Execution
How to get recommended by AI
You do not persuade a model directly. You make the public evidence about your brand clearer, more consistent and easier to defend than the alternatives. Recommendation follows legibility.
Answer first
How do you get recommended by AI assistants?
Start with one recommendation intent, measure who is recommended today, then improve the sources that make your brand easy for a model to classify, compare and justify.
There is no guaranteed switch to flip. What works is narrowing the job to be done, tightening your public positioning, strengthening third-party evidence, and checking whether the answers actually change.
The framework
A five-step process that is realistic for an early-stage brand
- 01
Choose one recommendation intent
Do not start with a vague goal like 'be more visible in AI'. Pick the exact phrase or buyer situation you want to win, such as 'best onboarding analytics tool for B2B SaaS'.
- 02
Measure the current answer
Run a fixed prompt set across the major assistants and note who gets named, how often, and how your brand is framed relative to competitors.
- 03
Make your positioning easier to quote
Create pages that answer one real question directly, define your category plainly, and connect your brand to a specific job instead of broad promises.
- 04
Strengthen the off-site evidence
Update the comparison pages, directory profiles, reviews, documentation references and third-party writeups that models are likely to rely on.
- 05
Re-run and watch the framing
The goal is not only to appear once. The goal is to appear consistently and for the right reason across repeated prompts and systems.
On-site work
What your website should do differently
The site should behave less like a brochure and more like an answer library.
One page per real question
Build pages around the prompts buyers naturally ask: what the category is, how it is measured, why competitors are named, and how to improve the result.
One clear job per page
A page should answer one question plainly enough that a model can lift the definition or logic without guessing what you meant.
Consistent terminology
Pick the category terms you want associated with your brand and repeat them across titles, headings, body copy and supporting pages.
Clean supporting facts
Products, use cases, limitations, integrations and audience need to be easy to extract from the page, not hidden inside abstract brand language.
Off-site work
Why your own site is necessary but not sufficient
Assistants often rely on evidence you do not own: review platforms, directory pages, comparison articles, user discussions and documentation references. If those sources do not connect your name to the recommendation intent, your homepage alone rarely saves you.
That is why AI Visibility work is partly editorial and partly distribution work. You are not just refining your message. You are improving the places where the market describes you back to itself.
Avoid this
Four mistakes that waste time
- -Publishing generic thought leadership with no connection to the buying questions you want to win.
- -Changing homepage copy while ignoring directories, review sites and comparison pages that shape the answer more strongly.
- -Targeting the broadest possible category instead of a narrow, defensible use case.
- -Claiming proof you have not earned, which makes the public evidence about the brand less trustworthy.
A better target
What success should look like first
First win
Do not try to become a default answer for your whole market immediately. Try to become the most defensible answer for one narrow, commercial intent.
That is the fastest path to evidence. Once one use case is reliably associated with your brand, adjacent intents become easier to win. To set the baseline before changing anything, start with how to measure AI Visibility.
Answers index
Keep reading
Each answer is a page. Each page ends in the same place: a free, manually run audit of your own category.
What is AI Visibility?
How often, how accurately and how favourably AI assistants name your brand when asked for a recommendation.
AI Visibility vs SEO - what's the difference?
SEO wins a position in a list of links. AI Visibility wins a mention inside an answer that already made the choice.
How do AI assistants choose which brands to recommend?
They rely on the evidence they can absorb or retrieve: comparisons, documentation, reviews, community discussion and consistent positioning.
How do I measure AI Visibility?
Mention rate, share of voice, accuracy and intent coverage across a fixed prompt set, re-run over time.
Why does ChatGPT recommend competitors instead of us?
Because the sources a model trusts describe your category without clearly connecting your brand to a specific job.
Turn this into a concrete plan
The audit shows which intent to target first, which competitors own it now, and which sources are making the assistants choose them over you.