STUDY 01
AI crawler access across 506 top sites
506 sites
What leading websites permit and block across major AI crawlers, based on publicly observable access controls during the collection period.
ORIGINAL RESEARCH
SEO and AI search research with methods attached
MoxSEO publishes focused research on crawler access, answer extractability, local business signals, and the website structures that influence machine retrieval.
01 / RESEARCH DIRECTORY
Start with the dataset closest to the question
Each study describes a defined sample and collection window. Findings should be used to generate better questions, evaluate observable patterns, and guide testing on your own website. They should not be treated as universal rules for Google, AI platforms, or every market.
STUDY 02
AI answer extractability across 243 sites
243 sites
A structural scoring study examining how clearly pages expose direct answers, supporting context, evidence, and machine-readable relationships.
STUDY 03
City-market AI readiness
148 businesses
A 20-city study of ownership, trust, local entity, and answer-readiness signals visible across sampled business websites.
02 / RESEARCH PRINCIPLES
Make the method inspectable enough to challenge
Useful research defines the question, sample, collection method, scoring rules, processing steps, exclusions, and known limitations. When code or data can be shared responsibly, the study should make reuse and verification easier.
- Specific research question
- Documented sample and collection date
- Reproducible definitions and scoring
- Separation of observation and inference
- Limitations, corrections, and version history
03 / INTERPRETATION
What the findings can—and cannot—tell you
OBSERVATION
Patterns in the sampled pages
Can show
Prevalence, co-occurrence, access settings, structural characteristics, and differences defined by the published method.
Bounded by the sample
INFERENCE
Possible explanations
May suggest
Relationships worth testing, implementation risks, areas for deeper inspection, and questions for controlled experiments.
Requires additional evidence
CAUSALITY
Universal ranking effects
Cannot prove
A cross-sectional website study cannot establish every platform’s internal ranking logic or guarantee that one change will cause visibility.
No universal platform rule
04 / DATA RESPONSIBILITY
Public evidence still requires careful handling
Research uses public or appropriately authorized information, minimizes unnecessary personal data, documents transformations, and avoids presenting sampled observations as private platform knowledge. Material errors should be corrected visibly.
05 / PRACTICAL USE
Turn research into a site-specific test
Use a study to identify a relevant pattern, inspect whether it exists on your own rendered pages, define the expected user or technical benefit, implement the smallest credible change, validate production, and measure an appropriate outcome. Research informs the decision; your website provides the evidence for your implementation.
06 / RESEARCH IN PRACTICEEVIDENCE OWNERFounder direction and standards CONTRIBUTORSResearch, content, technical, and data roles APPLICATIONFrom finding to production test AI SEARCHAI SEO and answer visibility SCALE CONTEXTMiracuves catalogue architecture CLIENT EVIDENCECase studies and measurement boundaries
Connect findings to accountable decisions and client work
Research should not sit in an isolated publishing archive. These links show who is responsible for evidence standards, how findings move into delivery, which capabilities use them, and where comparable questions arise in client systems.
Review the responsibility for keeping claims, priorities, and recommendations proportional to available evidence.
See the specialist responsibilities that turn a question into inspection, implementation requirements, and measurement.
Follow the stages used to translate a pattern into a scoped change, validated release, and measured result.
See how crawler access, extractable answers, entity signals, and measurement become service requirements.
Explore a project where page systems, templates, retrieval, and large-scale consistency were operational questions.
Compare research findings with project-specific constraints and recorded outcomes.
06 / COLLABORATION
Bring the question your team needs to answer
MoxSEO can help frame a focused research problem, audit an observable system, design a measurement approach, or translate findings into implementation requirements.