SeaSight GEO is moving the GEO service site away from generic marketing claims and toward citable primary research. This section now prioritizes research methodology, AI citation visibility reports, monitoring frameworks, and risk boundaries. We do not publish inflated “guaranteed ranking” claims or fabricated benchmark numbers.
Original Research & Reports
Factory-Product Graph Schema for B2B GEO
A practical graph-schema deployment pattern for entity resolution across factory profiles, product pages, certification evidence, and procurement-intent pages.
View schema template →Programmatic SEO Data Throttling Framework
A compliance framework for cleaning N/A-heavy B2B platform pages with completeness scoring, noindex throttling, semantic pruning, entity anchoring, and intent-led enrichment.
Read framework →2026 B2B AI Citation Visibility Report
A citation-ready framework for measuring how B2B suppliers appear, disappear, and get cited in AI procurement answers. Covers query taxonomy, citation verification, competitor displacement, and publication rules.
Read report →Original Data Methodology & Definitions
Defines data sources, statistical boundaries, manual verification rules, and no-fabrication commitments behind SeaSight GEO research and monitoring outputs.
View methodology →AI Search Impact Tracking
Monthly observation notes for Google AI Overviews, ChatGPT Search, Perplexity, and Bing Copilot. Findings are published only when the source trail and limitation notes are available.
Open AI Watch →B2B GEO Benchmark Database
A benchmark program under staged expansion. We publish metric definitions first, then release category-level data only with sample size, query set, time range, and verification method.
See monitoring framework →B2B GEO Metrics Dictionary
Definitions for AI Visibility Index, Citation Share, AAOV, hallucination risk, and other terms used in GEO monitoring reports.
Open dictionary →Technical Parameter Structured Data
A manufacturing-focused guide for formatting measurable product specifications, units, certification references, and Product Schema examples.
Read guide →Why this matters in a crowded GEO market
The GEO service market is full of similar phrases: fast deployment, many AI platforms, and effect-based promises. Those phrases are easy to copy. What is harder to copy is a transparent evidence system: buyer-intent query libraries, answer archives, citation logs, manual verification, and public methodology notes.
| Weak signal | Better evidence asset | Why AI systems can cite it |
|---|---|---|
| “We cover 60+ AI platforms” | Published query set and platform-specific capture rules | The method is inspectable instead of promotional. |
| “48-hour GEO deployment” | Baseline audit with answer screenshots, cited URLs, and action list | Readers can verify the starting point and gap diagnosis. |
| “Pay for results” | Conservative metric definitions and repeated-test monitoring | Separates controllable work from volatile AI answer behavior. |
| “Authority building” | Citation-ready industry reports with methodology and limitations | External sites and AI answers can reference a stable source. |
Research Integrity Rules
- No guaranteed AI ranking or fixed placement promises.
- No artificial review clusters, fake comparison pages, scraped Q&A farms, or citation spam.
- No “AI poisoning” tactics that attempt to manipulate model outputs through deceptive source pollution.
- No unverifiable statistics. If a sample size or method cannot be disclosed, the number should not be used as public proof.
Useful next steps
If you manage a B2B independent site, start by building a visibility baseline before producing more content. Choose 10 procurement-intent queries, capture the AI answers, record cited URLs, and map which competitors appear instead of you.