Professional services
Start with the decision.
Focused engagements in metrics, experimentation, and causal analysis. Our services approach pairs analytical tools with the expertise to use them in your business context.
Metrics alignment
A shared definition of progress
For leaders and product teams working with competing KPIs or unclear success measures.
The engagement
Work through the business objectives, the decisions teams make, and the signals available in your data. Establish a metrics framework that connects day-to-day product work to strategic priorities.
What to bring
Your current goals, KPI definitions, a view of available data, and the people responsible for acting on the results.
Discuss a metrics workshopProposed outputs
- A shared metrics hierarchy and definitions
- A record of data gaps and measurement assumptions
- A prioritized set of questions to investigate
- A practical measurement plan
Experimentation program setup
Build the practice around the test
For teams starting an experimentation program or improving an existing one.
The engagement
Translate a product hypothesis into an experiment design. Consider assignment, sample size, measurement windows, guardrail metrics, and how results will be reviewed.
What to bring
A proposed product change, current traffic or customer volumes, and a description of how events and outcomes are collected.
Discuss your experimentation programProposed outputs
- An experiment design and analysis plan
- Sample-size and measurement considerations
- Templates for hypotheses and result reviews
- An implementation and governance checklist
Custom causal analysis
Understand what the data can support
For a specific decision about product adoption, retention, customer experience, or another measurable outcome.
The engagement
Frame the causal question, assess the available evidence, and choose an approach suited to the study design. Examine relevant assumptions and explain where conclusions remain uncertain.
What to bring
The decision you need to make, the changes or interventions involved, and an overview of the data available. Data-sharing arrangements are agreed before any transfer.
Discuss a causal analysisProposed outputs
- A clearly defined causal question and model
- An assessment of data suitability and assumptions
- Effect estimates and uncertainty where justified
- Findings, limitations, and recommended next steps
Ongoing advisory
Build your team’s judgment
Analytical guidance and knowledge transfer as your product questions evolve.
Discuss regular reviews of experiment plans, measurement choices, and causal analyses. Workshops and working sessions are scoped around the team’s actual questions and experience.
Discuss advisory supportHow we scope the work
We start with a conversation about the decision, your data readiness, and the support you need. Deliverables, timing, availability, and fees are agreed before an engagement begins.
PROSE is under development. A services conversation does not require committing to a future software subscription.
Bring us the question
Tell us where measurement is holding your team back and what a useful answer would help you decide.
Start a conversation