Amazon Data Analysis for Sales Growth
The objective of this project is to analyze Amazon's sales, customer, and product data to gain insights into the current state through visualization and identify opportunities for revenue improvement. By examining Amazon's sales trends, customer behavior, and product performance, the aim is to develop effective business strategies. The expected outcomes include increased sales and enhanced operational efficiency
Tool
| Category | Description |
| Language | Python, SQL |
| Library | Pandas, Matplotpy, Seaborn, Numpy |
| Visual Tool | Tableau, Python, Canva, PPT |
Dashboard
Project PPT result
Data information
Upon initially reviewing the data based on the earliest dates, we discovered a gap from mid-March 2018 to early January 2019. Additionally, for weekday data, Thursdays showed zero sales, similar to Wednesdays, making it challenging to use this data in the analysis. Therefore, we decided to focus on the 2019 data to predict sales trends for 2020. Subsequently, we performed several preprocessing steps, including date format conversion, removal of missing values, column elimination, and rounding of amount columns
Data Analysis
- Top Sales by Product:
- Canned shrimp and dried mushrooms recorded the highest sales, accounting for 16% of total sales.
- Sales by Day of the Week:
- Weekend sales were significantly higher, with over 50% of total sales occurring on weekends, excluding the sparse data on Wednesdays and the lack of data on Thursdays.
- Customer Analysis:
- The top 20% of customers accounted for 87% of total sales.
- These top customers showed a pattern of bulk purchasing.
- Top Revenue Products and Customers:
- Over 90% of sales for the top 3 products were made by the top 20% group of customers (A, B, C).
- Canned shrimp and dried mushrooms, which account for over 16% of total sales, are included in this group, indicating Amazon's high dependency on specific customers, likely supplying ingredients to businesses.
- Products with Declining Margins:
- The bottom 20 products resulted in a deficit of approximately $62,500.
- The fondue mix, in particular, showed abnormally low margins and requires review.
- Market and Order Growth Trends:
- The growth rates for the market and orders in 2019 showed a declining trend over time, indicating stagnation.
- Sales and Margins by Category:
- Higher sales correlated with higher margins, showing a normal pattern.
Dashboard [Tableau]
We utilized Tableau to build a data visualization dashboard based on the above analysis.
- Main Page:
- Displays overall sales metrics for 2019, including total sales and margins, focusing on the overall trends.
- Includes market growth rate and daily sales data for 2019 for easy viewing.
- Visualized monthly sales data with graphs and trend lines to illustrate sales, costs, and margins.
- Product Page:
- Shows monthly sales status by category and product.
- Central graph displays the top 10 and bottom 10 products by margin.
- Below the central graph, it summarizes the 2019 sales trends, total sales, and margins by category.
- The right section includes sales metrics for the top 3 products.
- The red graph on the top left indicates products with negative margins, highlighting loss-making items.
- Allows differentiation between the top 20% of customers and all customers for a clearer analysis.
- Customer and Monthly Settings:
- Allows settings for monthly and overall customer data, as well as for the top 20% of customers.
- Enables users to easily view key metrics and identify patterns.
Conclusion
- Sales Trend Analysis:
- Over 50% of total sales occur on weekends.
- It suggests that buyers tend to shop on weekends, indicating that focused marketing campaigns and promotions during weekends could be effective.
- Customer Analysis:
- The top 20% of customers account for the majority of total sales.
- These customers are crucial to the business and the sales dependency on them is high.
- Therefore, targeted marketing for this segment is essential.
- Product Analysis:
- Identified products that result in a loss when sold.
- Negative margin products and unpopular items need to be reviewed and potentially eliminated.
- The strategy should focus on high-profit products.
- Business Strategy Development:
- Sales Trend Strategy:
- Implement weekend special discount events and flash sales to boost weekend sales.
- Increase weekend advertising budget to attract potential customers and maximize shopping traffic.
- Customer Strategy:
- Introduce a VIP membership with special benefits and personalized marketing for top customers.
- Analyze key customer behavior to encourage repeat purchases.
- Regularly conduct satisfaction surveys and incorporate feedback.
- Product Strategy:
- Thoroughly review and eliminate low-margin products from inventory.
- Reassess discount strategies and pricing policies to increase sales while maintaining margins.
- Sales Trend Strategy:
PPT Feedback Summary
- Overall Evaluation:
- Worked diligently under limited conditions.
- The PPT was concise, visually appealing, and easy to understand.
- The use of numbers strengthened the logic.
- The conclusion was well-compressed and presented.
- Key Content:
- Theme: The Tableau title focused on the key concepts of revenue growth and operational efficiency.
- Objective: To assess profitability and current status.
- Data Preprocessing:
- The handling of missing values and the analysis of weekdays in relation to sales were well-aligned with the goals.
- There was an explanation of preprocessing by category, but additional details on how the categorization was done would be beneficial.
- PPT and Dashboard:
- It would be helpful to mention how the overall trends relate to revenue growth.
- The dashboard charts were too dense.
- The market flow was impressive but it was difficult to understand the supporting logic.
- Some axes were hard to see.
- Synchronizing the axes to extend equally on both sides would be better.
- Storytelling:
- It would be beneficial to develop a storytelling approach that connects operational efficiency and revenue growth.