KPMG AU- DATA ANALYTICS JOB SIMULATION ON FORAGE

• Data Quality Assessment

Sprocket Central Pty Ltd, a medium size 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. Smith discusses KPMG’s expertise and speaks about how the team can effectively analyze the datasets to help Sprocket Central Pty Ltd grow its business. Primarily, Sprocket Central Pty Ltd needs help with its customer and transactions data. The organization has a large dataset relating to its customers, but their team is unsure how to effectively analyse it to help optimize its marketing strategy. However, in order to support the analysis, you speak to the Associate Director for some ideas and she advised that “the importance of optimizing the quality of customer datasets cannot be underestimated. The better the quality of the dataset, the better chance you will be able to use it drive company growth.”

The client provided KPMG with 3 datasets:

- Customer Demographic

- Customer Addresses

- Transactions data in the past 3 months

You decide to start the preliminary data exploration and identify ways to improve the quality of Sprocket Central Pty Ltd’s data.

Draft an email to the client identifying the data quality issues and strategies to mitigate these issues. (Please see attached file.)

• Data Insights

Sprocket Central Pty Ltd has given us a new list of 1000 potential customers with their demographics and attributes. However, these customers do not have prior transaction history with the organization.

The marketing team at Sprocket Central Pty Ltd is sure that, if correctly analyzed, the data would reveal useful customer insights which could help optimize resource allocation for targeted marketing. Hence, improve performance by focusing on high value customers. 

Their marketing team is looking to boost business by analyzing their existing customer dataset to determine customer trends and behaviour.

Using the existing 3 datasets (Customer demographic, customer address and transactions) as a labelled dataset, please recommend which of these 1000 new customers should be targeted to drive the most value for the organization. In building this recommendation, we need to start with a PowerPoint presentation which outlines the approach which we will be taking. The client has agreed on a 3 week scope with the following 3 phases as follows - Data Exploration; Model Development and Interpretation. Prepare a detailed approach for completing the analysis including activities – i.e. understanding the data distributions, feature engineering, data transformations, modelling, results interpretation and reporting. This detailed plan needs to be presented to the client to get a sign-off. Please advise what steps you would take.

Please see below presentation:

• Data Insights and Presentation

After building the model we need to present our results back to the client. Visualizations such as interactive dashboards often help us highlight key findings and convey our ideas in a more succinct manner. A list of customers or algorithm won’t cut it with the client, we need to support our results with the use of visualizations.

Please develop a dashboard that we can present to the client at our next meeting. Display your data summary and results of the analysis in a dashboard.  Maximum of 3 dashboard views/tabs, creativity in layout and presentation is welcome.  

In the simulation I:

- Completed a simulation focused on advising a client on customer targeting with the Data, Analytics & Modelling team
- Assessed data quality and completeness in preparation for analysis
- Analyzed data to target high-value customers using RFM Analysis based on demographics and attributes
- Developed dashboards using Power BI to communicate findings with visuals