Volatility-Aware AI-Visibility Measurement Skill

Purpose

This skill measures AI visibility correctly. Raw citation counts are structurally volatile -- platforms change citation behavior wholesale, and a month-over-month drop often means the platform moved, not the site. This skill designs prompt panels, computes share-of-citation, tracks citation position, and produces trend reports that separate signal from platform noise. Use it to evaluate any GEO work done with the other skills in this pack.

Core Insight

Citation volume is structurally volatile. ChatGPT's citation volume fell >90% in March-April 2026, then rebounded (seoClarity, Jun 2026). Google-side citation churn runs 8-10x ChatGPT's (same analysis). A site that did nothing wrong can lose most of its measured citations in a month; a site that did nothing right can gain them.

The consequence: monthly citation counts mislead. The valid metric is share-of-citation over repeated runs of a fixed 60-100+ prompt panel (SparkToro methodology) -- of all citations the engine gives for your prompt set, what fraction point to you versus competitors? Share-of-citation is self-normalizing: when a platform cuts citations sitewide, everyone's counts drop but shares stay comparable.

---

Step 1: Panel Design

1. Fixed prompt set. Define 60-100+ prompts that represent the site's target sub-query space (use skills/geo-fanout/ to generate them across eligibility/cost/process/location/language axes). Freeze the set -- never edit prompts mid-trend, or you break comparability. Version the panel file instead (add new prompts as panel-v2, keep v1 running for continuity).
2. Repeated runs. Run the full panel on a fixed cadence (weekly or biweekly). A single run is a sample, not a measurement -- AI answers are non-deterministic, so each prompt should ideally be run multiple times per cycle or across cycles to smooth variance.
3. Per-engine split. Measure each engine separately -- ChatGPT, Google AIO/AI Mode, Gemini, Perplexity behave differently and move on different schedules. Never blend engines into one number. Note that ChatGPT retrieval is Bing-index-based while Gemini/AIO use Google (see skills/geo-ai-index-access/) -- engine-level swings often trace back to index or pipeline changes.
4. Competitor set. Fix 3-10 competitor domains per panel. Share-of-citation is meaningless without the denominator.
5. Instrumentation. Where available, pull first-party data to corroborate: Bing WMT's AI Performance (Copilot) report (unlocked by skills/geo-ai-index-access/), and AI referral traffic in analytics.

Step 2: Metrics to Compute Per Run

Metric	Definition	Why
Share-of-citation	Your citations / all citations across the panel, per engine	The core metric; self-normalizing against platform volume swings (SparkToro)
Citation rate	% of panel prompts where you are cited at all	Breadth of cluster coverage
Citation position	Ordinal position of your citation within each answer	Position-1 citation gets ~4-5x the CTR of position 5 (⚠️ single vendor source, AuthorityTech Jun 2026 -- treat the magnitude as directional)
Turn-1 capture	% of citations earned on opening questions vs follow-ups	Opening questions are 2.5-4x more likely to produce citations (Profound, 700K conversations, Feb 2026) -- panel prompts should mostly simulate turn-1
Co-citation cluster	Which domains are cited alongside yours	Citations travel in packs: a cited conversation carries ~6 unique citations on average (Profound, Feb 2026). Your cluster neighbors reveal who the engine considers your peer set

Step 3: Co-Citation Cluster Analysis

1. For every answer citing the site, record ALL cited domains, not just yours.
2. Build the co-citation matrix: domain pairs that appear together across answers.
3. Use it to:
   • Identify the real competitive set (often not who the client expects -- .gov and institutional domains over-index in YMYL verticals).
   • Spot pack-entry opportunities: if competitors A and B are consistently co-cited for a sub-query cluster and you are absent, that cluster is the build target for skills/geo-fanout/.
   • Detect displacement early: your share stable but a new domain entering your cluster = future pressure.

Step 4: Reporting Without Overreacting

Rules for trend interpretation:

1. Never report raw citation counts as the headline. Lead with share-of-citation and citation rate over the panel.
2. Annotate platform events. Before attributing any movement to site work, check whether the whole panel moved. If all competitors' counts dropped together, the platform changed (like the >90% ChatGPT drop and rebound, Mar-Apr 2026, seoClarity Jun 2026) -- report it as a platform event, not a loss.
3. Use rolling windows. Report 4-8 week rolling share, not week-over-week deltas. Google-side churn of 8-10x ChatGPT means weekly deltas on Google surfaces are mostly noise.
4. Demand persistence. Treat a trend as real only if it holds across 3+ consecutive panel runs. Single-run spikes and drops are sampling variance plus platform churn.
5. Separate position from presence. Losing position 1 while keeping citations is a different problem (title/slug gate -- see skills/geo-fanout/) than losing citations entirely (index/access -- see skills/geo-ai-index-access/).
6. Expect the YouTube lane to swing. Video-citation share moved 50+ points in 3 months in YMYL tracking (BrightEdge, Jan 2026) -- report YouTube citations as their own series (see skills/geo-youtube/).

---

Output Format

Generate a file called GEO-MEASUREMENT-PANEL.md (panel definition + latest results):

# AI Visibility Panel: [Domain]

**Panel Version:** [vN -- prompts frozen at definition]
**Panel Size:** [N] prompts | **Competitors:** [list]
**Cadence:** [weekly/biweekly] | **Engines:** [ChatGPT / AIO / AI Mode / Gemini / Perplexity]
**Latest Run:** [Date] | **Runs to Date:** [N]

---

## Headline Metrics (Rolling 4-8 Week Window)

| Engine | Share-of-Citation | Citation Rate | Avg Position | Trend (3+ runs?) |
|---|---|---|---|---|
| ChatGPT | [X]% | [X]% | [X.X] | [Up/Flat/Down -- persistent?] |
| Google AIO | [X]% | [X]% | [X.X] | [...] |
| Perplexity | [X]% | [X]% | [X.X] | [...] |

## Platform-Event Log

| Date | Engine | Event | Panel-Wide Impact |
|---|---|---|---|
| [date] | [engine] | [e.g., citation volume drop] | [all domains -X% = platform move, not site loss] |

## Co-Citation Clusters

| Sub-Query Cluster | Domains Cited With Us | Absent Competitor | Action |
|---|---|---|---|
| [cluster] | [domains] | [domain] | [fan-out build target / watch] |

## Notes for Stakeholders

- Raw counts are NOT reported as performance; share-of-citation is the metric (SparkToro).
- Position-1 citations carry ~4-5x position-5 CTR (⚠️ single vendor source).
- Trends require 3+ consecutive runs before action.

---

Related Skills

• skills/geo-fanout/ -- generates the panel's prompt set and consumes co-citation gap findings.
• skills/geo-ai-index-access/ -- a sudden citation-rate collapse to zero usually means an index/access failure, not a content problem; check gates first.
• skills/geo-youtube/ -- YouTube citations are a separate, high-volatility series.
• skills/geo-compare/ -- monthly delta reports should consume this skill's share-of-citation series rather than raw counts.