Google Maps Optimization
Google Maps Optimization Case Study: therankingstore.com
therankingstore.com is our own site, run by the same owner as The Ranking Factory, so this is not a client engagement. That made it a clean place to test the question underneath Google Maps optimization work: when someone asks an AI engine the things your market asks, does the engine cite your pages? From Aug 15, 2026, The Ranking Factory asked AI engines the questions people ask about the site’s subjects — rank tracking and ranking software, local and digital marketing, backlink and link building services, Google penalties, SEO pricing and ranking timelines — and listed every subject it found missing from the site as a gap to close.
What we did, and why
We ran The Ranking Factory, our own software, on therankingstore.com. Between Aug 28 and Oct 21, 2026, it wrote and published 112 pages on the site, one subject per page, and submitted every one of them to IndexNow. The pages covered rank tracking and ranking software, local and digital marketing, link building, Google penalties, SEO pricing and ranking timelines — the subjects the gap list had flagged as missing.
On Oct 9 we added our crawler log to the site through our WordPress plugin, so we could see which crawlers fetched each page. Roughly once a week from Aug 15 to Oct 21 the AI engines were asked the site’s questions again, and each answer’s sources were checked for the site’s pages. The point was to measure citation, not to assume it.
How it turned out
By Oct 23, 2026, 75 of the 112 pages — 67% — had been cited by at least one AI answer. The first was cited on Sep 4. By Oct 21, 34 of the pages had been cited in answer to a question that did not name The Ranking Store, meaning the pages were being surfaced on the strength of their subject matter rather than the brand name.
The citations were spread across engines: Perplexity Sonar cited 66 of the pages, DeepSeek 19, Google Gemini 14 and OpenAI’s GPT-5.6 Luna 13, and Google AI Overviews were the first to cite 5. Between Oct 9 and Oct 21 the crawler log recorded a fetch of every one of the 112 pages, 104 of them by a crawler whose identity was verified — so the pages were not merely published, they were being retrieved.
What the record shows
The sequence is straightforward and repeatable: build a gap list from the questions the market actually asks, publish one page per subject, submit each page to IndexNow as it goes live, and re-ask the engines on a regular cadence so each answer’s sources can be checked. Running it on our own site means the result is documented end to end, from the missing subjects identified on Aug 15 to the crawler fetches and citations logged by late October.
Sources and supporting material
Further reading:
- Reference: Was Unternehmen über Google-Sichtbarkeit und bezahlte Platzierungen wissen sollten
- Reference: Map Pack Optimization
- Case study: Map Pack Optimization
- Case study: Map Pack Optimization
- Case study: google page rank checker download
- Case study: google ranking kaufen
- Case study: google my business listing optimization training
