Most niche-site builders pick a keyword, check a volume number, and start writing. Before building my latest project, I tried something cheaper and more honest: I scripted Google's free Autocomplete API and harvested every real query pattern around one product niche — car laptop desks.
The method (free, ~300 requests)
Google's suggest endpoint (suggestqueries.google.com/complete/search) returns what real users type. For each seed term (car laptop desk, car laptop stand, laptop desk for car...), I appended a–z and 0–9 suffixes and collected everything — 296 queries later I had 636 unique search phrases, each a real thing people type.
Simple scoring: +3 if it contains a year (fresh demand), +2 for question words (content opportunity), +1 for 4+ words (long tail).
What surprised me
- The top query wasn't about products at all. "Is it legal to have a laptop mounted in your car" appeared across 17 different seed expansions. Nobody selling desks answers it — that's a content gap you could drive a truck through.
- "3D print" showed up 12 times. A meaningful slice of this market wants to print a stand, not buy one. A product-only site would never serve them; a guide on materials that survive hot cars (PLA softens at dashboard temperatures) does.
- Intent clusters map to site architecture. Position words (passenger seat / back seat / steering wheel / cup holder) and type words (stand / table / tray / mount) each had full suggest trees — so the site's URL structure became exactly those clusters. The keyword data designed the sitemap.
- Navigational noise is a filter, not a target. "near me", "amazon", "officeworks" queries tell you what NOT to build pages for.
The result
The data became CarLaptopDesk.com — position pages, type pages, and guides answering the legality/heat/DIY questions the autocomplete surfaced. Whether it ranks is now Google's call, but at least every page maps to a query someone actually typed.
Takeaway: before trusting a paid tool's volume estimates, spend 20 minutes with the autocomplete API. It won't give you numbers, but it gives you the shape of demand — and shape is what decides your information architecture.
Happy to share the harvesting script if anyone wants it — it's ~80 lines of Python with rate limiting.
Top comments (1)
Appending a-z to a seed only walks the tail. Prefix expansion does a different job: run the alphabet in front of the seed, plus inserts like "why", "vs", "diy", and you get a separate tree full of comparison and objection intent. Your legality winner probably sits in there under "is it" variants, no new seed list required.
The other thing suggest won't tell you is who is asking. A phrase appearing across 17 seed expansions means it's being typed into forums this week too, so I'd paste "is it legal to have a laptop mounted in your car" into Reddit search before writing that page. Shipping our own product, that pass is where the real objection wording came from, autocomplete only gave the topic.