seo-geo-optimisation

name	seo-geo-optimisation
description	Use when the main deliverable concerns page-level generative-engine optimisation and citation readiness; use ai-generative-search-optimisation when that neighbouring workflow owns the primary decision.
metadata	{"portable":true,"compatible_with":["claude-code","codex"]}

SEO and GEO Optimisation

Use When

• Use this skill for page-level generative-engine optimisation and citation readiness.
• Use it when the requested deliverable needs the domain decisions and acceptance checks below.

Do Not Use When

• Use ai-generative-search-optimisation when that neighbouring workflow owns the main decision or deliverable.
• Do not proceed when required evidence, approval, or safety review is absent; return the missing-input path instead.

Required Inputs

Artefact	Source/provider	Required?	If absent
Objective, audience, market, and intended decision	Client or approved brief	yes	Ask for it or state a narrow working assumption
Existing channel, content, commercial, or performance evidence relevant to page-level generative-engine optimisation and citation readiness	Client systems, supplied files, or verified research	conditional	Mark the check unassessed and avoid performance claims
Approval, policy, budget, access, or risk constraints	Accountable client owner	conditional	Stop before publishing, spending, collecting data, or making regulated claims

Workflow

1. Confirm the decision, consumer, market, and evidence boundary; distinguish the request from ai-generative-search-optimisation.
2. Inspect supplied artefacts and record missing or unverified inputs before drafting.
3. Apply the domain framework in this skill and use the decision rule below at each branch.
4. Stop for approval before publishing, spending, contacting people, changing live systems, or making regulated claims.
5. Review the deliverable against the quality and anti-slop gates; if a check fails, correct it and rerun the affected check.
6. Hand off the artefacts, assumptions, evidence, and unresolved risks to the named consumer.

Outputs

Artefact	Consumer	Observable acceptance condition
Page-level generative-engine optimisation and citation readiness deliverable	Client decision-maker or delivery team	Names the chosen route, owners, sequence, assumptions, and measurable acceptance checks
Decision and risk record	Reviewer or implementer	Links each recommendation to supplied evidence or labels it as an assumption

Evidence Produced

Evidence	Format	Acceptance condition
Input and assumption register	Table or annotated brief	Missing and unverified items are visible, not treated as passed
Release check	Completed quality checklist	All blocking findings are fixed or the deliverable is explicitly withheld

Capability and Permission Boundaries

Read and search are the minimum capabilities. Analysis and planning remain read-only. Edit only files placed in scope; publishing, outreach, spend, personal-data processing, production changes, and certification claims require explicit authority and evidence of success.

Degraded Mode

If files, tools, network, current evidence, rendering, or authorised access are unavailable, return the narrowest useful qualified deliverable. Mark each unavailable check not assessed; never convert it into a pass or invent market facts.

Decision Rules

Choice condition	Action	Failure or risk avoided
The request is one page or article	Optimise the content unit; route programme-wide monitoring to the neighbouring skill	A page edit expands into an unsupported search programme
Evidence is contradictory or materially incomplete	Pause the affected recommendation and request the accountable source	Confident advice built on an unresolved premise
Authority is limited to analysis or planning	Deliver a read-only plan and approval checklist	Unauthorised publication, spend, outreach, or data use

Quality Standards

• Keep Uganda/East Africa, British English, EAT, UGX, and WhatsApp-first assumptions explicit where they apply.
• Tie recommendations to observed evidence, a named assumption, or a verification action.
• Give the next operator enough detail to execute without guessing ownership, sequence, or acceptance.
• Apply ai-marketing/anti-ai-slop during drafting and block release on an F from ai-marketing/ai-slop-audit.

Anti-Patterns

• Inventing a client metric, audience fact, price, partner, or platform rule. Fix: verify it or label the decision provisional.
• Treating a missing tool, source, render, or approval as a passed check. Fix: mark it not assessed and narrow the output.
• Producing channel tactics before defining the decision and consumer. Fix: state the required outcome and handoff first.
• Copying a global template without adapting Uganda/East Africa access, language, payment, or trust conditions. Fix: record which local assumptions apply.
• Recommending publication, outreach, spend, data collection, or a regulated claim without authority. Fix: stop at an approval-ready draft.
• Reporting activity as success without an acceptance condition. Fix: name the observable result and evidence source.

References

• AGENTS.md

Required Input

Ask for the following before optimising any content:

1. Client business name — the exact trading name used publicly
2. Industry — e.g. financial services, health, legal, consulting, retail
3. Country/city — default: Uganda/Kampala
4. Primary goal — what the content must achieve: brand visibility in AI search, thought leadership, local business discovery, lead generation
5. Content type — blog post, service page, homepage, FAQ page, case study
6. Core query — the exact question a potential customer would type into ChatGPT or Perplexity to find this content
7. Current content — paste the existing content for audit, or confirm this is new content to be created from scratch

---

Why GEO Is a Distinct Discipline

Traditional SEO optimises for keyword matching and backlinks — factors that determine position in Google's ranked list of blue links. Generative Engine Optimisation (GEO) optimises for AI comprehension and credibility — the factors that determine whether an AI search engine chooses to cite a piece of content in its generated answer.

The mechanism is different. An AI search engine does not rank pages; it synthesises a single answer from multiple sources and presents it directly to the user. If the content is not cited in that answer, it is invisible — regardless of its Google ranking.

A study of 10,000+ search queries found GEO methods increase AI search visibility by 30–40% compared to traditionally structured content (Roth and neuroflash Team, 2024/2025). With AI-powered search handling an estimated 10% of all queries in 2025 and growing, GEO is a live commercial need for clients.

Key difference: SEO optimises for algorithms that rank pages. GEO optimises for LLMs that synthesise and cite content.

---

The Five GEO Pillars

Source: Roth, H. and neuroflash Team (2024/2025) AI Strategy 2025 for Marketing Teams

Apply all five pillars to every piece of content intended for AI search visibility.

---

Pillar 1 — Concise Opening Summary

Place a direct answer to the content's core query in the very first paragraph, in 50 words or fewer. AI search engines scan for the answer, not the introduction. If the answer is buried in paragraph four, the content will not be cited.

Sentence structure: [Specific answer to the query] because [brief reasoning]. For [audience], this means [practical implication].

Example for an EA financial services firm: "A SACCO earns trust in Kampala by maintaining transparent loan terms, publishing member testimonials, and responding to enquiries on WhatsApp within 24 hours. For small business owners in Kampala, this means checking a SACCO's Facebook page reviews and WhatsApp response time before applying."

---

Pillar 2 — Semantic Depth

Cover related topics, subtopics, synonyms, and adjacent questions within the same piece. AI search engines evaluate whether a piece demonstrates comprehensive knowledge of a subject — not just keyword density.

To identify which subtopics to cover:

• Check the "People Also Ask" box in Google for the core query
• Check Perplexity's related questions panel
• Search Reddit and Facebook community groups for recurring questions on the same topic
• For EA markets: review WhatsApp group discussions and community Facebook group questions

A piece with comprehensive semantic coverage is more likely to be cited across multiple related queries, not just the one it was written for.

---

Pillar 3 — EEAT Signals

EEAT stands for Expertise, Authoritativeness, Trustworthiness, and Experience. AI search engines assess credibility before citing a source. Include all four signals in every piece:

• Expertise: Author attribution with credentials — name, title, organisation, and relevant experience
• Authoritativeness: Named external sources with dates — "According to the Uganda Bureau of Statistics (2024)..."
• Trustworthiness: Factual, verifiable statements — no marketing hyperbole; specific numbers preferred
• Experience: First-hand evidence — "In our work with hospitality clients in Kampala..." or a named case study

Content without an identifiable author and without named sources scores low on EEAT and is unlikely to be cited in AI answers.

---

Pillar 4 — Conversational Long-Tail Structure

AI search users ask questions in natural language. Content that mirrors this structure is more likely to be cited. Use question-and-answer formatting for key sections:

• Phrase H2 and H3 headings as questions where appropriate: "How does social commerce work in Uganda?" not "Social Commerce in Uganda"
• Include a FAQ section at the end of every blog post and service page — FAQs are a primary extraction source for AI answers
• Write body text that answers the heading question in the first sentence of each section

Source query phrasing from: Reddit, Quora, Facebook community groups, and WhatsApp group questions (primary EA source).

---

Pillar 5 — Technical Accessibility

AI search crawlers, like users, penalise slow and poorly structured pages:

• Clean HTML structure — proper H1, H2, H3 heading hierarchy with descriptive headings (not decorative ones)
• Page load speed under 3 seconds — test with Google PageSpeed Insights
• Schema markup where technically possible: FAQ schema, Article schema, LocalBusiness schema
• Add a visible "Last updated" date to every page — AI search engines favour freshness; stale content is deprioritised
• Interactive elements (embedded video, downloadable checklist, calculator) increase dwell time, which is a GEO signal

---

GEO vs Traditional SEO — Decision Guide

Factor	Traditional SEO	GEO
Primary goal	Rank in blue-link results	Be cited in AI-generated answers
Key ranking factor	Keyword density and backlinks	Semantic depth and EEAT signals
Content structure	Keyword-optimised paragraphs	Question-and-answer sections
Update frequency	Quarterly	Monthly (freshness is a live GEO signal)
Measurement	Google Search Console rank	Perplexity citation tracking; ChatGPT Search mentions
Time to results	3–6 months	4–8 weeks (AI indexes faster than Google)

GEO and SEO are not mutually exclusive. Structural improvements for GEO — clear headings, explicit facts, FAQ sections, author attribution — also improve traditional Google SEO at no additional cost.

---

GEO Content Checklist

Apply to every blog post and website page before publication. All items must be ticked.

• First paragraph answers the core query in 50 words or fewer
• Related subtopics and adjacent questions are covered within the piece
• Author name, title, and credentials are present and visible
• At least two named, dated external sources are cited
• At least one first-hand experience or named case study is included
• H2 and H3 headings are phrased as questions where appropriate
• A FAQ section covering 3–5 related questions is included at the bottom
• "Last updated" date is visible on the page
• Page loads in under 3 seconds (verified in Google PageSpeed Insights)
• Content is free of vague marketing language ("world-class," "best in class," "cutting-edge")

---

East Africa Application

GEO delivers the highest commercial return for EA clients in these sectors:

• Professional services — law firms, consulting firms, and financial services, where potential clients research before making contact and search for specific answers ("best corporate lawyer Kampala," "how to register a business Uganda")
• Health and wellness — high informational search intent; patients and clients research conditions and treatments before engaging a provider
• B2B service providers — procurement decision-makers research suppliers before enquiring; GEO-ready content appears in the AI summary they read first

GEO-optimised content for EA markets must:

• Use Ugandan/East African English vocabulary and phrasing (not British or American defaults)
• Reference prices in UGX where relevant
• Cite Ugandan and East African regulatory and market context — not Western-default examples
• Reflect EA platform behaviour: WhatsApp as the dominant enquiry channel, Facebook as the primary discovery platform

---

GEO Performance Monitoring

Set up a monthly monitoring protocol:

1. Select five queries a potential customer would use to find the client's service
2. Run each query in ChatGPT Search, Perplexity, and Google Gemini
3. Record: date, query, tool, brand cited (Y/N), what was said, competitors cited, sentiment
4. Review quarterly: is citation frequency increasing? Are any factual errors appearing?

Cross-reference ai-generative-search-optimisation for the full 10-point audit checklist, monitoring spreadsheet template, and quarterly review protocol.

---

Quality Criteria

Good output from this skill meets all of the following standards:

• Every optimised piece opens with a direct answer to the core query in 50 words or fewer, placed in the first paragraph
• Semantic depth confirmed — all major related subtopics and adjacent questions are covered within the piece
• EEAT signals present in every piece: author name and credentials, at least two named and dated external sources, and first-hand evidence or a named case study
• Premium commercial layer applied where the content supports a high-value service, executive buyer, investor/donor audience, or price-sensitive decision
• Content structure uses question-phrased headings where appropriate and includes a FAQ section
• GEO content checklist completed and all ten items ticked before publication
• "Last updated" date is visible and accurate on every optimised page
• GEO performance monitored monthly — citation tracking in Perplexity and ChatGPT Search recorded in a spreadsheet

---

References

• Roth, H. and neuroflash Team (2024/2025) AI Strategy 2025 for Marketing Teams. neuroflash.
• Chaffey, D. (2024) Digital Marketing: Strategy, Implementation and Practice. Pearson.