TATA DATA VISUALIZATION JOB SIMULATION: Empowering Business with Effective insights

Background Information

An online retail store has hired you as 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 analyze 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. They would also like to view different metrics based on the demographic information that is available in the data.

Business Questions — Data Metrics

In this section, Data Exploration was performed on the business dataset to provide relevant business questions to the CEO and CMO for better data-driven business decision making.

CEO Questions:

- Which region has the highest revenue and which region has the lowest revenue?

- Who are the top customers and how much do they contribute to the total revenue?

- Which months generated the most revenue?

CMO Questions:

- What is the percentage of customers who are repeating orders?

- What is the revenue of customers with multiple orders?

- Which region has the highest number of customers with multiple orders? How much are they contributing to revenue?

Data Cleaning

• Which store has the highest revenue and which store has the lowest revenue?

In this section, the dataset was cleaned for better analysis and visualization in other to provide effective data insights.

· Create a check that the Quantity field should not be below 1 unit

· Create a check that the Unit Price field should not be below $0

Data Transformation

Create a Revenue calculated field: multiple each quantity sold by its unit price.

Data Analysis and Visualization

• Revenue by Month

Key insight: 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 years. This analysis shows that the retail store sales are impacted by the seasonality which usually occurs in the last 4 months of the
year.

• Top 10 Countries by Revenue and Quantity Sold per Month

Key insight: This data does not include the UK as the country already has a very high demand. The analysis shows that countries such as the Netherlands, Ireland, Germany and France have high quantity sold and revenue generated.

• Top 10 Customers by Revenue

Key insight: 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 1.34% more than the 2nd highest which shows that the business is not relying only on a few customers to generate the revenue.

Dashboard

During this task, created a dashboard using Tableau to communicate and convey key findings from the analysis to the stakeholders of the organizations.

Tableau link: https://public.tableau.com/app/profile/oyedele.samuel/viz/OnlineRetailStoreData/Dashboard1

Data Insights:

1. They are total of 4,372 distinct customers.

2. United Kingdom has the most customers and generated the highest revenue among all regions. Over 87.04% of the overall revenue generated.

3. South Africa is the region with the lowest revenue with only one customer.

4. November is the month with the highest revenue. There is a high increase in revenue from September to November.

5. Netherland has the customer with the highest generated revenue.

6. They are 98.99% of customer multiple orders compare to 1.01% of single order. This shows customers are satisfied with the products.

Recommendations:

1. They should be a new marketing strategy focusing on region with the lowest revenues such as South Africa, Brazil, and UAE etc. to help boost sales revenues and profitability.

2. The company should invest more in regions with the high volume of quantity sold and revenues generated such as Netherlands, Ireland, Germany and France etc. to increase demand for products.

Conclusion

This virtual internship program was a challenging and great one for me. I was able to work as a Data Analyst consultant to provide effective data insights through data visualizations to the stakeholders of the business on their retail store sales data in other to make a data-driven informed decision making. It also help sharpening my data analysis and visualization skills including communication and presentation skills.

I am looking forward to work more on real-world projects to continuing learning and growing my data analysis skills and career.

Special thanks to Tata Group Consultancy Services and Forage for this opportunity.

You can check out other projects on my Github repository and portfolio website

Here is the link for anyone interested in the virtual internship: Tata Data Visualization

Thank you for taking your time to read it, kindly comment your suggestion on this project. I will also appreciate a like/follow from you.