E-Commerce Analysis

This is analysis of a UK-based online retail company. The dataset contained sales transactions for 2010 and 2011.

From the analysis, the store operates in 38 countries. The revenue for the period covered is £9.75M, there was about 5M orders for this period from 4737 customers.

From the visualization, 94% of sales are recorded in the UK, with DOTCOM POSTAGE bringing in the highest number of revenue. The top 3 selling products are Dotcom Postage, Regency and White Hanging Heart.

Further analysis shows that, the highest sales is recorded in November and the lowest sales is recorded in April. The month on month change in sales shows that sales fluctuate every month, with January and April having significant negative change.

The sales by time invoice visual shows that the highest number of sales is recorded at 9:15am and the highest number of returns is also recorded at 9:27am. Sales slows down around 7am and 7pm.

Looking at all the analysis together:

RECOMMENDATIONS

• From the dataset, it seems like when sales peaks, a relatively high number of returns is also recorded. This could be because of errors while handling orders. Management may need to carry out more investigations to pinpoint the exact cause of the returns and work on eliminating it.

• Sales seems to peak toward the end of the year. Management could study the sales pattern at the end of the year to apply findings to the other months to improve sales all year.

• The focus for management should be on the reasons for the returns. In the months of January and April, sales were not very great, but the returns were quite significant. If returns can be reduced to the barest minimum, there will be a significant increase in sales.

• The retail store operates in 38 countries, but most of its customers are in the UK. Management might need to embark on campaigns to increase awareness of its online store in other countries where it operates.

• Since sales traffic is low around 7am and 7pm, management could come up with a marketing strategy that will attract more customers around this time. This could reduce the sales traffic at other times and increase revenue.

The link to the slides I prepared for this analysis is here: https://bit.ly/2XP37CL