--- title: "What Is the AEO Score? How Waggle Rates Your Content for AI Search" url: "https://plugpress.co/docs/waggle-aeo-score.md" canonical: "https://plugpress.co/docs/waggle-aeo-score/" published: "2026-07-28" modified: "2026-07-28" author: "Fahim" tags: - "Waggle" --- # What Is the AEO Score? How Waggle Rates Your Content for AI Search Waggle's per-page **AEO score** (0–100) rates how easily an AI answer engine — ChatGPT, Perplexity, Google AI Overviews, Gemini, Claude — can lift and quote your content. It is a transparent, deterministic rubric: no AI runs to produce it, every point has a reason, and every weight is grounded in published evidence. This page explains each factor, its weight, and *why* it's weighted that way, so nothing reads as invented. ## The evidence base The weights are tiered by how strong the evidence for each factor is: - **Tier 1 — causal, peer-reviewed.** The Princeton/Georgia Tech study *"GEO: Generative Engine Optimization"* (Aggarwal et al., **KDD 2024**, [arxiv.org/abs/2311.09735](https://arxiv.org/abs/2311.09735)) ran controlled experiments over ~10,000 queries and found three page edits that measurably raised how often content was cited — roughly **+30–41% each**: adding **cited sources**, **statistics**, and **quotations**. These carry the most weight. - **Tier 2 — retrievability, well-supported.** Where the answer sits and how extractable it is. About **44% of AI citations are lifted from the first ~30%** of a page (Ahrefs), and pages whose headings match the query are cited far more often. - **Tier 3 — hygiene, modest/correlational.** Freshness (AI-cited pages run only ~26% fresher on average — real but small) and author attribution (an E-E-A-T signal). ## The 9 components and their weights | Component | Weight | Tier | Why this weight | | --- | --- | --- | --- | | **Early answer** | 18 | 2 | A direct, self-contained answer in the opening. ~44% of AI citations come from the first ~30% of a page — the opening is what gets lifted. | | **Cited sources** | 17 | 1 | Outbound links to authoritative sources. The single biggest page-level lever for content that isn't already top-ranked (GEO: up to +115% for a mid-ranked page). | | **Statistics** | 16 | 1 | Concrete numbers and data. GEO measured ~+30–41% visibility from adding statistics. | | **Quotations** | 12 | 1 | Direct quotes from sources/experts. A GEO top-three lever (~+28–40%). | | **Readability** | 9 | 2 | Fluent, scannable writing: concise sentences (~18 words is the cited-content average) plus subheadings and lists so passages are self-contained. GEO fluency lift ~+15–30%. | | **Question headings** | 8 | 2 | Headings phrased as the questions readers ask. Pages with query-matching headings are cited markedly more (~41% vs 29%). | | **Freshness** | 8 | 3 | Recency of the last update. Real but small (~26% fresher), so weighted low and with generous thresholds — evergreen pages aren't punished. | | **Attribution** | 7 | 3 | A visible author bio / expertise signal (E-E-A-T; GEO authoritative-tone lift ~+10–20%). | | **FAQ coverage** | 5 | 3 | Visible on-page Q&A pairs — self-contained, extractable answers. Weighted lightly: it overlaps Question headings, and note this scores *visible content*, not FAQPage schema (see below). | Total: **100**. Each component scores full / half / zero against simple, fixed thresholds, and returns a plain-language note plus a fix hint. ## What we deliberately do **not** reward Because the evidence says these don't drive AI citations: - **Raw word count / long-form for its own sake** — near-zero correlation (~0.04 across 174k pages, Ahrefs); about half of AI-cited pages are under 1,000 words. - **Keyword stuffing** — zero or *negative* effect in the GEO study. - **A table on every page** — tables help *comparison/commercial* queries, not how-to guides, so we reward a table when present (inside Readability) but never penalise a page for not having one. ## What the score **can't** see (and we say so) A page-level score can't measure off-page factors that, for **Google AI Overviews and Perplexity**, matter most of all: - **Organic ranking** — ~76–91% of AI Overview / Perplexity citations are pages already ranking in Google's top 10 ([Ahrefs, 1.9M citations](https://ahrefs.com/blog/search-rankings-ai-citations/)). - **Off-page brand mentions** — the strongest brand-level signal (unlinked brand mentions, including on YouTube) correlates with AI visibility ~3× better than backlinks ([Ahrefs, 75k brands](https://ahrefs.com/blog/ai-brand-visibility-correlations/)). So a perfect on-page score is necessary but not sufficient: it decides *which of the already-eligible pages gets quoted*. Waggle surfaces these as guidance, not as scored points it can't honestly measure. ## Honesty notes on adjacent features - **llms.txt** is discoverability hygiene, **not** a proven citation driver. There's no confirmed evidence a major engine consumes it (Google has said its Search systems don't read it). Waggle serves it and lists it, but never sells it as a ranking win. - **Schema / structured data** is correlated with citation but **not** causally proven; controlled tests show no significant citation lift from adding JSON-LD. It's legibility hygiene (and Bing confirms it aids *understanding*), not a citation lever. - **FAQ / FAQPage schema** — Google retired the FAQ *rich result* (the SERP dropdown) on **May 7, 2026**, so the JSON-LD earns no Search snippet, and LLMs read rendered text rather than the markup. Waggle's FAQ score therefore rates **visible on-page Q&A content** (which is still extractable by AI), not the schema — and weights it lightly because it overlaps question-style headings. The FAQPage markup remains valid and is still read by some non-Google crawlers, but it is never sold as a Google ranking or rich-result feature. ## Key sources - [GEO (peer-reviewed, KDD 2024)](https://arxiv.org/abs/2311.09735) - [Ahrefs — organic rank vs AI citations (1.9M citations)](https://ahrefs.com/blog/search-rankings-ai-citations/) - [Ahrefs — brand-visibility correlations (75k brands)](https://ahrefs.com/blog/ai-brand-visibility-correlations/) - [Ahrefs — content length vs AI Overviews (174k pages)](https://ahrefs.com/blog/short-vs-long-content-in-ai-overviews/) - [Zyppy — 23 factors / 54-study meta-analysis](https://ppc.land/23-factors-that-actually-get-your-content-cited-by-ai-search-engines/) - [Search Engine Land — schema & AI search reality check](https://searchengineland.com/schema-markup-ai-search-no-hype-472339) - [Search Engine Journal — Google on llms.txt](https://www.searchenginejournal.com/google-says-llms-txt-is-purely-speculative-for-now/577576/) ## Related guides - [The Waggle panel in the editor](/docs/waggle-editor-sidebar/) - [Reading your Waggle Dashboard and readiness score](/docs/waggle-dashboard-and-readiness-score/) - [Machine files: llms.txt, Markdown, and pricing.md](/docs/waggle-machine-files/)