Analytics And Reporting

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.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: social-media-skills
• Source: social-media-skills/skills
• License: MIT
• Homepage: https://social-media-skills.com

Install and usage instructions live in the source repository linked above.