Description

Customers don't churn overnight — they move through states: active, drifting, dormant, returning. Customer State Intelligence uses Hidden Markov Models based in machine learning to infer these shifts from behavior and assign probabilities for where each customer is now — and what state they're likely to move into next.

Using your first-party behavioral data, we identify the hidden lifecycle states that sit beneath surface KPIs and quantify transition risk (and opportunity) over time. The output is simple and operational: clear state definitions, state probabilities, and decision-ready rules your CRM team can use for targeting, timing, and escalation. We build the models, wire them into your CRM/CDP, and keep them calibrated over time.

Typical questions it answers:

• Who is quietly drifting — and what's their probability of churn in the next weeks/months?

• Which customers are most likely to reactivate with the right nudge (and which aren't)?

• Where in the lifecycle are we losing value — and what changes move customers forward?

• Which interventions reduce "state decay" without training customers to discounts?