Customer Targeting Analysis

Situation

During a simulation at KPMG AU, I was tasked with advising a client on customer targeting, which immersed me in the role of a Data Analyst. This opportunity allowed me to apply my analytical skills in a practical, real-world context.

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Task

The primary responsibilities included:

• Data Quality and Completeness Assessment: Evaluated the datasets to ensure they were complete and reliable for analysis.
• Analysis Targeting High-Value Customers: Conducted in-depth analysis to identify and target high-value customers based on their demographics and attributes.
• Development of Visually Engaging Dashboards: Created dashboards to effectively communicate the findings and insights derived from the analysis.

Action

To address these tasks, the following steps were taken:

• Assessment of Data Quality and Completeness: Scrutinized the data to ensure accuracy and completeness.
• Analysis Targeting High-Value Customers: Analyzed demographic and attribute data to identify high-value customer segments.
• Development of Visually Compelling Dashboards: Designed and developed dashboards to present insights in a clear and engaging manner.

Result

The dashboards delivered key insights that met stakeholder requirements and provided a detailed view of various aspects of customer behavior and product performance:

Dashboard Highlights:

• Product Line Costs: Standard Cost: $7.50M, List Price: $15.63M; Road Cost: $2.64M, List Price: $4.04M; Touring Cost: $0.65M, List Price: $2.00M; Mountain Cost: $0.23M, List Price: $0.27M
• Age and Gender Distribution: Provided a detailed breakdown of male and female counts across various age groups, highlighting demographic trends.
• Online vs. Offline Transactions: Compared the number of transactions conducted online versus offline across different states, revealing customer preferences.
• Transaction Insights by Product Line and Brands: Offered an overview of transactions for different product lines and brands, indicating customer preferences.

Conclusion

The dashboards successfully communicated complex findings in a visually compelling manner, enabling the client to make informed decisions about targeting high-value customers. The analysis provided valuable insights into product costs, demographic distribution, and transaction preferences, enhancing the client's ability to tailor their strategies effectively.