Rabbit Rank

Multilingual AEO. 🌍

AI engines cite per-language. Your English page can’t earn German citations. Run a locale-by-locale audit — gaps become priorities.

THE LOCALE SCAN (example brand):

Configured: 9 locales · At parity: 3 of 9 · Avg coverage: 68% · Biggest gap: JA (22%)

→ EN-US (PRIMARY) — 100% — 142 pp — 540 cites ✓
→ EN-GB (LIVE) — 92% — 131 pp — 318 cites ✓
→ DE (LIVE) — 78% — 110 pp — 184 cites ✓
→ FR (GAP) — 65% — 92 pp — 118 cites
→ ES (GAP) — 51% — 72 pp — 78 cites
→ PT-BR (GAP) — 44% — 63 pp — 52 cites
→ JA (CRITICAL) — 22% — 31 pp — 14 cites ⚠
→ ZH-CN (CRITICAL) — 18% — 26 pp — 9 cites ⚠
→ NL (DRAFT) — 8% — 11 pp — 2 cites

The rule: Locale = entity.

Ship hreflang + per-locale schema. Each locale earns citations independently — treating EN as the master is the #1 multilingual AEO mistake.

Translating your EN page to German and switching the URL is not multilingual AEO. The German page needs its own:
→ Author bios (in German)
→ Schema (in German, with )
→ Internal links (between DE pages, not back to EN)
→ Original sources cited (German news, not just NYT)

Most teams skip 3 of those 4 and wonder why their German citations are flat.

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GlobalMarketing

AEO × the funnel. 🎯

“AEO content” isn’t one thing. Each funnel stage needs different formats, different schema, different signals. Here’s the playbook per stage.

→ STAGE 01 — AWARENESS (4 plays)
Glossary, “what is X” pages, frameworks.
Goal: own the concept. Article + DefinedTerm schema.

→ STAGE 02 — CONSIDERATION (3 featured plays) ← 42% of AEO budget · 3.2× cite rate vs awareness

01 — Comparison pages (you vs them).
“Brand X vs Brand Y” pages with explicit feature, price, use-case tables. Highest cite rate on mid-funnel queries. Build one for every competitor.

02 — Use-case landing pages.
One URL per use case. Specific buyer language: “Atlas for marketing teams”. AI engines lift these for “best X for Y” queries.

03 — Buyer’s-guide hubs.
10+ page clusters: criteria, pitfalls, evaluation rubrics, ROI math. FAQPage schema mandatory. Cited as “expert source” by 60%+ of engines.

→ STAGE 03 — DECISION (5 plays)
Pricing, case studies, demo pages, security docs.
Product + Offer + FAQ schema. High intent traffic.

→ STAGE 04 — RETENTION (3 plays)
Help centre, release notes, integration docs.
HowTo + FAQ schema. Cited for “how do I” queries.

The error most teams make: they spend 100% of AEO budget on awareness (“what is AEO”) and wonder why they don’t convert. Consideration content gets cited 3.2× more for the queries that actually drive deals. Allocate accordingly.

Save this.

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The AEO settings panel. ⚙️

Eight settings in your CMS. Get them right once and your AEO foundation runs itself. Get them wrong and every page leaks.

THE 8 SETTINGS, GROUPED:

→ AI BOT ACCESS
01 — Allow GPTBot (OpenAI’s crawler. Required for ChatGPT citations.)
02 — Allow PerplexityBot & ClaudeBot (Don’t block these — growing fast.)
03 — Allow Google-Extended (Powers AI Overviews. Separate from Googlebot.)

→ CONTENT & SCHEMA
04 — Default schema type: Article (auto-apply to new posts)
05 — Refresh cadence: 30 days (auto-bump modified dates on top pages)

→ MONITORING
06 — Citation alerts: ON (Slack ping on new AI citation)
07 — Brand-prompt monitor: ON (20 daily prompts, accuracy + sentiment)
08 — Saved.

The rule: All toggles ON.

The only valid reason to disable an AI bot is a paid deal with that engine — and you’d know if you had one. Default to access. The 1% of teams that should block are big enough to have an opinion about why; everyone else benefits from leaving it open.

Most teams never look at these settings. They install a plugin, accept defaults, and move on. The cost is invisible — until you realize your competitor’s GPTBot toggle is on and yours isn’t.

→ rabbitrank.com

Your citation heatmap. 📊

A year of AEO activity on one screen. When your content gets cited — and the dead zones — tell you exactly what’s working.

THE NUMBERS (last 12 months):
→ 2,847 total citations
→ +94% year-over-year
→ 284 active days / 365
→ Best week: Week 11 (142 cites)
→ Current streak: 28 days
→ Peak day: March 14, 2026 (38 citations)

3 patterns the heatmap reveals:

01 — Tuesdays & Wednesdays peak.
Mid-week is when AI engines do most refreshing. Publish Monday to land in the next crawl.

02 — Dec–Jan dead zone.
Lighter cells = lighter engagement. Don’t ship pillar content over holidays. Use the window to refresh existing work.

03 — Q1 was the breakout.
Week 11 had 142 citations — that’s a content piece that hit. Reverse-engineer it. What was different about that week? Replicate.

Save this — and look at your own citation pattern this way. The dead zones tell you when not to ship. The bright weeks tell you what to do more of.

→ rabbitrank.com

The AEO 2027 roadmap. 🗓️

Four quarters. Four directional bets. Plan against these now — the teams that prepare in Q1 catch the curve, not the wave.

Q1 ‘27 — AI OVERVIEWS EVERYWHERE (HIGH confidence)
→ ~90% of Google SERPs show AI Overview by default
→ Click-through to traditional results drops further
→ “Zero-click” becomes the norm, not the exception

Q2 ‘27 — CITATION APIs FOR BRANDS (MED confidence)
→ Engines expose “how often you’re cited” via API
→ Citation share becomes a tracked KPI
→ First-party AEO analytics matures

Q3 ‘27 — VOICE AI HITS 25% (MED confidence)
→ Voice queries reach 25% of AI search
→ Conversational schema (action-oriented) gains weight
→ “Best answer” beats “best ranked”

Q4 ‘27 — MULTIMODAL BECOMES STANDARD (LOW confidence)
→ AI answers blend text + image + video natively
→ Image + video schema parity with article schema
→ Single-format pages get penalized

The directive: Prepare now.

Q1 is the only high-confidence quarter. Plan for it. Treat Q2–Q4 as scenarios — ready your team but don’t bet the year on them.

Most teams plan AEO one quarter at a time. The teams that win are the ones reading the next four quarters now — even if half of them turn out wrong.

Save this — and check it against your own 2027 roadmap.

→ rabbitrank.com

Your AI activity feed. 📡

Stop guessing what AI engines are doing on your site. Surface every fetch, every index, every citation — in one feed.

SAMPLE ACTIVITY (live · ~7 events/hr):

🌸 2 min ago — PerplexityBot CITED /aeo-guide for “what is AEO” (source #1 of 3)

🟢 14 min ago — GPTBot CRAWLED /blog/citation-share (200 OK · 6,420 tokens)

🌸 22 min ago — ChatGPT CITED /help/schema for “FAQPage schema example” (source #2 of 4)

🔵 38 min ago — Google-Extended RE-FETCHED /sitemap.xml (200 OK · 142 URLs)

🟠 52 min ago — ClaudeBot CRAWLED /research/2026-report (200 OK · 8,910 tokens)

🟣 1h ago — BingBot INDEXED /comparison/x-vs-y (first time)

3 events worth alerting on:

01 — 403 / 404 from any AI bot
Something’s blocking access. Investigate same day.

02 — 30+ days since last citation
A page that stopped getting cited. Refresh trigger.

03 — New URL crawled but never cited
Eligible but not trusted. Audit content quality.

Most teams have no idea what AI bots are doing on their site. They check their dashboard once a week. The teams with real-time feeds catch problems before they become drops.

Save this.

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TechnicalSEO SiteMonitoring

Mine the AEO long tail. ⛏️

Head queries are crowded. Long-tail queries get cited 4× more often per impression — with 90% less competition. Filter, rank, ship.

QUERY MINING (example “AEO” cluster):

WIN candidates (high opp. score):
→ “how to add FAQ schema to a saas pricing page” (5w) → Opp. 9.2
→ “does GPTBot respect noindex tags” (6w) → Opp. 8.9
→ “why is my page not cited by perplexity” (7w) → Opp. 8.6

TEST candidates (medium opp.):
→ “aeo schema example for ecommerce” (5w) → Opp. 6.8
→ “aeo vs geo difference” (4w) → Opp. 5.4

SKIP candidates (low opp., high difficulty):
→ “what is aeo” (3w) → Opp. 3.1
→ “aeo tools” (2w) → Opp. 2.4

3 takeaways from the mining process:

→ 5–7w SWEET SPOT
Queries of 5–7 words have highest opp. scores. Shorter = competitive. Longer = no volume.

→ 4× CITE RATE LIFT
Long-tail cite-rate is ~4× head queries. AI engines reach further on specific Qs.

→ 200+ PER CONCEPT
A single concept yields 200+ minable long-tail queries. Mine the cluster — don’t pick one.

Most teams chase head queries because volume looks attractive. The cited-rate math says: 200 long-tail wins beat 1 head-query rank, every time.

Save this — and mine your concept this week.

→ rabbitrank.com

The AEO QA workflow. ✅

Most teams rely on writer judgment. Industrial teams run content through a 6-step pipeline. Every piece, every time, no exceptions.

THE 6-STAGE PRE-PUBLISH PIPELINE:

01 · DRAFT
Outline & first draft per brief. 50-word block locked.

02 · SCHEMA CHECK
Validates clean. Article + FAQ + Person. 0 errors.

03 · QUOTE AUDIT
≥ 2 named experts. Credentials linked. Sources verified.

04 · STAT CHECK ← currently running
≥ 3 numbers with source URLs. Each verified & dated.

05 · DATE STAMP
Published & modified dates set. Visible & in schema.

06 · PUBLISH
Sitemap updated. Engines pinged. Tracked in CMS.

The rule: Any step fails → the piece doesn’t ship.

Writers fight this for the first month. By month 3, they brief themselves to the spec because they’re tired of failing QA.

6 gates, no exceptions. The teams that install this pipeline ship 30% less content — but 3× the cite rate per piece. The math wins.

If your AEO is inconsistent, it’s because your pipeline is. Industrial-grade content needs industrial-grade QA.

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AI engine market share, 2026. 🥧

If you’re only thinking ChatGPT, you’re missing 40% of the market. Here’s the share — and where to actually focus.

THE BREAKDOWN (estimated share of AI-search queries):

→ ChatGPT — 60% (883M MAU, still growing)
→ Gemini — 15% (Google AI, growing)
→ Perplexity — 10% (growing fast)
→ Claude — 8% (Anthropic, growing)
→ Copilot — 5% (Microsoft, flat)
→ Other — 2% (DuckDuckGo, You.com, etc, flat)

Total AI queries: ~2.4B per day.

3 calls on where to actually focus:

01 — Optimize for ChatGPT first.
60% of the market. If your content isn’t cited here, nothing else matters yet.

02 — Don’t skip Perplexity & Claude.
18% combined, growing fast, B2B-skewed audiences. The teams that catch them early win.

03 — Test on Gemini monthly.
Google’s pull means it ramps fastest from here. Check accuracy quarterly.

The pattern: ChatGPT is the floor, not the ceiling. Win there, then expand. Brands that obsess over one engine miss the next one — and the audience is splitting faster than most teams realize.

Save this.

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Steal your competitor’s citation map. 🔍

If a rival is getting cited and you aren’t, the data is sitting right there. Pull it, study it, copy the moves — specifically.

Side-by-side (30-day citations):

YOUR-DOMAIN.COM — 42 citations
→ /aeo-guide (14)
→ /blog/citation-share (9)
→ /help/schema (7)
→ /blog/dates-matter (6)
→ /about (6)

RIVAL.COM — 118 citations
→ /research/2026-aeo-report (38)
→ /comparison/x-vs-y (24)
→ /glossary/aeo-terms (19)
→ /blog/case-studies (21)
→ /founder/jane-doe (16)

3 moves the data tells you:

01 — They own “research” pages. You don’t.
/research/2026-aeo-report alone = 38 citations. Build your own original-data piece this quarter.

02 — They have a founder page that gets cited.
/founder/jane-doe = 16 citations. You don’t have a /founder/ URL at all. Fix this in week 1.

03 — They’re winning bottom-funnel.
/comparison/x-vs-y + /glossary = 43 combined. You have neither. These are quick builds — ship next sprint.

This isn’t espionage. It’s pattern recognition. The pages your rival is winning on are visible. Decide which patterns to copy this quarter.

→ rabbitrank.com