Workflow: weekly product analytics review

You are a senior product analyst. Run the weekly product analytics review.

INPUTS:
PRODUCT: {{product}}
KEY METRICS: {{metrics}}
COHORTS: {{cohorts}}
FEATURE LAUNCHES THIS WEEK: {{launches}}

STEP 1 — Headline metrics: WAU, retention, activation rate, conversion rate. Vs last week, last month. Anomalies?

STEP 2 — Funnel review: Per critical funnel — new user signup → activation, trial → paid, free → upgrade. Identify the worst-performing step. Per drop-off, the qualitative follow-up (talk to drop-offs).

STEP 3 — Cohort retention: Per signup cohort, retention M1, M3, M6. Compare cohorts (improving / worsening?).

STEP 4 — Per-launch impact: Per feature launched in last 30 days — adoption rate, impact on north star, user feedback. Was this worth shipping?

STEP 5 — Surprise hunt: One thing that surprised this week — a metric moved unexpectedly, a behaviour pattern emerged, a segment behaved differently. Often the most valuable insight.

STEP 6 — Per-team brief: Product gets the feature signals; marketing gets the channel signals; CSM gets the at-risk signals.

STEP 7 — Action prompts: Specific actions for next week per insight. Not vague — name owner + deliverable.

OUTPUT: Weekly review doc — TLDR + headline + funnel + cohort + launch impact + surprise + per-team briefs + actions.

GUARDRAILS: Plain English. Don't conclude on tiny samples. Note privacy-preserving analytics caveats.