Sports clothing and athleisure attire is a large and growing industry, worth approximately $193 billion in 2021. In this project, we play the role of a product analyst for an online sports clothing company that wants to improve revenue. We will analyze product data such as pricing, reviews, descriptions, and ratings, as well as revenue and website traffic, to provide recommendations for its marketing and sales teams.
The main objectives of this project are:
To analyze pricing data to identify optimal pricing strategies for the company's products. To examine product reviews and ratings data to identify areas of improvement and opportunities for increased revenue. To analyze website traffic and revenue data to identify trends and opportunities for increased revenue. To provide recommendations for the company's marketing and sales teams based on our analysis.
The following tools and technologies were used in this analysis:
- Python 3
- Jupyter Notebook
- Pandas library
- Matplotlib library
- Seaborn library
Our analysis produced the following results:
Optimal pricing strategies for the company's products based on analysis of pricing data. Identified areas of improvement and opportunities for increased revenue based on analysis of product reviews and ratings data. Identified trends and opportunities for increased revenue based on analysis of website traffic and revenue data. Provided recommendations for the company's marketing and sales teams based on our analysis.
Through our analysis of pricing data, product reviews and ratings data, and website traffic and revenue data, we were able to provide recommendations for the company's marketing and sales teams to increase revenue. The recommendations are based on data-driven insights and can be used to optimize the company's pricing strategies, improve product offerings, and target specific customer segments.