Answer-first summary for fast verification
Answer: Apply clustering algorithms to segment customers based on their purchase behavior, which can uncover hidden patterns and groups within the data for targeted marketing.
Option C is the most comprehensive and scalable approach for exploratory analytics in this scenario. Clustering algorithms can efficiently segment customers into groups with similar purchase behaviors, which is invaluable for developing targeted marketing strategies and personalized offers. While options A and B provide useful insights into specific aspects of the data, they do not offer the holistic view needed for strategic decision-making. Option D, while useful for forecasting, does not directly address the need for customer segmentation and pattern identification in the current context.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
As a Microsoft Fabric Analytics Engineer Associate, you are tasked with analyzing a dataset containing customer purchase history to identify patterns and trends that could inform strategic business decisions. The dataset includes variables such as customer age, purchase amount, purchase frequency, and timestamps of purchases. Your goal is to perform exploratory analytics that not only identifies central tendencies and relationships but also segments customers into meaningful groups for targeted marketing strategies. Considering the need for scalability and the potential for real-time analytics, which of the following approaches would be the BEST to achieve this objective? (Choose one option.)
A
Calculate the mean and median of the purchase amounts to determine the central tendency, as this provides a quick overview of the dataset's distribution.
B
Use scatter plots to visualize the relationship between customer age and purchase frequency, enabling the identification of any correlations between these variables.
C
Apply clustering algorithms to segment customers based on their purchase behavior, which can uncover hidden patterns and groups within the data for targeted marketing.
D
Perform a time series analysis to forecast future sales based on historical data, helping in inventory and resource planning.
No comments yet.