The KPMG Data Analytics Virtual Internship is designed to help gain a practical insight into the work done at KPMG and it is an opportunity to build career skills and experience.
Sprocket Central Pty Ltd, a medium-sized bikes & cycling accessories organization, has approached Tony Smith (Partner) in KPMG’s Lighthouse & Innovation Team. Sprocket Central Pty Ltd is keen to learn more about KPMG’s expertise in its Analytics, Information & Modelling team. Primarily, Sprocket Central Pty Ltd needs help with its customer and transaction data. The organization has a large dataset relating to its customers, but its team is unsure how to effectively analyze it to help optimize its marketing strategy. The project is mainly divided into three tasks:
Assessment of data quality and completeness in preparation for analysis. We start the preliminary data exploration and identify ways to improve the quality of Sprocket Central Pty Ltd’s data. The client provided KPMG with 3 datasets
- Customer Demographic
- Customer Addresses
- Transactions data in the past 3 months
Targeting high-value customers based on customer demographics and attributes. In building this recommendation, we need to start with a PowerPoint presentation that outlines the approach that we will be taking. The client has agreed on a 3-week scope with the following 3 phases as follows -
- Data Exploration
- Model Development
- Interpretation.
Prepared a detailed approach for completing the analysis including activities – i.e. understanding the data distributions, feature engineering, data transformations, modeling, results interpretation, and reporting.
Using visualizations to present insights. Developed a dashboard using Tableau that displays the data summary and results of the analysis. Some of the focused business contexts when presenting findings were:
- What are the trends in the underlying data?
- Which customer segment has the highest customer value?
- What do you propose should be Sprocket Central Pty Ltd’s marketing and growth strategy?
- What additional external datasets may be useful to obtain greater insights into customer preferences and propensity to purchase the products?
