Answer Engine Optimization for B2B / A Danish Lead Co company
Research

What AI Engines Cite Changes Completely By Industry

We ran the same measurement for ten companies in ten different industries, 924 tracked questions put to five answer engines. Directories and marketplaces were cited in 320 of 709 answers for a coworking operator, 45.1%, and in 4 of 245 answers for a financial data vendor, 1.6%. Same method, same engines, same week.

Most published AI citation statistics quote one number for the whole web. This page is the argument against that. Ten latest measurement runs, one per company, taken between 17 and 22 September 2026, produced 4,570 answers and 18,201 cited links across 6,304 distinct domains. One thing held everywhere: vendor and agency websites were the most cited kind in all ten industries, within a narrow band of 178 of 245 answers, 72.7%, to 392 of 454 answers, 86.3%. Everything underneath that moved enormously. Documentation and standards were cited in 312 of 500 answers, 62.4%, for a software supply chain security company, and in 1 of 709 answers, 0.1%, for the coworking operator. That is the same source kind, measured the same way, 442 times apart. If you are deciding where to spend to be cited, the industry you are in changes the answer more than anything else on this page.

Vendor sites vary 1.2 times across ten industries. Documentation and standards vary 442 times.

01 / Method

Exactly what was measured

Every number on this page is computed in SQL against ten stored snapshots. The SQL is printed in full at the end of the page source so anyone can reproduce it.

ParameterValue
Runs10, the latest published run for each of 10 accounts, one account per industry
Run dates17 to 22 September 2026
Questions924 in total, each account has its own tracked set of 49 to 150 questions
Answer engines5: ChatGPT, Gemini, Microsoft Copilot, Google AI Mode, Google AI Overviews
Engine cells4,619. One question on one engine. 924 questions times 5 engines is 4,620, and one cell was absent from one snapshot
Answers excluded as no-answer49 of 4,619, 1.1%. An engine that returned no answer text cannot have cited anything
Answers counted4,570. This is the denominator for every share on this page
Answers with no source list790 of 4,570, 17.3%. Kept in the denominator, reported in section 06
Cited links counted18,201
Link exclusions236 links removed: Google result-viewer links of the form google.com/searchviewer, which point at the engine's own result panel rather than at a source. 205 were in the coworking run and 31 in the staffing run. The same rule removed nothing from the single-account report
Distinct domains6,304, counted at the registrable domain so subdomains roll up
Unit of the sharean answer, meaning one question on one engine. An answer counts once for a source kind however many links of that kind it cited

Six of the ten accounts are named with permission: Westhive, CodeCargo, Cruitfly, DealSource Systems, Danish Lead Co and our own account. The other four are shown as an industry label only. No account's own visibility score, pricing or commercial volumes appear anywhere on this page.

Each cited URL is reduced to a registrable domain and assigned to exactly one of seven source kinds by an explicit named rule set, printed in the SQL at the end of the page source. Vendor or agency site is the residual, which means it also contains each measured company's own website and its direct competitors. This is a companion to the single-account citation report, which takes one of these ten runs apart domain by domain.

02 / The spread

Source mix by industry

Share of that industry's answers citing at least one source of each kind. Rows are ordered by the directories and marketplaces share. An answer can cite several kinds, so rows do not sum to 100%.

IndustryVendor or agency siteDirectories and marketplacesDocs and standardsGovernment and regulatorSocial and videoCommunityNews and media
Coworking and flexible office space
Westhive
524 of 709
73.9%
320 of 709
45.1%
1 of 709
0.1%
8 of 709
1.1%
6 of 709
0.8%
3 of 709
0.4%
0 of 709
0.0%
B2B outbound and lead generation
Danish Lead Co
441 of 590
74.7%
60 of 590
10.2%
8 of 590
1.4%
8 of 590
1.4%
74 of 590
12.5%
42 of 590
7.1%
3 of 590
0.5%
Healthcare benefits, employer buyers
account not named
223 of 270
82.6%
27 of 270
10.0%
30 of 270
11.1%
63 of 270
23.3%
12 of 270
4.4%
8 of 270
3.0%
1 of 270
0.4%
Private equity and M&A deal sourcing
DealSource Systems
424 of 499
85.0%
47 of 499
9.4%
21 of 499
4.2%
12 of 499
2.4%
51 of 499
10.2%
19 of 499
3.8%
11 of 499
2.2%
Ecommerce development
account not named
408 of 539
75.7%
50 of 539
9.3%
13 of 539
2.4%
2 of 539
0.4%
70 of 539
13.0%
53 of 539
9.8%
8 of 539
1.5%
Construction and industrial staffing
Cruitfly
392 of 454
86.3%
39 of 454
8.6%
6 of 454
1.3%
49 of 454
10.8%
21 of 454
4.6%
15 of 454
3.3%
1 of 454
0.2%
Healthcare benefits, clinic buyers
account not named
218 of 264
82.6%
14 of 264
5.3%
24 of 264
9.1%
26 of 264
9.8%
18 of 264
6.8%
7 of 264
2.7%
0 of 264
0.0%
Software supply chain security
CodeCargo
401 of 500
80.2%
13 of 500
2.6%
312 of 500
62.4%
6 of 500
1.2%
84 of 500
16.8%
62 of 500
12.4%
0 of 500
0.0%
Answer engine optimization
SourceRank AI
367 of 500
73.4%
10 of 500
2.0%
39 of 500
7.8%
4 of 500
0.8%
67 of 500
13.4%
43 of 500
8.6%
20 of 500
4.0%
Financial market data and news
account not named
178 of 245
72.7%
4 of 245
1.6%
11 of 245
4.5%
18 of 245
7.3%
27 of 245
11.0%
17 of 245
6.9%
92 of 245
37.6%

Two of the ten accounts sit in the same broad healthcare category with different buyers, an employer-side set of questions and a clinic-side set, which is why two rows look related. They are separate accounts with separate question sets and separate runs.

Read down the directories column: 45.1%, 10.2%, 10.0%, 9.4%, 9.3%, 8.6%, 5.3%, 2.6%, 2.0%, 1.6%. Read down the documentation column and the order is almost reversed. There is no single AI citation profile to optimise against. There are at least ten.

03 / The second source

Vendor sites lead everywhere, so what comes second is the whole story

Vendor and agency websites were the most cited kind in all ten industries. The column that matters is the next one.

IndustryVendor or agency sitesLeading non-vendor kindIts shareRunner up
Software supply chain security
CodeCargo
401 of 500, 80.2%Docs and standards312 of 500, 62.4%Social and video, 84 of 500, 16.8%
Coworking and flexible office space
Westhive
524 of 709, 73.9%Directories and marketplaces320 of 709, 45.1%Government and regulator, 8 of 709, 1.1%
Financial market data and news
account not named
178 of 245, 72.7%News and media92 of 245, 37.6%Social and video, 27 of 245, 11.0%
Healthcare benefits, employer buyers
account not named
223 of 270, 82.6%Government and regulator63 of 270, 23.3%Docs and standards, 30 of 270, 11.1%
Answer engine optimization
SourceRank AI
367 of 500, 73.4%Social and video67 of 500, 13.4%Community, 43 of 500, 8.6%
Ecommerce development
account not named
408 of 539, 75.7%Social and video70 of 539, 13.0%Community, 53 of 539, 9.8%
B2B outbound and lead generation
Danish Lead Co
441 of 590, 74.7%Social and video74 of 590, 12.5%Directories and marketplaces, 60 of 590, 10.2%
Construction and industrial staffing
Cruitfly
392 of 454, 86.3%Government and regulator49 of 454, 10.8%Directories and marketplaces, 39 of 454, 8.6%
Private equity and M&A deal sourcing
DealSource Systems
424 of 499, 85.0%Social and video51 of 499, 10.2%Directories and marketplaces, 47 of 499, 9.4%
Healthcare benefits, clinic buyers
account not named
218 of 264, 82.6%Government and regulator26 of 264, 9.8%Docs and standards, 24 of 264, 9.1%

A pattern falls out of that column. In a local, physical, bookable category the engine reaches for a marketplace. In a technical category it reaches for documentation and specifications. In a market data category it reaches for the news. In regulated categories, healthcare benefits and industrial staffing, it reaches for a government or regulator site. And in the professional services categories, lead generation, deal sourcing, ecommerce development and answer engine optimization, it reaches for social and video, which in practice means LinkedIn, YouTube and Reddit. Four different industries, four different answers to the question every buyer of this service asks first.

04 / The widest gaps

How far each source kind moves between industries

For each kind, the industry where it was cited most, the industry where it was cited least, and the ratio between them.

Source kindAll 10 industriesHighest industryLowest industryGap
Docs and standards465 of 4,570, 10.2%Software supply chain security
312 of 500, 62.4%
Coworking and flexible office space
1 of 709, 0.1%
442 times
Directories and marketplaces584 of 4,570, 12.8%Coworking and flexible office space
320 of 709, 45.1%
Financial market data and news
4 of 245, 1.6%
28 times
News and media136 of 4,570, 3.0%Financial market data and news
92 of 245, 37.6%
Healthcare benefits, clinic buyers
0 of 264, 0.0%
no floor: zero answers in the lowest vertical
Government and regulator196 of 4,570, 4.3%Healthcare benefits, employer buyers
63 of 270, 23.3%
Ecommerce development
2 of 539, 0.4%
63 times
Social and video430 of 4,570, 9.4%Software supply chain security
84 of 500, 16.8%
Coworking and flexible office space
6 of 709, 0.8%
20 times
Vendor or agency site3,576 of 4,570, 78.2%Construction and industrial staffing
392 of 454, 86.3%
Financial market data and news
178 of 245, 72.7%
1.2 times
Community269 of 4,570, 5.9%Software supply chain security
62 of 500, 12.4%
Coworking and flexible office space
3 of 709, 0.4%
29 times

News and media has no ratio because three industries, coworking, software supply chain security and clinic-side healthcare benefits, recorded 0 answers citing a news source out of 709, 500 and 264 answers respectively.

The aggregate column is the number a vendor would publish as the industry benchmark. Directories and marketplaces were cited in 584 of 4,570 answers, 12.8%. That number is true and almost useless: it is nine times too low for the coworking operator and eight times too high for the financial data vendor. Any single AI citation statistic quoted without an industry attached is describing a company that does not exist.

05 / By engine

The engines disagree with each other more than the industries do

All ten industries pooled, split by engine. Share of that engine's answers citing each kind.

EngineAnswersNo source listVendor or agency siteDirectories and marketplacesDocs and standardsGovernment and regulatorSocial and videoCommunityNews and media
Microsoft Copilot9240, 0.0%922 of 924
99.8%
205 of 924
22.2%
104 of 924
11.3%
17 of 924
1.8%
76 of 924
8.2%
34 of 924
3.7%
37 of 924
4.0%
Google AI Overviews87530, 3.4%831 of 875
95.0%
120 of 875
13.7%
87 of 875
9.9%
32 of 875
3.7%
227 of 875
25.9%
142 of 875
16.2%
33 of 875
3.8%
Google AI Mode924118, 12.8%737 of 924
79.8%
109 of 924
11.8%
73 of 924
7.9%
27 of 924
2.9%
108 of 924
11.7%
70 of 924
7.6%
24 of 924
2.6%
ChatGPT923117, 12.7%705 of 923
76.4%
113 of 923
12.2%
144 of 923
15.6%
110 of 923
11.9%
5 of 923
0.5%
0 of 923
0.0%
41 of 923
4.4%
Gemini924525, 56.8%381 of 924
41.2%
37 of 924
4.0%
57 of 924
6.2%
10 of 924
1.1%
14 of 924
1.5%
23 of 924
2.5%
1 of 924
0.1%

Engine rows use that engine's own answer count as the denominator, because the engines did not all answer the same number of questions.

Three findings sit in that table. First, ChatGPT cited a community site in 0 of its 923 answers, and a social or video site in 5 of 923, 0.5%. Google AI Overviews cited community in 142 of 875, 16.2%, and social or video in 227 of 875, 25.9%. On this dataset those are not the same medium. Second, ChatGPT is the engine that reaches for authority: it cited a government or regulator source in 110 of 923 answers, 11.9%, against 17 of 924 for Microsoft Copilot, 1.8%. Third, Microsoft Copilot cited a vendor or agency site in 922 of its 924 answers, 99.8%, and returned a source list on every single answer.

The ChatGPT community figure of 0 of 923 deserves a caveat rather than a headline. It is a real property of what our collector captured from ChatGPT on these dates, and it is consistent across ten independent accounts, which makes a per-account fluke unlikely. It is still one collector, one window of dates, and it may reflect what ChatGPT exposes as a citation rather than what it read.

The same disagreement inside one industry

Two industries where one source kind dominates, split by engine, to show the effect is not an artefact of pooling.

EngineCoworking: answers citing a directory or marketplaceSoftware supply chain security: answers citing documentation or standards
Microsoft Copilot115 of 150, 76.7%79 of 100, 79.0%
Google AI Overviews66 of 109, 60.6%67 of 100, 67.0%
ChatGPT68 of 150, 45.3%61 of 100, 61.0%
Google AI Mode56 of 150, 37.3%57 of 100, 57.0%
Gemini15 of 150, 10.0%48 of 100, 48.0%

In coworking, Microsoft Copilot cited a directory or marketplace in 115 of its 150 answers, 76.7%, while Gemini did so in 15 of 150, 10.0%. In software supply chain security the same kind of split does not appear: documentation ran from 79 of 100 answers on Microsoft Copilot down to 48 of 100 on Gemini, and every engine put it above 48%. Where a source kind is genuinely the substance of the category, the engines agree. Where it is a convenience, they do not.

06 / Denominators

Every industry's full denominator

Including the answers that returned text and no source list, which is the number most AI visibility statistics leave out.

IndustryQuestionsAnswersNo source listCited linksDistinct domains
Answer engine optimization
SourceRank AI
100500120 of 500, 24.0%1,969914
B2B outbound and lead generation
Danish Lead Co
118590137 of 590, 23.2%2,296698
Financial market data and news
account not named
4924556 of 245, 22.9%919366
Ecommerce development
account not named
108539115 of 539, 21.3%2,0491,238
Coworking and flexible office space
Westhive
150709146 of 709, 20.6%2,547526
Private equity and M&A deal sourcing
DealSource Systems
10049971 of 499, 14.2%2,074718
Healthcare benefits, employer buyers
account not named
5427028 of 270, 10.4%1,124551
Construction and industrial staffing
Cruitfly
9245446 of 454, 10.1%1,896673
Healthcare benefits, clinic buyers
account not named
5326426 of 264, 9.8%1,108631
Software supply chain security
CodeCargo
10050045 of 500, 9.0%2,219463

790 of 4,570 answers, 17.3%, carried no source list at all, and 525 of those came from Gemini. The sourceless rate itself varies by industry, from 26 of 264 answers, 9.8%, up to 137 of 590, 23.2%. Every share on this page is computed over the answers that did carry sources and expressed against the full answer count, so the shares below are floors, not estimates. A provider who drops sourceless answers from the denominator will report the same runs with materially higher numbers.

07 / The practical read

What to invest in, by industry

What this run says about where citation effort pays and where it does not. Every figure is share of that industry's answers.

If you are inWorth the moneyLowest return in this run
Coworking, flexible space, any bookable local categoryMarketplace and directory listings. Cited in 320 of 709 answers, 45.1%, on 24 distinct platforms. The four most cited were flexoffice.swiss in 82 answers, workin.space in 47, homegate.ch in 46 and matchoffice.ch in 38Documentation, 1 of 709 answers, 0.1%. Community, 3 of 709, 0.4%. News, 0 of 709
Software, developer tools, securityDocumentation, standards bodies and public repositories. Cited in 312 of 500 answers, 62.4%, and above 48% on every one of the five engines. Community and video follow: 62 of 500, 12.4%, and 84 of 500, 16.8%Directory listings, 13 of 500 answers, 2.6%, across 4 platforms. News, 0 of 500
Market data, financial informationEarning a mention in the financial press. News and media cited in 92 of 245 answers, 37.6%, across 19 outlets, which is the highest non-vendor share of any industry outside softwareDirectory listings, 4 of 245 answers, 1.6%. No single directory was cited more than once
Healthcare benefits, insurance, anything regulatedAlignment with the government and regulator sources the engines quote. Cited in 63 of 270 answers, 23.3%, drawn from 40 distinct government domains, and in 26 of 264 answers, 9.8%, on the clinic-side accountCommunity, 8 of 270 answers, 3.0%. News, 1 of 270, 0.4%. Directories, 27 of 270, 10.0%, and mostly niche ones rather than the household names
Staffing and industrial servicesRegulator alignment plus a small set of sector directories. Government cited in 49 of 454 answers, 10.8%, directories in 39 of 454, 8.6%, led by clearlyrated.com in 13 answers and ziprecruiter.com in 12Documentation, 6 of 454 answers, 1.3%. News, 1 of 454, 0.2%
B2B services: lead generation, deal sourcing, ecommerce build, AEOSocial, video and community. Social and video cited in 10.2% to 13.4% of answers across these four accounts, community in 3.8% to 9.8%. In lead generation, clutch.co was cited in 23 of 590 answers and trustpilot.com in 17, so the classic review directories do earn a place hereGovernment and documentation, both under 5% in three of the four. For answer engine optimization specifically, directories were 10 of 500 answers, 2.0%

The general rule this run supports: your own website carries the citation load in every industry, between 72.7% and 86.3% of answers, and no listing, profile or press mention substitutes for it. What changes by industry is the second surface, and that is where a budget is either well spent or wasted. A coworking operator ignoring marketplaces is invisible in 45.1% of the answers about it. A software company buying directory listings is buying into 2.6%.

Limits

What this does not tell you

  • +One industry, one company, one run. Each industry here is represented by a single company's tracked question set on a single date. A second coworking operator, or the same one a week later, would not return identical shares. Treat each row as one observation, not as the industry's constant.
  • +The question sets are not identical. Each account has its own questions, from 49 to 150 of them, written for its own buyers. Part of any gap between two industries is a difference in what was asked, not only in what the engines did with it.
  • +Domain kind is a judgement. Seven kinds, assigned by an explicit named rule set printed in the SQL at the end of this page's source, with vendor or agency site as the residual. The hardest calls are the ones where a category's competitors are the source type: a news vendor competing with news outlets, a code platform that is also a documentation host. We classified by what a site primarily is and published the list so it can be re-cut.
  • +The vendor bucket includes the company itself. Vendor or agency site covers each measured company's own website, its competitors and unrelated commercial sites. We do not publish any individual account's own-domain figures, so the vendor column should be read as a category total, not as anyone's visibility score.
  • +Sourceless answers are real and uneven. 790 of 4,570 answers, 17.3%, carried no source list, 525 of them from Gemini, and the rate ranges from 9.8% to 23.2% between industries. Shares here are floors.
  • +It measures sources, not sales. Being cited is not being chosen, and a marketplace citation is not a booking. This page counts what the engine reached for.
  • +Ten industries is not every industry. There is nothing here about legal services, industrial manufacturing, hospitality or consumer retail. The finding that the mix varies is well supported. The specific number for an industry not listed is not something this page can give you.

We re-measure every account every 6 days. This page is refreshed in place on the same URL as each account's newest run lands, so the URL stays stable and the numbers stay current rather than freezing on the day we first published them. If a figure here is being quoted, quote it with the run dates attached.

Key takeaways
  • +Directories and marketplaces were cited in 320 of 709 answers, 45.1%, for a coworking operator and 4 of 245 answers, 1.6%, for a financial data vendor. Same method, same five engines, same week.
  • +Documentation and standards ran from 312 of 500 answers, 62.4%, in software supply chain security to 1 of 709, 0.1%, in coworking. That is the widest gap on the page, 442 times.
  • +Vendor and agency websites were the most cited kind in all ten industries and moved least: 178 of 245 answers, 72.7%, to 392 of 454, 86.3%.
  • +ChatGPT cited a community site in 0 of its 923 answers. Google AI Overviews cited one in 142 of its 875, 16.2%. Microsoft Copilot cited a vendor site in 922 of 924, 99.8%.
  • +790 of 4,570 answers, 17.3%, carried no source list, which is why the denominator has to be published alongside any AI citation statistic.
Related

Where to go next

What AI engines actually cite

The companion report. One of these ten runs taken apart domain by domain, including the 25 most cited domains and the review directory count.

The measurement method

How the tracked question sets, the engines and the snapshots work, published before any numbers came out of them.

Free site readiness scan

A free scan of whether your site is structurally ready to be cited. It checks your site, it does not measure your citations.

To get this run for your own industry rather than one of these ten, the $497 audit on the pricing page is where it starts. The free scan at /score/ is a site readiness check, not a citation measurement, so it will not produce numbers like the ones on this page.

Questions

Common questions

Does the mix of sources AI engines cite change by industry?

Yes, and by far more than the averages suggest. Across ten companies in ten industries, 4,570 answers on five engines, directories and marketplaces were cited in 320 of 709 answers, 45.1%, for a coworking operator, and in 4 of 245 answers, 1.6%, for a financial data vendor. Documentation and standards ran from 312 of 500 answers, 62.4%, in software supply chain security down to 1 of 709, 0.1%, in coworking.

What do AI engines cite in every industry?

Vendor and agency websites. They were the most cited kind in all ten industries, and the range was narrow: from 178 of 245 answers, 72.7%, at the low end to 392 of 454 answers, 86.3%, at the high end. That is a spread of 1.2 times, against 442 times for documentation and standards.

Should a company invest in directory listings to get cited by AI?

It depends entirely on the industry, which is the point of this page. For the coworking operator, directories and marketplaces were cited in 320 of 709 answers, 45.1%, so listings are a primary surface. For the financial data vendor they were cited in 4 of 245 answers, 1.6%, and for the software supply chain security company in 13 of 500, 2.6%, so the same spend buys close to nothing.

Do different AI engines cite different kinds of sources?

Sharply. ChatGPT cited a community site such as Reddit, Quora or Stack Overflow in 0 of its 923 answers, and a social or video site in 5 of 923, 0.5%. Google AI Overviews cited community in 142 of its 875 answers, 16.2%, and social or video in 227 of 875, 25.9%. Microsoft Copilot cited a vendor or agency site in 922 of 924 answers, 99.8%.

Which AI engines does SourceRank AI measure?

Five: ChatGPT, Gemini, Microsoft Copilot, Google AI Mode and Google AI Overviews. Every number on this page comes from those five engines and no others.

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Find out what your industry's answers are built from

Ten industries, ten different source mixes. The audit runs this measurement on the questions your buyers actually ask.