Brand Recall and customer loyalty metrics

The dataset data_loyalty is designed to simulate key metrics associated with brand loyalty and customer retention. It consists of four primary variables, each representing a different aspect of customer engagement and loyalty:
Brand Recall: This variable measures the ability of consumers to remember a brand when prompted. It is generated using a normal distribution with a mean of 50 and a standard deviation of 15, indicating that most values will cluster around the average, with some variability reflecting differences in consumer memory.
Customer Retention Rate (CRR): This metric quantifies the percentage of customers who continue to engage with the brand over time. It is also simulated using a normal distribution, with a mean of 65 and a standard deviation of 10. This suggests that while many customers remain loyal, there is variability in retention rates across the sample.
Net Promoter Score (NPS): The NPS is a widely used metric that gauges customer loyalty based on their likelihood to recommend the brand to others. In this dataset, NPS values are generated as random integers ranging from 1 to 10, providing a straightforward measure of customer sentiment.
Customer Lifetime Value (CLV): This variable estimates the total revenue that a business can expect from a single customer account throughout their relationship. It is simulated using a normal distribution with a mean of $20,000 and a standard deviation of $5,000, reflecting the potential variability in customer value.
The dataset comprises 100 observations for each variable, providing a robust foundation for analysis.