Why do many agencies claim they do GEO, but are actually just doing SEO?

发布时间：2026/03/14

类型：Frequently Asked Questions about Products

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.

GEO vs SEO Generative Engine Optimization structured data evidence mapping ABKE