GEO · generative engine optimization
GEO is the work of making models mention your brand and cite your site when a buyer asks ChatGPT, Gemini or Perplexity for a supplier. We measure what they say, fix the pages and sources that decide it, then measure again.
Enter a domain, like example.com.
Free: 1 Perplexity sample × 1 tracked question · no signup · report in about 90 seconds
Why GEO, why now
Purchase research moved from ten blue links to one paragraph. That paragraph names a handful of brands, and it is the answer your buyer acts on.
01
Decisions start in a chat, not in a results page
Engineers and buyers open with a question like “who is the best steel structure warehouse manufacturer”. The model answers with three to eight names, and those names are the shortlist.
02
There is no page two in an AI answer
One answer, a few brands. Every competitor named holds a slot you do not, and every one of those conversations is an inquiry you never see in analytics.
03
A score your board can read
A 0-100 visibility score, a history, and a like-for-like re-measure against the same questions. No screenshots of vibes, no invented lift.
How we measure
Same domain, same week, same questions. Nothing is inferred from rankings alone, and no number is shown without the answer it came from.
Buyer-intent prompts from your category, the phrases your buyers actually type, plus the comparison prompts that decide shortlists.
Day 0Perplexity, Gemini and DeepSeek are asked directly, in repeated rounds. Every answer and its source list is stored verbatim.
3 enginesA 0-100 score across five weighted dimensions, plus share of voice against the brands named beside you.
0-100The domains cited instead of you, ranked by frequency, and the fixes that move each dimension.
Fix listThe 0-100 score
Weights are published so you can recompute any score from the transcript. Sentiment and description quality no longer count toward the score; they appear in the report as AI-assisted observations only.
| Dimension | Weight | What it measures |
|---|---|---|
| Brand presence | 35 pts | Case-insensitive match: does your brand appear in the answer at all |
| Website cited | 25 pts | Cited domains compared with your domain, subdomains included |
| Source diversity | 15 pts | Distinct external domains; three or more scores full marks |
| Position | 10 pts | Character offset of the first mention; earlier scores higher |
| Fact consistency | 15 pts | Binary verdict against your fact library; “no info” is excluded from the denominator |
Deliverables
Delivered as a PDF and a live dashboard. Every number links back to the answer that produced it.
01
One 0-100 score per question, per engine, with the five dimensions broken out.
02
Perplexity, Gemini and DeepSeek side by side, so you know where the gap hurts most.
03
The domains the models quote instead of you, ranked by how often they appear.
04
Full transcripts with the sentence where you appear and the sources attached to it.
05
Re-measured on the same questions; a trend is only discussed after six weeks of data.
06
An indexable URL you can send to a client or a colleague without a login.
See a live one →Two halves, one loop
Buy them separately or together. Most teams start with the baseline, then decide how much content they want to publish.
01 · monitoring
Real AI calls on your target questions, run on a schedule. The report includes the transcript and the cited sources, not just a grade.
02 · seeding
Ten Q&A pairs written for the way models answer, shipped with the structured data and page HTML that make them liftable.
Nothing in seeded content is invented: every fact, certificate and selling point is confirmed by you before publishing.
Measured result
Steel structure · “steel structure warehouse manufacturer”
Real Perplexity API answers, same rules version
No demo injection. The before and after are two runs of the same question against the same sampling rules, and both transcripts ship with the report.
We ran the whole test on ourselves first: crawl access 100 / 100, homepage 97.6 / 100 under rules version geo_page_v1, and an AI mention rate of 0% at baseline across three Perplexity sampling rounds. The gap between “we can measure it” and “we can move it” is the product.
Baseline across engines, technical check, competitor comparison.
Content live, plus external sources: directories, Q&A, press.
Automatic re-measure against the baseline, Wilson intervals.
Long-tail expansion, competitor countering, refresh cycle.
First changes usually appear in 4-8 weeks and stabilize in 8-12. About half of AI citations come from content newer than 13 weeks, so this is operation, not a one-off. If there is no gain by the week-six re-measure, one extra round is free.
GEO vs SEO
A page-one rank does not put you in the answer. The two channels share the work of being findable, but they are scored on different things.
| SEO | GEO | |
|---|---|---|
| Goal | Rank a page for a query | Be named in the answer, with your site cited |
| Surface | Results page, ten links, page two exists | One answer, three to eight brands, no page two |
| Decides it | Crawlability, links, intent match | Indexable English sources, structured data, entity consistency |
| Scored by | Rank, traffic, impressions | 0-100: presence, citation, diversity, position, facts |
| Relationship | A rank-one page can still be left out of the answer | GEO covers the Q&A channel that now precedes the click |
They complement each other. The question is not which one to drop, it is which one your buyers meet first.
Where citations come from
Gemini leans on the Google index and Knowledge Graph, ChatGPT on review sites, Perplexity on Reddit. Placement follows each engine's mechanics instead of one-size-fits-all.
FAQPage JSON-LD lets a model lift your answer directly; Gemini local search cites your site most.
A Knowledge Graph source. Gemini cites the business entry for “find a supplier” queries.
Answer-shaped, and among the most-cited sources, with data partnerships behind them.
Media coverage accounts for roughly 84% of AI citations in industry tracking. Paid distribution.
Alibaba, ThomasNet and category directories: what models cite for supplier searches.
The entity profiles models read for “what does this company do” questions.
Per engine, the weight sits in different places: for Gemini, schema.org markup, the Knowledge Graph, YouTube transcripts and Google News placement; for ChatGPT, review sites, directories and comparison pages; for Perplexity, Reddit and fresh editorial. One plan, laid out per engine instead of one-size-fits-all.
No one can guarantee a citation, and a vendor who promises one is selling something else. We also refuse the shortcuts: no hidden instructions inside content, no zombie Reddit accounts, no press farms. Models defend against them and they backfire. What we do is place consistent facts in the sources each engine reads, iterate, and prove movement with a re-measure.
Questions
SEO optimizes Google rankings; GEO optimizes brand presence in AI answers from Perplexity, Gemini and DeepSeek. AI answers usually cite only a few sources, so a high SEO rank does not mean the model mentions you. They complement each other: GEO targets the AI Q&A channel that now runs before the click.
Yes. Monitoring asks real AI APIs your target questions and ships the answer transcript and cited sources with the report. Every fact, selling point and certificate in seeded content is confirmed by you first; we do not fabricate brand facts.
Content is usually indexed and cited within one to three weeks of publishing. One automatic re-measure follows on day 14 after delivery, then a like-for-like trend comparison in week six; trends are only discussed after at least six weeks. Results are judged on mention rate, website citation rate and fact accuracy. We do not promise a specific score increase.
Seeding copy is generated in English for overseas buyer scenarios. You review it online and add the real selling points; nothing is published until you confirm it.
Yes. Monitoring is a monthly subscription, and seeding is bought per run. See your baseline first, then decide. Both can be activated at any time.
Start with the free audit
Three engines, one tracked question, a 0-100 baseline and the full transcript. No signup, and the result is public so you can share it.