AI citation rate: what counts as a good one?

There is no single good AI citation rate, because the number depends on the questions you ask. We measured one. We put 18 buying questions about AI agencies through Google AI Mode three times each, 54 answers in all. The most-named firm appeared in 20% of them, and no firm held more than 3 of the 18 questions in every run. A rule of thumb that says 30% means you are winning does not describe this category.

AI citation rate is the share of answers on a fixed panel of buying questions that name your company. Six answers naming you out of twenty is 30%. The arithmetic is easy. What makes the number mean anything is the panel, the engine and the number of runs behind it. An earlier version of this page gave three bands for it with no source; the section "What we got wrong before" says what we did about that.

What we measured

• Panel: 18 buying questions about AI agencies: shortlists, offers, prices, regions, platforms and verticals. Questions that contain a brand name are out, because they measure recognition. The full list is at the end.
• Engines: Google AI Mode, run three times per question (54 answers), and Bing Copilot Search, which gave the same answer to repeated runs and so counts once per question (15 answers). ChatGPT and Perplexity answer only after sign-in, so they are not in this edition.
• When and where: 22 October 2026, logged out, from Bangladesh.
• What counts: a firm is named when it appears in the answer. Different spellings of one firm (Intercom, Fin by Intercom) are merged with a published list; nothing else is merged or dropped.

What the numbers show

Answers name a lot of firms and almost no firm is named often. On Google, 94 different firms shared 54 answers, and 33% of them were named in a single answer. On Bing, 5 firms tied for first at 2 of 15 answers (Accenture, Deloitte, IBM, LowCode Agency and RTS Labs) and 61 of 66 names appeared once.

"Questions named" is the number of the 18 questions on which the firm appeared at least once. "Held" means it appeared in every run of that question. The firm list includes software vendors such as Intercom as well as agencies, because the engines named both.

What good means on this evidence

Good is relative to the leader on your own panel. On the Google panel the leader was named in 20% of answers, and the typical firm was named in 3 answers or fewer, which is one question held or a stray mention. Being named in about one answer in five put a firm at the top. A target set in the abstract, before you know who the leader is on your questions, tells you nothing.

The rate depends on how narrow the panel is. On 17 of the 18 questions at least one firm was named in every run, and 48 different firms held at least one question. The same firms score 20% or less across the whole panel. A firm that owns one narrow question has a 100% rate on it and a rate of 6% on a panel of 18. So a citation rate quoted without its panel cannot be compared with anything.

One run proves little. When we asked the same question three times, the sets of firms named overlapped by 68% on average, and 36 of 107 firm-and-question appearances (34%) showed up in only one run. Bing repeated itself exactly, which is a cache, not stability. Run each question at least three times, spread out in time, and track the questions you hold as well as the rate.

What we got wrong before

This page, and three other Gigabit articles, used to say that unoptimized brands sit at 0 to 10%, that a deliberate program reaching 30 to 40% is winning its category, and that past 50% you are the default answer. Those bands had no source and no sample. The data above does not support them: on this panel nobody reached 30%, and the leader was at 20%. We have removed the bands from all four pages.

Where Gigabit stands

Gigabit wrote this panel and is the author of the study, so it is shown but never counted as the leader or in the medians. The panel follows our service lines (pilots, managed operations, embedded engineers, prototype rescue, AI security, GEO, n8n, Odoo, Shopify), which favours us. Gigabit was named on 3 questions (p03, p05, p09) in every run, 9 of 54 answers (17%). That ranks second by answers, behind AY Automate and level with Intercom. It was not named on the other 15 questions. Read that as an example of what a strong result looks like on a panel you chose, not as a ranking of agencies.

How to report your own number

1. Write the panel down. 15 to 25 questions a buyer in your category really asks, with no brand names. Publish it with the rate.
2. Run each question at least three times per engine, logged out or on a clean account, and note the date and country.
3. Report four numbers: the share of answers that name you, the questions where you appear in every run, the leader's rate on the same panel, and how many runs sit behind it.
4. Repeat monthly on the same panel and watch the questions you hold, not any single answer.

The free citation audit runs this for your category, and the field guide covers the work that moves it. Ascent is scoped and reported on this basis.

Limits

• One category (AI agencies), one day, one country (Bangladesh; Bing localises results to the visitor even with a US setting).
• Two engines. Not ChatGPT, Perplexity or the Copilot app, which need a signed-in account that would bias a brand's own results.
• 18 questions and three runs each. Answers to one question are not independent, so the real sample is 18 questions, not 54 answers.
• Google shows source names, not URLs, so we count names in the answer rather than links.
• Bing showed search results instead of an AI answer for 3 questions; those are not counted.
• The panel was written by the firm being measured.
• The next run is planned for late November 2026, on the same panel.

The panel

The data is free to reuse under CC BY 4.0: download every firm named, with its counts. Please cite it as "Source: Gigabit, AI citation benchmark, October 2026, CC BY 4.0" and link to this page. If you think a row is wrong, write to hello@gigabit.agency.