Applied Behavioral Intelligence

 

We turn academic research into predictive behavioral intelligence—revealing, forecasting, and shaping the customer behaviors that drive long-term value. Grounded in first-party data and guided by the Pareto principle, we start with the decision, identify the signals that matter, and turn insight into action.

Customer Base Audit

A research-based diagnostic (descriptive or predictive) that maps how customer value is created, sustained, and lost—so you can focus retention, acquisition, and investment where it matters most.

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Predictive CLV Modeling

Explainable, research-driven CLV models that forecast future customer value accurately at the individual level, so you can allocate budgets, set targeting rules, and grow profitably with confidence.

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Customer State Intelligence

A dynamic probabilistic lifecycle model that detects state shifts (active → drifting → dormant) and predicts what's next—so your CRM team can intervene earlier, choose the right action, and avoid one-size-fits-all journeys.

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Micro-Behavioral Value Drivers

We isolate the few repeatable behaviors that reliably drive retention and long-term value—then operationalize them as CRM triggers and targeting rules that turn insight into action.

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Behavioral Experimentation

We design and guide decision-critical experiments grounded in behavioral science, to quantify incremental profit, retention, and long-term value—so you can scale the right playbook with confidence.

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Behavioral Segmentation

Behavior-based segmentation that turns your customer base into actionable groups—so your CRM team can tailor journeys, policies, and experiences by how customers behave and what they're likely to do next.

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"We partner with organizations where growth depends on long-term customer behavior—across retail, travel, subscriptions, NGOs, and broad B2B portfolios. Deployed into your existing CRM/CDP, we apply research-grade statistical modeling to reveal, predict, and scale the behaviors that drive retention and profitability—earlier than traditional metrics can."

Joel Anderssén, Partner & Lead Data Scientist
Joel Anderssén, Partner & Lead Data Scientist
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