What this is
I help teams measure what matters, turn raw data into KPIs and dashboards, and deliver explanations and recommendations — not just charts.
The process in three steps:
- Define questions and KPI definitions
- Validate data and compute metrics
- Communicate insights and next actions (readout / slides)
Who it’s for
Typical roles
- Founders / Management
- Marketing leadership (growth, acquisition)
- Product leadership
- Ops / Finance leads
- Analysts needing stronger pipelines and definitions
Typical situations
- “Different teams report different numbers”
- “We have dashboards, but nobody trusts them”
- “We need recurring reporting for stakeholders”
- “We need to evaluate experiments/A-B tests properly”
Typical engagements
KPI & Reporting Audit (1–2 weeks)
You get: a short report + prioritized plan
- KPI definitions and gaps
- Data quality issues (sources, freshness, missing fields)
- Dashboard review: what’s useful, what’s noise
- Recommendations: fixes + quick wins
KPI System + Dashboards (2–6 weeks)
You get: working dashboard(s) + documentation
- KPI dictionary (definitions, formulas, owners)
- Dashboard(s) in Looker/Metabase/custom
- Scheduled reporting (optional)
- Handover workshop
Ongoing Decision Support (monthly)
- Recurring analysis & narrative reporting
- “What changed / why / what to do” readouts
- Experiment evaluation support
Deliverables
- Dashboard(s) + metric definitions (“KPI dictionary”)
- Short executive summary (1–2 pages) or 5–10 slide readout
- Query pack / notebooks used for analysis
- Handover: how to interpret metrics, what to watch
For technical readers
- Data modeling for metrics (staging → marts)
- SQL metric layers, standardized dimensions
- Data validation checks (freshness, null rates, outliers)
- Reproducible notebooks/scripts for analysis
- Versioned dashboard changes + documented KPI assumptions
Why I’m good at this
- Built KPI dashboards and recurring reporting for management/marketing/product teams
- Ran experiments (A/B tests) and statistical analyses to answer business questions
- Worked in SaaS/Fintech contexts where metrics need governance and reliability
- Comfortable translating findings into stakeholder-ready presentations
How I work
- Kickoff: goals + current tooling + constraints
- Quick diagnostic: sample data + current metrics
- Iteration cycles: weekly readout + next steps
- Ownership: client owns dashboards + definitions; I deliver docs + handover