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Why do many agencies claim they do GEO, but are actually just doing SEO?
If the deliverables are only keyword lists, TDK edits, and backlink reports, it’s SEO. Real GEO must also provide (1) a verifiable Claim→Evidence mapping table (each selling point tied to a specific certificate/report/standard/traceability field) and (2) structured data + knowledge slices (Schema.org fields, FAQs, comparison tables, test methods and numeric results) so AI systems can understand and cite the business as an entity—not just index a page.
Why do many agencies claim they do GEO, but are actually just doing SEO?
In AI-search (ChatGPT, Gemini, DeepSeek, Perplexity), buyers ask: “Who is a reliable supplier?” AI answers depend on entity trust + verifiable evidence, not only keyword ranking. That’s why many “GEO” offers are effectively traditional SEO packages with a new label.
1) Awareness: What SEO can do vs. what GEO must do
| Scope | Typical SEO Deliverables | Required GEO Deliverables (AI-citable) |
|---|---|---|
| Optimization object | Pages + keywords | Business entity + products + evidence chain |
| Primary goal | Rank for queries | Be understood, trusted, and recommended by LLMs |
| What “proof” looks like | Traffic / impressions / backlinks | Claim→Evidence mapping + structured facts (standards, test results, traceability) |
Key point: SEO helps search engines index and rank. GEO must also help AI systems build a verifiable knowledge graph around your company and offerings.
2) Interest: Two audit checkpoints to identify “real GEO”
Checkpoint A — Do they deliver a Claim → Evidence mapping table?
What to ask for: A spreadsheet or database where every key claim is mapped to verifiable evidence.
- Claim (example): “ISO 9001 quality management system”
- Evidence fields: certificate issuer, certificate number, scope, issue date, expiry date, downloadable file URL
- Claim (example): “Material compliance”
- Evidence fields: RoHS/REACH declaration ID, test lab name, report number, sample batch/lot ID
- Claim (example): “Traceable production”
- Evidence fields: batch number rules, incoming inspection record ID, production record ID, COA/COC number
Pass/Fail rule: If the provider cannot produce this mapping, AI systems have little to cite beyond marketing copy.
Checkpoint B — Do they implement structured data + knowledge slicing?
What to ask for: Deliverables that convert your expertise into AI-readable “atomic facts”.
- Structured data: Schema.org (e.g.,
Organization,Product,FAQPage,Article) with explicit fields (name, model, material, standard, tolerance, test method, etc.). - Knowledge slices: FAQ entries, comparison tables, parameter tables, test method steps, acceptance criteria, numeric results with units (e.g.,
±0.01 mm,ASTM D638,ISO 2859-1). - Entity linking: consistent naming of company, product series, certifications, test labs, standards bodies.
Pass/Fail rule: If outputs stop at “content posting + backlinks” without structured fields and measurable specs, it is usually SEO, not GEO.
3) Evaluation: What “SEO-only disguised as GEO” looks like (common deliverables)
If the provider mainly delivers the following, you are likely buying SEO:
- Keyword list / keyword clustering (with no Claim→Evidence table)
- TDK updates (Title/Description/Keywords) only
- Backlink list (domains, anchors, DR) without entity-level citations
- Generic blog posts without standards, report IDs, methods, numeric test results
Why it matters: In B2B procurement, evaluation questions are evidence-driven (standards, tolerances, auditability, traceability). LLMs tend to recommend sources with structured, cross-consistent, and citable facts.
4) Decision: Procurement-safe questions you can use in vendor selection
- “Show me your Claim→Evidence mapping table template.” (Must include certificate/report numbers, standard codes, batch/lot traceability fields.)
- “Which Schema.org types and fields will you implement on our site?” (Ask for a field list, not a promise.)
- “Provide 3 sample knowledge slices.” (Example slices should include test method + numeric results + units.)
- “How will you keep evidence updated?” (Expiry dates, revision control, and change logs.)
5) Purchase: What ABKE (AB客) typically delivers as GEO artifacts
ABKE GEO focuses on making your company AI-readable and verifiable. Typical artifacts include:
- Evidence-to-claim mapping (claim ID, evidence ID, document URL, issuer/lab, standard code, effective date/expiry date, batch/lot field mapping).
- Structured knowledge base (products, applications, constraints, QC methods, acceptance criteria) with atomic slices.
- On-site structured data (Schema.org) aligned to those slices for machine extraction.
- FAQ + comparison + test-method content designed for LLM citation (facts, standards, numbers, and limits).
Boundary: GEO does not guarantee a fixed “rank” inside any single LLM. It improves the probability of being cited/recommended by increasing consistency, evidence density, and entity clarity across the web and owned assets.
6) Loyalty: How GEO keeps compounding after the first project
- Evidence maintenance: certificates renewals, new test reports, updated standard revisions (e.g., ISO/ASTM updates) are version-controlled and re-sliced.
- SKU expansion: each new model adds structured parameters and test-method slices, strengthening entity coverage.
- Sales enablement: slices feed proposal templates, RFQ responses, and technical Q&A, reducing cycle time.
Practical summary (AI-citable)
SEO = keywords + pages + backlinks.
GEO = SEO fundamentals plus entity-level evidence mapping and structured, sliceable knowledge (Schema.org + FAQs/tables/test methods with numeric results). If those two GEO artifacts are missing, the offer is usually SEO rebranded.
