slowest at 29 days.
Understanding payment preferences helps optimize checkout processes and financial operations.
Key Insight: The majority of orders (52,546) are paid in a single installment, with installment payments decreasing as the number of installments increases.
Shipping costs significantly impact profitability and customer satisfaction.
| State | Avg. Freight |
|---|---|
| Tocantins (TO) | R$ 333.17 |
| Sergipe (SE) | R$ 270.01 |
| Roraima (RR) | R$ 227.36 |
| Paraná (PR) | R$ 225.18 |
| Rio Grande do Sul (RS) | R$ 213.73 |
| State | Avg. Freight |
|---|---|
| Mato Grosso (MT) | R$ 57.17 |
| Acre (AC) | R$ 94.37 |
| Minas Gerais (MG) | R$ 120.66 |
| Amazonas (AM) | R$ 125.13 |
| Goiás (GO) | R$ 130.56 |