What the research says about search and AI answers
Of 1,974 Wikipedia results, 27% appeared first; that is not Wikipedia’s share of all first positions (Lewandowski et al., 2021, §5).
The claim that Wikipedia occupied roughly a quarter of all first positions is not what the cited paper measured. Lewandowski and colleagues described the positions occupied by Wikipedia's own results. That small change in wording changes the population. Lewandowski et al., 2021, §5.
Jill Whalen's historical warning about ranking measurement, “an impossible measurement,” is a useful companion to these tables. It is attributed practitioner testimony, not a new experimental finding. [Ledford, 2009, printed p. 448].
We started this section by reading a supplied collection of search research, textbooks, operator guidance and recent writing about AI answers. The collection contains 21 PDF documents, including an edited article collection and a large conference volume; it is not a set of independent experiments of equal quality. The source ledger separates the articles and editions that those containers hold. The evidence standard explains what each grade permits.
You can use these pages to find a defensible claim, inspect a familiar statistic or decide what to measure next. Google search positions, scholarly relevance ordering and vendors named in AI answers are different outcomes. We place their findings beside each other where they illuminate a practical question, while retaining their original units.
Which questions do the insights answer?
| Question | The useful distinction |
|---|---|
| Where is the advantage if most Google results carry optimization signals? | A page's signals, its position and a causal benefit are separate claims. The comparison with AI-cited pages awaits its registered analysis. |
| Why is there no reliable ranking recipe? | An exploratory correlation cannot reveal a universal engine formula. |
| What does a single rank conceal? | The same vendor can be named in some repeats and absent in others. |
| Does a familiar brand ensure visibility? | Presence in a fixed buyer-question sample is a separate observation from company stature. |
| Can an engine's ordering change without a notice? | Dated snapshots remain useful when their collection conditions travel with them. |
| Who gets cited for software questions? | A cited publisher class describes the source of a link; it does not reveal an engine's private trust judgment. |
| What role do software review sites play? | Citation frequency and the quality of the underlying reviews need separate assessment. |
| How concentrated are category answers? | A category may spread mentions across vendors differently from another category or engine. |
| Why publish original research? | Google's advice supports useful original work without promising a citation or a commercial return. |
| How much GEO research can a reader check? | A dated, reproducible search is more informative than a confident claim about the whole literature. |
What is each study’s current status?
Study 1, optimization signals on cited pages: the existing plan is public at OSF dvyfu, with platform registration timestamp 30 October 2026 at 01:06:12 UTC. No result is presented here. The study concerns observable signals and citation samples; those signals cannot establish why an engine selected a page.
Study 2, publishers cited for B2B software questions: the plan is registered at OSF vczkt, 30 October 2026 at 01:32:03 UTC. Its registered secondary analysis concerns the explicit citation arrays in the September archive. The published protocol fixes the units and the treatment of repeated links, controls and uncertain publisher classifications.
Study 3, persistence of absence: the prospective plan is registered at OSF mkj9v, 30 October 2026 at 01:12:44 UTC. Its persistence analysis requires a further eligible release under comparable conditions. The existing August and September standings are dated observations; they are not a measured transition.
Registration preserves a plan. It does not mean a result exists or that a study has passed peer review. Completed descriptive tables from an existing release are identified separately from these registered studies.
Take a number with its boundary
The quotable numbers page gives the observation, source location and wording that can travel together. Its companion, numbers we could not verify, retains claims whose sources are missing, whose units changed in retelling or whose original papers do not support the advertised inference.
Some rejected claims have useful ancestors. A historical Google Home study measured the length of spoken answers, for example; it did not establish the length of the user's voice query. Recovering the original does not make its observation current. Both the date and the measured object still matter.
The Absence Manual supplies the longer explanation of measurement noise and engine divergence. The answer library addresses individual buyer questions. This section supplies the source reviews, definitions and evidence behind those practical decisions.
One inconvenience remains deliberate. When a source's table and prose disagree, the uncertainty stays visible. A useful page may end with an unresolved question, particularly when the alternative would be a neat claim that the underlying record cannot carry.
What our own data shows
The September release is a fixed set of captured answers, not a survey of every buyer or every possible question. Its versioned primary record and the derived tables linked from the individual insight pages keep the observation base visible. We have no measurement on this point: publishing this research section itself has not yet been shown to improve Broadcastwell's AI citation or search traffic.
Sources
- Lewandowski, D., Sünkler, S., & Yagci, N. (2021). The influence of search engine optimization on Google's results: A multi-dimensional approach for detecting SEO. In WebSci '21 (pp. 12 to 20). ACM. doi:10.1145/3447535.3462479 . Accessible original Verified 30 October 2026.
- Broadcastwell. (2026). Absence Index, release 2026-09 [Data set]. Zenodo. Release JSON, answer JSONL and README. https://doi.org/10.5281/zenodo.22907695 Verified 30 October 2026.
- Broadcastwell. (2026). Who do AI engines cite for B2B software questions? [Registration]. OSF. Registered 30 October 2026, 01:32:03 UTC. https://doi.org/10.17605/OSF.IO/VCZKT Verified 30 October 2026.
- Broadcastwell. (2026). Does absence persist from one release to the next? [Registration]. OSF. Registered 30 October 2026, 01:12:44 UTC. https://doi.org/10.17605/OSF.IO/MKJ9V Verified 30 October 2026.
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Ledford, J. L. (2009). SEO: Search engine optimization bible (2nd ed.). Wiley. Jill Whalen interview, printed pp. 447 to 449 (PDF pp. 469 to 471). ISBN 978-0-470-45264-6. https://books.google.com/books?vid=ISBN9780470452646 Verified 30 October 2026.
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Broadcastwell. (2026). Do AI engines cite optimized pages? [Registration]. OSF. Platform registration timestamp 30 October 2026, 01:06:12 UTC. https://doi.org/10.17605/OSF.IO/DVYFU Verified 30 October 2026.
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Broadcastwell. (2026). Supplied search-research collection: 21-document identity inventory [Data set]. Original filenames, PDF page counts and SHA256 identities; duplicate editions retained as physical files, not independent studies. Collection inventory. Verified 30 October 2026.
Cite this page
Broadcastwell research team. (2026, October 30). What the research says about search and AI answers. Broadcastwell. https://docs.broadcastwell.com/research/ Published 30 October 2026; updated 30 October 2026.
@online{broadcastwell2026research1,
author = {{Broadcastwell research team}},
title = {What the research says about search and AI answers},
year = {2026},
date = {2026-10-30},
url = {https://docs.broadcastwell.com/research/},
urldate = {2026-10-30},
note = {Published 2026-10-30; updated 2026-10-30}
}
Prepared by the Broadcastwell research team. Lead: Priya Nair, management consultant.
Sources checked 30 October 2026. Independent check: 30 October 2026. This page has not been peer reviewed.
Last updated: 30 October 2026. Next review: 30 January 2027.