Decision-Driven Customer Intelligence

 

We start with the decisions that matter most for profitable growth and translate first-party customer data into research-based predictive signals that guide prioritization and action. As journeys become less observable, these signals provide a reliable foundation for decision-making, focusing on the critical few that drive long-term value.

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 translate them into 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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Value-Based Acquisition Signals

We design and validate customer value signals (e.g., predicted CLV or contribution margin) and translate them into decision rules for activation in Google/Meta, implemented with your in-house team or agency.

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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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