We asked four AI engines about 465 Danish companies: the technology determines whether you’re quoted — not whether you’re recommended

We asked four AI engines 576 questions about 465 Danish companies. Technical configuration is a strong predictor of whether your site will be used as a source — but says nothing about whether your company will be recommended. Two outcomes, two answers.

We asked four AI engines 576 questions about 465 Danish companies across three sectors — firms that can be found via a Google search in 12 Danish towns and cities. The results were split in two: technical setup is a strong predictor of whether your site is used as a SOURCE (p=0.000). It predicts nothing about whether your company is RECOMMENDED (p=0.988).

These are two questions that are usually lumped together as one. We did this ourselves when we started analysing the data — and initially concluded that ‘technical aspects don’t matter’, which was incorrect. They do matter. Just not in the way you might think.

How we measured it

We didn’t ask the search engines about individual companies. We asked the questions a typical customer would ask — “Which plumbing firms can you recommend in Aalborg?” — in 12 Danish towns, using four question variants, for ChatGPT, Gemini, Claude and Perplexity, with web search enabled. We then measured which companies in the sector the search engines themselves brought up.

Two factors were counted separately: whether the company was mentioned by name in the answer, and whether its domain was cited as a source.

How many were mentioned?

Industry	Measurable	Mentioned by name	Cited as a source
Lawyers	106	60 (57%)	59 (50%)
Plumbing	162	62 (38 per cent)	90 (45%)
Accountants & bookkeepers	127	41 (32%)	46 (31 %)
Total	395	163 (41 per cent)	195 (42 %)

Around four in ten were mentioned by at least one influencer. The variation between sectors is striking: a solicitor was almost twice as likely to be mentioned as an accountant.

The technical score did not predict who was recommended

We already have a technical score for each site — readable text without JavaScript, llms.txt, robots.txt access for AI crawlers, structured data, H1 and meta description. If that score determined who the AI recommended, the sites mentioned should have scored higher.

Industry	Score, mentioned	Score, not mentioned	p-value
Plumbing	77.9	78.8	0.66
Accountants	76.5	72.7	0.22
Solicitors	70.8	67.3	0.30
Total	74.9	74.3	0.70

None of the sectors comes close to reaching statistical significance. llms.txt even went the wrong way in two out of three cases: amongst plumbing firms, 6% of those mentioned had the file, compared with 13% of those not mentioned; amongst accountants, 10% compared with 16%.

The obvious objection is that there isn’t enough variation: 41 per cent of the sites scanned have exactly the same score, because they already have the basics in place. So we divided the field into score bands and measured the mention rate in each:

Technical score	Companies	Mentioned by AI
Below 60	59	36%
60–74	104	43%
75–84	37	32%
85–100	195	44 %

The curve is flat. There are 101 companies scoring below 70 points in the data, so there is a spread — and they are mentioned roughly as often as those at the top. A lack of variance therefore does not explain this on its own.

This does not mean that the technique is irrelevant. It means that it resembles a ticket to entry rather than a competitive advantage: necessary to be considered, but not the deciding factor amongst those who are already in. Our data cannot tell us what the situation is like for the sites below the bottom line — by definition, they are not visible in search results and are therefore not included.

But technical setup determines something else — and that’s important

When we broke down the two outcomes, the picture became quite different. Technical setup is a strong predictor of whether your site is used as a SOURCE. It predicts nothing about whether your business is RECOMMENDED.

Outcome	Technical score	JSON-LD	p-value
Cited as a source	77.9 versus 72.7	68% versus 57%	0.000
Mentioned as a recommendation	74.9 versus 74.9	63% versus 61%	0.988

These are two different questions, and they each have their own answer:

• “Does AI use my site as a source?” — here, the technology matters a great deal. The difference is 5.2 points and highly significant. Structured data and readable HTML make your site usable for a model.
• “Does AI recommend my business?” — here, the technical aspects have no measurable impact. The score is identical on both sides of the dividing line.

So it is possible to be the page that AI reads and refers to, without being the business that AI highlights. The technical work is not wasted — it simply leads to a different outcome than most people expect.

However, one thing does not hold true: content length. Cited pages have an average of 1,083 words compared to 895 for non-cited ones, but the difference is not statistically significant (p=0.32). We mention this because ‘write longer texts’ is a common piece of advice — our data does not support it.

What the AI actually cited

The search engines referred to 4,034 sources spread across 494 domains. The distribution surprised us:

• 61 per cent were the companies’ own websites (2,457 citations).
• 16% were directories and review sites (630).
• 23% were other third parties — industry portals, media outlets, other companies’ websites (1,237).

So, companies’ own websites dominate. It’s worth bearing this in mind if you’re about to conclude that AI only looks at mentions elsewhere — it doesn’t.

The six sources that appeared consistently across all sectors

Out of 494 domains, only six were cited in all three sectors. All six are directories or registers.

Domain	Citations	What it is
krak.dk	103	Business directory
findformig.dk	78	Review directory
Trustpilot	73	Review platform
cvrexplorer.com	23	CVR register mirror
LinkedIn	22	Company profiles
degulesider.dk	17	Business directory

Everything else was sector-specific. This is the most actionable observation in the dataset: whether you’re a solicitor, an accountant or a plumber, the search engines drew on the same small set of directories — and a directory profile is something you can sort out in an afternoon.

Be aware of what this does not tell us. We have measured which sources the AI cited — not whether a profile in those directories gets you mentioned. To do that, we’d need to track the same companies over time and see whether changes to the directories make a difference. We haven’t carried out that measurement yet.

What we cannot answer

We can say with reasonable certainty what does not determine visibility: the technical score, amongst sites that are already visible in search results. We cannot say what does.

We haven’t measured the number of reviews, age, company size or marketing budget. Any explanation as to why lawyers perform better than accountants would be a guess on our part. It’s a measurement we’d like to carry out — and we’ll publish the results, whatever they show.

The practical implication is the same regardless of the explanation: you cannot calculate whether AI will mention your business. A technical checklist can tell you whether you’ve got the basics in place — but not whether the search engines will actually rank you highly when a customer searches. These are two different questions, and only one can be answered through measurement.

May I quote the figures?

Yes. Please cite “Geoa, July 2026, n=465 companies, 576 AI responses” and feel free to link to this page. We update the dataset and note the date of each update, so that older citations can be traced back to the version from which they were taken.