Data Analyst Professional Practical Exam Submission
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Data Validation and Cleaning
Data Types: Confirmed that all columns are in the correct data types (week: numeric, sales_method: character, customer_id: character, nb_sold: numeric, revenue: numeric, years_as_customer: numeric, nb_site_visits: numeric, state: character). Missing Values: No missing values were identified in the data. Inconsistencies: No inconsistencies were found in the data integrity (e.g., revenue was positive, customer_id seemed unique). Categorical Variables: Values in categorical columns (sales_method, state) were consistent (Email, Call, Email & Call).
Exploratory Data Analysis (EDA)
Univariate Analysis
Customer Distribution: The chart shows that Email reached the most customers (42%), followed by Email & Call (38%), and Call (20%).
Revenue Distribution: The overall revenue distribution is skewed to the right, indicating that a small number of sales generated a significant portion of the revenue. This is further evident when examining the revenue distribution by sales method. The Call method has the highest average revenue per customer, but also the most significant variation, suggesting some calls resulted in very high sales. Email & Call and Email methods have a lower average revenue per customer with less variation.
Time Series Analysis: The line charts for revenue over time by sales method don't reveal any clear trends within the six-week timeframe.
Multivariate Analysis
Customer Characteristics: There seems to be no significant difference in the distribution of years_as_customer and nb_site_visits across the three sales methods. However, the Call method seems to target customers in a wider range of states compared to Email and Email & Call, which seem concentrated in fewer states.
Revenue Correlation: The scatter plots between revenue and other variables (nb_sold, years_as_customer, nb_site_visits) don't show any strong linear correlations.
Metric Calculation and Analysis
Customer Acquisition Cost (CAC): Due to limitations in the data (absence of cost information for each method), CAC could not be directly calculated. However, an estimate could be made based on assumptions about the cost per call and email.
Customer Lifetime Value (CLTV): Similar to CAC, CLTV cannot be accurately estimated without additional data on customer purchase history and behavior.
Return on Investment (ROI): ROI cannot be definitively calculated without CAC. However, we can analyze revenue generated by each method relative to the time investment required. Call requires the most time per customer but also has the highest average revenue per customer. Email requires minimal time but also has the lowest average revenue per customer. Email & Call offers a balance between time investment and revenue generation.
Findings and Recommendations
Email: Reached the most customers but generated the lowest overall revenue. It's a good option for initial outreach due to minimal time investment.
Call: Generated the highest average revenue per customer but reached the fewest customers and required the most time investment. This method might be suitable for high-value products or customer segments where in-depth conversations are necessary.
Email & Call: Achieved a balance between customer reach, revenue generation, and time investment. This method could be a good default strategy for future product launches, especially for products with moderate price points.
Considering the current data, Email & Call seems to be the most balanced and effective strategy for customer acquisition and revenue generation for the new product line. However, the following recommendations are made for future analysis and improvement:
Gather data on cost per call and email: This would allow for a more accurate calculation of CAC and ROI.
Analyze customer lifetime value: By tracking future purchases from these customer groups, we can estimate CLTV and identify which method generates the most valuable customer relationships.
Segment customer analysis: Investigate if specific customer segments respond better to certain sales methods. This could help tailor outreach strategies for future product launches.
Conclusion
This analysis examined the effectiveness of three sales methods for a new product line launched by Pens and Printers. While Email & Call appears to be the most balanced approach based on the current data, further analysis with cost and customer lifetime value data can provide more definitive insights.
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