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Product analytics for complex systems and high-stakes decisions.

Independent analytical support for teams that have data, competing interpretations, and a product decision approaching.

Discuss a product decision

When it helps01

The team has evidence, but not yet a shared answer.

The work connects product behavior, configuration, commercial context, and stakeholder assumptions.

01The metrics disagree.

Dashboards show what changed, but not which behavior or system decision caused it.

02Retention risk is visible but vague.

The team needs to locate the journey, segment, or product logic responsible for the friction.

03Pricing needs a defensible model.

Value, user behavior, competitive context, and revenue assumptions need to be evaluated together.

04The answer must survive handoff.

The analysis needs to become a reusable model, dashboard, specification, or source-of-truth workflow.

Scope02

Evidence into action

Analysis built around the decision, not the dashboard.

I define the question, reconcile the available evidence, model the important scenarios, and translate the result into a recommendation the team can act on.

Retention diagnosis

Connect funnel, cohort, progression, and product behavior to locate friction and prioritize interventions.

Cohorts / Journeys

Pricing & value analysis

Evaluate product tiers, offers, competitive context, user choice, and the commercial implications of change.

Pricing / Scenarios

Configuration audit

Turn complex product rules and tables into traceable logic, validation checks, and safer decision inputs.

Risk / Integrity

Decision tooling

Build analytical models, dashboards, specifications, and workflows that remain useful after the initial question.

Models / Handoff

Working model03

Frame

Define the decision, deadline, owner, constraints, and evidence that would change the answer.

Diagnose

Reconcile data, product logic, qualitative evidence, and the assumptions currently shaping the discussion.

Model

Test the important scenarios and make risk, tradeoffs, and uncertainty visible.

Hand off

Deliver a recommendation, priorities, and a reusable model or operating tool.

Free diagnostic

Product Systems Health Check

Review 25 common risks across data, user journeys, pricing, system integrity, and decision readiness.

Run the health check

Questions04

Do you only work with game products?

No. Games are my deepest domain, but the analytical work transfers to products with complex user behavior, pricing, incentives, retention, or configurable systems.

Do we need a mature analytics stack?

No. The engagement can begin with exports, configuration, existing reports, qualitative evidence, and a clear product question. Data limitations are made explicit rather than hidden.

What does the team receive?

Depending on scope: a diagnosis, scenario model, decision-ready readout, prioritized recommendations, and reusable analytical tools or documentation.

Next step05

Bring the product decision that currently feels least clear.

A short qualification form establishes the context, evidence, timeline, and level of support your team needs.

Start an enquiry