Introduction: In this report, I conducted a comprehensive analysis of an online sport retail business using Python and SQLite. The analysis focused on various aspects of the business, including revenue metrics, product performance, customer engagement, pricing strategy, brand analysis, and seasonal trends.
Revenue Metrics: I began by examining the total revenue generated by the company, which amounted to $12,328,902.34. Additionally, I analyzed the average revenue per product, which was approximately $4,531.44. Revenue distribution by brand revealed that Adidas contributed significantly more revenue than Nike, with Adidas accounting for $11,526,619.08 and Nike contributing $802,283.26.
Product Performance Metrics: I investigated several metrics related to product performance. The analysis included product sales count, which totaled 3,179 products, and the average sale price per product, which was $69.72. Moreover, I found that approximately 98.14% of products were on sale, indicating an active pricing strategy. The top-selling products based on sales count and revenue were also identified, providing insights into consumer preferences.
Customer Engagement Metrics: Customer engagement was evaluated through average product rating and the number of product reviews. The average product rating was 3.27, indicating moderate satisfaction among customers. Furthermore, the total number of product reviews amounted to 3,179, indicating active engagement and feedback from customers.
Traffic Trends: Analysis of traffic trends revealed insights into user behavior and website performance. Daily, weekly, and monthly traffic trends were examined, showing fluctuations in website visits over time. The average session duration was calculated to be approximately 6.83 hours, indicating considerable user engagement.
Discount and Pricing Metrics: The effectiveness of discount strategies and pricing elasticity was analyzed. The average discount rate applied was found to be 27.61%, with discounts impacting revenue positively. Pricing strategy effectiveness revealed that 67.92% of products with discounts effectively increased sales, highlighting the efficacy of promotional pricing.
Brand Analysis: Brand loyalty metrics based on customer reviews and repeat purchases were investigated. Adidas demonstrated higher average ratings (3.37) compared to Nike (2.79), indicating stronger brand loyalty among Adidas customers.
Seasonal and Trend Analysis: Finally, I examined revenue and traffic trends during peak seasons such as summer and holidays. Revenue trends during these periods showed fluctuations, reflecting seasonal variations in consumer spending patterns.
Conclusion: In conclusion, the analysis provided valuable insights into the online sport retail business, highlighting key performance indicators, customer engagement metrics, pricing strategies, and brand loyalty. These insights can inform strategic decision-making processes and help optimize business performance in a competitive market landscape.