SourceCited / Question dataset
Original data · First-party
We harvested and released the real demand curve for AI-search optimization — 3,307 distinct questions from three engines autocomplete, with counts and a CSV you can cite.
This is original, first-party data: 3,307 distinct questions about AI search optimization, pulled from Google, Bing and DuckDuckGo autocomplete across 764 seeds (July 2026), with appearance counts and cross-engine coverage. The loudest demand is tooling/measurement and how-to-cite. Free to reuse with attribution — download the CSV below.
This is a first-party dataset: 3,307 distinct questions people actually type about AI search optimization, harvested from the autocomplete suggestions of Google, Bing and DuckDuckGo across 764 seed queries in July 2026. Each question carries how many seed-and-engine combinations surfaced it (a rough demand weight) and how many of the three engines suggested it. Total suggestion appearances: 15,463. We release it in full, with a downloadable CSV, because nobody else publishes autocomplete-level demand data for this vertical — and being the origin of a number is how you get cited.
| Measure | Value |
|---|---|
| Distinct questions harvested | 3,307 |
| Seed queries expanded | 764 |
| Engines sampled | 3 (Google, Bing, DuckDuckGo) |
| Total suggestion appearances | 15,463 |
| Questions suggested by all 3 engines | 252 (cross-engine consensus demand) |
| Questions suggested by ≥2 engines | 1,235 |
| Questions about citing AI / citing sources | 63 distinct, 1,104 appearances |
The single loudest signal is tooling and measurement — "ai search optimization tools" alone surfaced 173 times — followed immediately by a wall of how-to-cite questions, which says the audience is split between marketers trying to get cited and researchers trying to cite AI correctly. Both land on this vertical.
Grouped into eleven themes, ranked by total suggestion appearances — the map of where attention actually sits in AI-search discourse right now.
| Cluster | Distinct questions | Appearances |
|---|---|---|
| ChatGPT | 659 | 3179 |
| GEO | 426 | 2593 |
| General AI-search | 550 | 2462 |
| AEO | 580 | 2306 |
| Google AI Overviews/AI Mode | 287 | 1634 |
| Tools/tracking | 290 | 1035 |
| How-to/checklist | 168 | 943 |
| Perplexity | 102 | 454 |
| Definitions/what-is | 112 | 452 |
| Vertical (ecom/saas/local) | 87 | 246 |
| llms.txt / technical | 46 | 159 |
Ranked by appearances across the 764 seeds and three engines. Eng = how many of the three engines suggested it (3 = strongest cross-engine consensus). The raw demand curve — the questions worth answering first.
| # | Question | Appearances | Eng |
|---|---|---|---|
| 1 | ai search optimization tools | 3 | 173 |
| 2 | how to get chatgpt to cite sources | 2 | 123 |
| 3 | how to cite information from chatgpt | 2 | 121 |
| 4 | ai search optimization expert | 3 | 115 |
| 5 | how to in text cite chatgpt | 2 | 114 |
| 6 | how to optimize for ai search | 3 | 111 |
| 7 | answer engine optimization aeo | 3 | 108 |
| 8 | how to optimise for ai search | 3 | 107 |
| 9 | what is ai search optimization called | 3 | 105 |
| 10 | how to optimise website for ai search | 2 | 105 |
| 11 | how to rank in google ai overviews | 3 | 104 |
| 12 | rank in ai search results | 2 | 104 |
| 13 | how to rank in ai search | 2 | 103 |
| 14 | answer engine optimization services | 3 | 102 |
| 15 | optimize content for ai search | 3 | 101 |
| 16 | how to cite wh chatgpt | 2 | 100 |
| 17 | how to cite chatgpt as a source | 2 | 94 |
| 18 | how to cite chatgpt as a reference | 2 | 94 |
| 19 | how to cite chatgpt | 2 | 91 |
| 20 | answer engine optimization for law firms | 3 | 80 |
| 21 | answer engine optimization certification | 3 | 77 |
| 22 | answer engine optimization definition | 3 | 74 |
| 23 | ai search engine optimisation | 1 | 73 |
| 24 | ai search engine optimization | 3 | 72 |
| 25 | rank all ai models | 2 | 69 |
| 26 | define answer engine optimization | 2 | 68 |
| 27 | best ai overviews rank tracking tools | 2 | 68 |
| 28 | ai overview rank tracking | 2 | 68 |
| 29 | what is answer engine optimization | 3 | 63 |
| 30 | geo vs seo marketing | 3 | 63 |
| 31 | ranking in ai search | 2 | 63 |
| 32 | answer engine optimization los angeles | 3 | 62 |
| 33 | what is ai search optimisation called | 3 | 62 |
| 34 | geo vs seo strategy | 3 | 62 |
| 35 | generative engine optimization pdf | 3 | 59 |
| 36 | ai search optimization | 3 | 59 |
| 37 | ai search optimization term | 3 | 59 |
| 38 | generative engine optimization strategy | 3 | 58 |
| 39 | how to rank in ai overviews | 3 | 57 |
| 40 | ai search optimization roadmap | 2 | 56 |
| 41 | ai search optimization swansea | 2 | 56 |
| 42 | ai search optimization for businesses | 2 | 56 |
| 43 | ai search optimization certification surfer | 2 | 56 |
| 44 | ai overviews rank tracking free | 2 | 56 |
| 45 | geo vs seo definition | 2 | 56 |
| 46 | answer engine optimization | 3 | 54 |
| 47 | ai search visibility optimization tool | 2 | 54 |
| 48 | answer engine optimization in nigeria | 2 | 53 |
| 49 | chatgpt citation and reference finder | 2 | 52 |
| 50 | answer engine optimization tips | 3 | 51 |
How it was built: 764 seed phrases spanning the AI-search vocabulary were expanded through the public autocomplete of Google, Bing and DuckDuckGo, deduplicated, filtered to on-topic questions, and clustered. Appearances counts how many seed×engine combinations surfaced a suggestion — a proxy for relative demand, not a search volume. What it is not: not keyword-planner volume, not clickstream; and autocomplete is itself shaped by past popularity, so treat it as a directional demand signal, strongest where all three engines agree. Harvested July 2026; autocomplete drifts, so we plan to refresh quarterly and date each release.
Free to reuse with attribution (CC BY 4.0). Cite as: SourceCited, "What People Ask About AI Search: a 3,307-question autocomplete dataset," 2026, https://sourcecited.com/data.html. If you republish a figure, a link back is appreciated and helps others verify it.
By this 3,307-question autocomplete dataset, the two loudest themes are tooling and measurement ("ai search optimization tools" led with 173 appearances) and how to cite AI sources correctly. Demand splits between marketers trying to get cited and researchers trying to cite AI.
By expanding 764 seed phrases through the public autocomplete of Google, Bing and DuckDuckGo in July 2026, then deduplicating, filtering to on-topic questions, and clustering. Appearance counts proxy relative demand, strongest where all three engines agree.
Yes — it is released under CC BY 4.0. Reuse or republish any figure with attribution to SourceCited and a link back to the dataset page so others can verify it.