Customer Lifetime Value (CLV) represents the total revenue or profit a business expects to earn from a customer over the entire duration of their relationship. It helps businesses understand how valuable different customers are and how much they can afford to spend on acquisition and retention.

At a basic level, CLV can be calculated as:
Average Revenue per Customer × Average Customer Lifespan

More advanced CLV models incorporate:

• Purchase frequency

• Gross margin

• Discount rates

• Retention probabilities

• Cohort behavior

CLV is critical for:

• Marketing budget decisions

• Pricing strategies

• Customer segmentation

• Retention programs

• Forecasting revenue

For example, if a customer’s CLV is $1,200, spending $200 to acquire them may make sense. Without CLV, acquisition spend decisions are guesswork.

In BI systems, CLV is often modeled using cohort data and rolling time windows. Predictive CLV models use machine learning to estimate future behavior based on historical patterns.

Challenges with CLV include:

• Data sparsity for new customers

• Changing behavior over time

• Channel attribution complexity

• Over-simplified assumptions

Because of this, CLV should be treated as a directional metric rather than an exact number.

CLV shifts business thinking from short-term transactions to long-term relationships, making it foundational for sustainable growth strategies.