The company and the data
The company is a mid-sized software engineering services firm: it designs and builds custom software and digital products for other businesses. We do not name it, its people or its competitors. The competitors are Competitor A to G below, ordered by how often the assistants named them.
The data is a weekly series of scans we ran for it. All the numbers in this post come from it.
| Item | Value |
|---|---|
| Period | Nine weekly scans, from 17 August to 12 October 2026 |
| Assistants | ChatGPT and Claude in all nine weeks, Gemini in the last eight. Each on a small, low-cost model. Gemini used a different model in its first week than in the seven after. |
| How | Each prompt asked once per assistant per week, with web search on, in English, as from the United States |
| Prompts | 397 asked every week, plus 2 added in week five: 399 in all. One more prompt that names the company is left out of every number here. |
| Answers | 10,344: 3,582 from ChatGPT, 3,576 from Claude, 3,186 from Gemini |
| Competitors | Seven firms in the same business, from regional specialists to a far larger global firm. The original list also tracked two publishers; they are left out here. |
Of the 399 prompts, 216 are commercial (comparing options), 146 informational and 37 transactional. Most of them were written from the topics of the company’s own pages, the rest from search queries it already followed and by hand. Keep that in mind: a list built from your own pages leans towards the subjects you already cover well.
The headline: named in 3 answers in 100
| Assistant | Answers | Named | Linked | Linked, not named | Share of voice |
|---|---|---|---|---|---|
| ChatGPT | 3,582 | 97 (2.7%) | 91 (2.5%) | 0 | 12.3% |
| Claude | 3,576 | 130 (3.6%) | 300 (8.4%) | 185 | 15.3% |
| Gemini | 3,186 | 117 (3.7%) | 121 (3.8%) | 27 | 9.5% |
| All three | 10,344 | 344 (3.3%) | 512 (4.9%) | 212 | 12.0% |
3.3% sounds poor, and on its own it says little. Two more numbers put it in context.
- Most answers named no firm at all. In 7,813 answers (75.5%), neither the company nor any of the seven competitors was named. For informational prompts that was 93.7% of answers; even commercial prompts, which ask to compare options, named none of the eight firms in 67.0% of theirs.
- Competitors were not everywhere either. 1,975 answers (19.1%) named at least one competitor and not the company. The rest, 556 answers, named or linked the company.
Where a tone was recorded for an answer that named the company (267 of the 344), it was positive in 180, neutral in 86 and negative in 1.
Where it was named: narrow questions in its own industries
The overall rate hides a very uneven picture. By category of prompt:
| Category | Prompts | Answers naming the company |
|---|---|---|
| Healthcare | 12 | 27 of 312 (8.7%) |
| Logistics | 86 | 156 of 2,211 (7.1%) |
| Design and UX | 46 | 60 of 1,195 (5.0%) |
| Financial services | 36 | 43 of 936 (4.6%) |
| Software engineering | 40 | 7 of 1,040 (0.7%) |
| Data and analytics | 23 | 3 of 598 (0.5%) |
| AI and machine learning | 68 | 4 of 1,766 (0.2%) |
| Cloud and infrastructure | 14 | 0 of 364 |
Questions set in an industry, and design questions, named the company. Questions about a technology almost never did. The 68 prompts about AI and machine learning produced 1,766 answers, and 4 of them named the company.
By intent, transactional prompts named it in 5.4% of answers, commercial ones in 4.2% and informational ones in 1.5%. And it was concentrated in a few prompts. Only 64 of the 399 prompts named the company in any answer. The ten that did so most often produced 149 of the 344 named answers, 43%. Eight of them were narrow requests of the form “can you recommend a vendor for this kind of work, for this kind of company”. Four of the ten had been written from the company’s own case studies and three from its industry pages. The strongest named it in 24 of its 26 answers.
Linked more often than named
The company’s site was cited in 512 answers, more than the 344 that named it. The two overlap, but not the way one might assume.
- When an assistant named the company, it usually linked to it as well: 300 of the 344 named answers.
- The other way round is different. 212 answers linked to the company without naming it, and 185 of those were Claude’s. ChatGPT never linked to the company without naming it.
The pages behind the unnamed links were mostly the company’s articles: cited as explanations, with the recommendation going elsewhere or nowhere. Case studies and industry pages, by contrast, were cited almost only in answers that named the company. The breakdown is in the companion post, Where 110,000 citations went.
Week to week: steady total, busy underneath
On the 397 prompts asked every week, in the eight weeks with all three assistants, the share of answers naming the company moved between 2.4% and 4.0%, without a direction. Underneath, individual answers changed constantly: in the seven week-to-week comparisons, an assistant started naming the company on a prompt 95 times and stopped 100 times. Of 1,191 combinations of prompt and assistant, only 9 named the company every week.
The two prompts added in week five, both asking for the top software development companies in the company’s main industry, named it in 22 of their 30 answers. Counted with the rest, they made the second half of the period look better than the first. About half of that apparent rise came from them alone. How to read a series like this is the subject of One scan is a sample.
What the data supports, and what it does not
What it supports:
- For this company, visibility in assistant answers was a matter of specific questions, not of the category as a whole. The overall rate was low and stable; the prompts that mattered were a few dozen.
- On broad technology questions, the assistants named a far larger firm or no firm at all.
- The three assistants were not interchangeable. Claude cited the company’s site most and most often without naming it; Gemini crowded more firms into its answers; ChatGPT linked only when it named.
What it does not support:
- Anything about Perplexity, Google AI Overviews or AI Mode, which were not part of these scans.
- Anything about larger models. Each assistant ran on a small one, and the answers people get in the apps may differ.
- Why the numbers are what they are. The data shows where the company was named and which pages were cited. Explanations are hypotheses to test with the next scans.
- A trend. Nine weeks with a stable list showed variation, not movement.
The questions a team would take from this are the ones the data raises: why the industry pages and case studies work and the technology articles do not, and whether the prompts about technology are the questions this company’s buyers actually ask. Teddit measures; the answers to those questions are the company’s to find.