Description

At Colcrane, we build predictive Customer Lifetime Value (CLV) models that estimate the future value each customer will generate—based on behavioral signals, timing, and engagement patterns. We define CLV as the net present value of all future variable profits generated by a customer, minus the associated costs (including acquisition), discounted over time to reflect the cost of capital or risk.

Unlike static, backward-looking and oversimplified CLV calculations built on historical averages, our models adapt dynamically to individual behavior over time—capturing customer heterogeneity rather than flattening it.

We focus on predictive statistical models that are explainable, decision-oriented, and purpose-built. Rather than relying on black-box AI, we design models that clients can understand, trust, and act on. For example, our models can reflect a company's actual cost of capital—offering a more financially relevant view of customer value across the full lifecycle.

By segmenting customers based on predicted future value, you gain clarity on which actions drive long-term profitability. With our models you'll understand how seasonality, acquisition quality, and engagement shape your bottom line—enabling sharper strategy, smarter targeting, and sustainable growth.

To maximize profitability, the CLV model must be fully integrated into the organization—driving key business decisions and powering critical use cases. This is where CLV evolves from a static metric into a strategic lens: a dynamic decision support system that improves focus, guides investment, and drives measurable business performance.