TATA-Data-Visualization: Empowering business with effective insights.
INTRODUCTION: An online retail store has hired a consultant to review their data and provide insights that would be valuable to the CEO and CMO of the business. The business has been performing well and the management wants to analyse what the major contributing factors are to the revenue so they can strategically plan for next year. The leadership is interested in viewing the metrics from both an operations and marketing perspective. Management also intends to expand the business and is interested in seeking guidance into areas that are performing well so they can keep a clear focus on what’s working. They would also like to view different metrics based on the demographic information that is available in the data.
DATA PREPARATION: Before beginning the analysis, we must make sure that the data is cleaned properly. The data contains some returns to the store which are provided in negative quantities and there are unit prices which were input in error. Following steps are to be performed to clean this data. Step 1: Create a check that the quantity should not be below 1 unit Step 2: Create a check that the Unit price should not be below $0 In order to apply the checks that have been mentioned above, we would need to use conditional formulas where the logic would state that if the conditions are met then the tool should exclude the data from analysis.Once this is done, the data will be good to be used for further analysis.
INSIGHTS:
We have to assure that data provided the most up to date and error free analysis. After I loaded the data into my software, I scrubbed any records that have negative quantities and unit price, as these records needed to be removed in order to provide helpful analysis. As for your first question, the CEO has requested a trend of the revenue to see if there is any seasonality in the store sales. My analysis shows that there are some months of the year where exceptional growth is witnessed. The data shows that the revenue in the first 8 months is fairly constant as the average revenue generated for these 8 months is around $685k. The increase in revenue starts in the month of September, where the revenue increases by 40% over the previous month. This trend continues till the month of November where it reached 1.5 million USD, the highest during the entire year. The data is incomplete for the month of December, therefore, no conclusion can be drawn from it, unfortunately. This analysis shows that the retail store sales are impacted by the seasonality which usually occurs in the last 4 months of the year. The second visual shows how the top 10 countries which have opportunities for growth are performing. This data does not include the UK as the country already has high demand and I’ve been told you’re more focused on the countries where demand can be increased. The analysis shows that countries such as the Netherlands, Ireland, Germany and France have high volumes of units bought and revenue generated. I would suggest that these countries should be focused on to ensure that measures are taken to capture these markets even more. The third analysis has been performed on the top 10 customers who have purchased the most from the store. The data shows that there is not much of a difference between the purchases made by the top 10 customers. The highest revenue generating customer only purchased 17% more than the 2nd highest which shows that the business is not relying only on a few customers to generate the revenue. This shows that the bargaining power of customers is low and the business is in a good position. Finally, the map chart shows the regions that have generated the most revenue compared with the regions that have not. It can be seen that apart from the UK, countries such as Netherlands, Ireland, Germany, France and Australia are generating high revenue and the company should invest more in these areas to increase demand for products. The map also shows that most of the sales are only in the European region with very few in the American region. Africa and Asia do not have any demand for the products, along with Russia. A new strategy targeting these areas has the potential to boost sales revenues and profitability.