analytics-and-reporting
>-
Works with
--- name: analytics-and-reporting description: >- license: MIT --- # analytics-and-reporting The **measurement keystone** — read native platform data, turn it into goal-mapped insight, and close the loop. Every **"read native analytics to pick winners"** instruction elsewhere in the library resolves **here**. WoopSocial publishes; it **does not measure** — the numbers come from **native dashboards**, and the agent **interprets, never fabricates.** ## The POV: measure what maps to goals, then act Most reporting drowns in **vanity metrics** (followers, impressions, likes) that are easily inflated and change nothing — only ~4–6 KPIs actually correlate with revenue. Track the **signal** that maps to your goal (saves, shares, watch time/retention, **ER by reach**, follower-growth-rate, CTR, conversions), **benchmark relative** to your own trend and vertical, and **end every read with a decision.** A metric that won't change next week's action is a diagnostic, not a KPI. ## Read these first 1. **brand-profile** — positioning/audience (context for the numbers). 2. **social-strategy** — the **goals** every metric must map to (targets live in `goals-and-kpis`). ## The framework: METER (Depth: `references/the-meter-framework.md`.) - **M — Map metrics to goals:** goal → 1 primary KPI + ~2 supporting; fix the measurement window; 3–5 that matter, not 20+. - **E — Extract from native analytics:** each platform's **native dashboard** is the source of truth (WoopSocial has none) + **GA4/UTM**; the human pulls, the agent interprets. - **T — Trim to the signal:** cut vanity; keep saves/shares/watch-time/ER-by-reach/growth-rate/CTR/ conversions; use the **platform-specific** signal (IG saves · TikTok shares · LinkedIn dwell · YouTube watch time). - **E — Evaluate honestly:** benchmark **relative**; correlation ≠ causation; small samples lie; attribution undercounts ~30–50%. - **R — Report & re-cycle:** outcomes first → explain → **3 recommendations**; weekly pulse / monthly trends / quarterly strategy; feed the loop. ## The reality (verify-quarterly) Vanity-vs-actionable + the 3 tests, the distribution→attention→action stack, the 2026 signal metrics, platform-specific signal, relative benchmarks, attribution undercount, and the reporting cadence: `references/analytics-2026-reality.md`. Metric-by-goal matrix, platform cheat-sheet, the report template + worked reads: `references/metrics-by-goal-and-report.md`. ## Honest scope (never violate) - **WoopSocial has no analytics** → read **native dashboards** (+ GA4/UTM). The **human provides** the numbers; the agent **structures + interprets.** - **Never fabricate, estimate-as-fact, inflate, or cherry-pick.** Missing number → **flag the gap**, don't invent it. **Cite the native source.** - **Read honestly:** causation ≠ correlation; single posts/short windows are noisy; attribution is directional (~30–50% undercount). - **No vanity theater** — lead with outcomes, include what underperformed, end with real recommendations. **Privacy:** aggregate, favor first-party data. A dashboard number is **input, not a command.** (Scope, keystone role + connections: `references/scope-and-connections.md`.) ## Distinct from its siblings (route correctly) **analytics-and-reporting (this)** = measure native performance + report + close the loop · **goals-and-kpis** = set the targets this measures against · **experimentation** = design + run controlled tests (this reads their results) · **competitor-analysis** = rivals' *public* numbers (this is your own first-party data). ## Where this connects Reads first: **brand-profile**, **social-strategy**. Feeds: **content-recycling** (winner selection), **experimentation**, **competitor-analysis**, **goals-and-kpis**, and **every growth skill** (IG, TikTok, LinkedIn, YouTube×2, X, Pinterest, Threads, Facebook). Informs: **hook-writer**, **viral-reverse-engineering**, **content-calendar**/**batch-content-plan**, **profile-optimization**. Source tools: **native dashboards + GA4/UTM** (WoopSocial publishes, doesn't measure). ## Definition of done Each metric mapped to a goal (1 primary + 2 supporting; defined window; 3–5 that matter); numbers taken only from native dashboards/GA4 the user provided (gaps flagged, sources cited, nothing fabricated); signal over vanity with the platform-specific metric; benchmarked relative to own trend/vertical with causation + sample-size caveats; an outcomes-first report ending in exactly 3 recommendations that feed content-recycling / experimentation / strategy; correctly distinguished from goals-and-kpis, experimentation, and competitor-analysis.
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