Notes

Introduction: Good morning everyone.I'm Sushma Kolli, an analyst I will be presenting an analysis for the sales performance for a chain of retail stores over the past few years. Our client, the Chief Financial Officer, has tasked us with identifying ways to maximize profit, whether that means cost savings on shipping or focusing marketing efforts on certain products or locations.

Problem Statement: Our problem is to analyze the returns data and identify the products and regions with high return rates. By understanding the return rates, the chain can take corrective actions to reduce the returns and improve the profitability.
• Returns can significantly impact a retail chain's profitability and reducing them can improve profitability.
• Analyzing returns data can help identify the products and regions with high return rates, leading to corrective actions to reduce returns and improve profitability.

Visualization 1: First, let's look at the return rates by product category. We can see from this bar graph that the category with the highest return rate is Office Supplies, followed by Furniture and Technology. This tells us that we need to investigate why so many customers are returning office supplies and if there is anything we can do to reduce those returns.

Visualization 2: Next, let's explore the return rates by region and product category using a stacked bar chart. This visualization shows that the West region has the highest return rate, especially for office supplies. The East, Central, and South regions also have high return rates for office supplies. This tells us that we may need to adjust our marketing efforts or pricing strategies in these regions to reduce returns.

Visualization 3: Finally, let's look at the return rates by person and region. This bar graph shows the return rates and products for each person, and we can see that Anna Andreadi has the highest return rate, especially for office supplies. This shows to work with Anna to identify the reasons for her returns and offer solutions to reduce them.

Conclusion: In conclusion, our analysis has identified the categories, regions, and people with the highest return rates. The retail chain has a high return rate for certain product categories such as office supplies which is approximately 100% more than the other categories. It needs to be investigated the reasons behind these returns and take corrective actions to reduce them, which will ultimately improve profitability.
By focusing on reducing returns in these areas, we can improve profitability for the retail chain. Thank you for your attention.