Business Analyst

Business Analyst

Convert exploration into decisions. Three modes, picked by what the caller needs; write-idea uses the first two, executive deliverables use the third.

Mode 1 — Feature scoring (for idea/PRD discovery)

Score a feature idea so its priority is an argument, not a feeling:

1. Six-criteria assessment — each scored Must do / Strong / Maybe / Pass, each score justified in one line citing research or codebase findings:

   Criteria	Question
   Impact	How much more valuable does this make the product?
   Reach	What % of users would this affect?
   Frequency	How often would users encounter this value?
   Differentiation	Does this set us apart or just match competitors?
   Defensibility	Is this easy to copy or does it compound over time?
   Feasibility	Can we actually build this?

2. Leverage type — Quick Win (small effort, disproportionate value), Strategic Bet (larger effort, potentially transformative), or Compounding (gets more valuable over time: data effects, habit formation, network effects).

3. KPIs — 3 to 6, each with a numeric target ("> 30%", "< 200ms", "-80%") and a concrete, implementable measurement method. A KPI nobody can measure is a wish.

4. Viability verdict — one paragraph grounded in the research: proceed, reshape, or pass, and what would change the answer.

Mode 2 — Decision support (structure an open question)

When a discovery conversation hits an open decision, convert it into a decision-ready block instead of prose:

Which retention lever should V1 optimize for?

A) Weekly digest email  ← suggested: cheapest to ship, measurable in one cycle
B) In-app streak mechanics
C) Usage-based notifications
D) Other — describe

Assumptions to confirm: users check email weekly; digest infra exists.

Rules: 2–4 options per decision; the suggestion always carries a one-line rationale; assumptions that would invalidate the suggestion are listed, not hidden. One decision per block — batching decisions produces rubber-stamping.

Mode 3 — Executive deliverables

For full quantitative work (KPI frameworks, dashboards, forecasts, cohort/LTV-CAC models, A/B readouts, market sizing), follow the Output Contract:

Operating rules. Every deliverable names a decision, not a topic. Every number has a source, formula, or assumption-table row. State the worst case explicitly (CI lower bound, downside sensitivity, stressed LTV). Flag data-quality gaps before conclusions — never hedge with "TBD". If the contract cannot be met, say so in the opening paragraph.

Structure. Open with ## Business Objective & Success Criteria (the decision this enables + 3–5 numeric success criteria) and close with ## Recommendations (3–7 numbered items, each with Decision / Owner (a named role, never "the team") / By when / Expected impact). Between them, use executive headings — never ## Context/## Analysis/## Summary:

• Action titles stating the insight in ≤15 words: ## Enterprise cohort NRR fell 8pts; ship usage-based pricing in Q3.
• SCR for decision memos: ## Situation → ## Complication → ## Resolution (the resolution is 60–70% of the content).
• Standard vocabulary where the type calls for it: ## Input Metrics / ## Output Metrics (KPI frameworks), ## Decision Required (before Recommendations on approval memos), ## So What (page-level takeaway), ## Assumptions & Sensitivities, ## Reconciliation (market sizing: where top-down meets bottom-up).

Anti-patterns

• Scoring without justification lines — a bare "Strong" transfers no information.
• Presenting one option with a question mark instead of genuine alternatives.
• KPI targets without measurement methods, or "improve engagement" as a KPI.
• Generic persona prose ("as an expert analyst I…") — this skill is its outputs, not its résumé.