KPMG_Virtual_Internship

• Data quality assessment, Data insights, RFM- Segmentation, Model Development and Representation.

Task 1

• Evaluating Data Quality
• Evaluating the quality and completeness of data before it's analyzed
• Sprocket Central Pty Ltd is a medium-sized company specializing in bikes and cycling accessories.

Mainly, Sprocket Central Pty Ltd requires assistance with its customer and transaction data. The company possesses a significant amount of data about its customers, but its team is uncertain about how to efficiently analyze it to enhance its marketing approach.

Nonetheless, to aid in the analysis, you consult with the Associate Director for suggestions, and she recommends, “the significance of enhancing the quality of customer data cannot be overstated. The higher the quality of the data, the greater the opportunity to leverage it for the company's expansion.”

The client has supplied KPMG with three datasets:

• Information about the customer's demographics
• Addresses of customers
• Transaction data from the last three months

You plan to begin the initial exploration of the data to find ways to improve the quality of Sprocket Central Pty Ltd's data.

Write an email to the client outlining the issues with the data's quality and strategies to address these issues. Use the 'Data Quality Framework Table' and resources provided below to determine the criteria and dimensions to consider.

Task 2

• Data Insights
• Selecting high-value customers based on customer characteristics and traits. For background, Sprocket Central Pty Ltd is a well-established client of KPMG, specializing in top-notch bicycles and cycling accessories for riders. Their marketing team aims to enhance their business by examining their current customer database to uncover trends and behaviors. Utilizing the three existing datasets (Customer demographics, customer addresses, and transactions) as labeled datasets, kindly suggest which of the 1000 new customers should be prioritized to maximize value for the company.

To develop this recommendation, we must begin with a PowerPoint presentation that details the strategy we plan to employ. The client has agreed on a three-week project with three phases: Data Exploration, Model Development, and Interpretation.

Please outline a comprehensive plan for the analysis, including tasks such as understanding data distributions, feature engineering, data transformations, modeling, interpreting results, and reporting. This detailed plan must be shared with the client for approval. Could you advise on the necessary steps to take?

Ensure your PowerPoint presentation includes a thorough strategy for each phase of the approach, including the activities involved - understanding data distributions, feature engineering, data transformations, modeling, results interpretation, and reporting. This detailed plan should be presented to the client for their approval.

Task 3

• Data Insights and Presentation
• Utilizing visual aids to convey insights Please create a dashboard that can be showcased to the client at our upcoming meeting. This dashboard should display a summary of the data and the analysis's results. It's crucial to consider the business context when sharing your insights:

What are the patterns in the underlying data? Which customer segment offers the highest value? What recommendations do you have for Sprocket Central Pty Ltd’s marketing and expansion strategy? What additional external datasets could provide further understanding of customer preferences and their likelihood to purchase products? Specifically, your presentation should identify who Sprocket Central Pty Ltd’s marketing team should focus on from the new list of 1000 customers, as well as the broader market segment to engage with.

The client has supplied KPMG with three datasets:

Customer Demographics Customer Addresses Transactions data from the last three months. You will initiate the preliminary data exploration to identify strategies for enhancing the quality of Sprocket Central Pty Ltd’s data.

Draft an email to the client outlining the issues with data quality and strategies to address these issues. Refer to the ‘Data Quality Framework Table’ and resources provided for the criteria and dimensions to consider.