Over the previous yr, we have gone from invisible in AI solutions for our class to constantly exhibiting up for the prompts consumers really use. That is the playbook — up to date with what practically a yr of operating it has taught us.
It began with a brutal wakeup name.
Simply weeks after launching Enterprise AIO and the AI Visibility Toolkit, I requested ChatGPT a easy query about AI monitoring instruments. It named each competitor — however not us. Regardless of the launch, LLMs had no thought we existed on this house.
And that wasn’t our solely drawback.
LLMs have been citing our weblog content material a whole bunch of occasions. But site visitors to our weblog was falling. Citations confirmed attain, not positioning — an LLM may cite our content material whereas recommending a competitor in the identical reply.
We have been dropping measurable affect whereas our true aggressive place stayed unclear.
That disconnect between citations and affect compelled us to rethink every part.
So, we used our personal instruments to construct a scientific strategy to AI visibility. In a single month, we practically tripled our AI share of voice — the proportion of solutions that point out us versus opponents — from 13% to 32% for our goal prompts.
That was the summer time of 2025. Since then, the self-discipline has moved quick. And so has our strategy.
We have re-scoped what we measure, narrowed the place we focus, and discovered which ways really drive visibility (and which do not).
What follows is the framework we nonetheless use, what’s modified since, the place our visibility stands right now, and methods to run it your self.
The measurement drawback
The measurement drawback is easy: Normal attribution cannot see AI affect as a result of LLMs form selections with out sending a click on or a conversion.
We may see LLMs utilizing our content material — citations confirmed that a lot. What we could not see was whether or not they really helpful us, ignored us, or acquired us unsuitable. Utilization is not positioning, and positioning is what strikes shopping for selections.
The operational facet was tougher.
Rank monitoring assumes steady positions you’ll be able to examine as soon as every week. AI solutions do not maintain nonetheless: The platforms are non-deterministic, returning totally different responses to the identical immediate inside a single day. In addition they shift quick. In our study of 230K prompts throughout ChatGPT, AI Mode, and Perplexity, ChatGPT’s citations of Reddit fell from practically 60% of responses to round 10% in a matter of weeks.
So I made a decision we must always change what we measured.
We stopped monitoring whether or not LLMs used our content material and began monitoring our aggressive place: whether or not we get talked about in any respect, and the way usually versus opponents after we do. (Whether or not AI represents us precisely turned out to matter simply as a lot — however aggressive place got here first.)
The 2 metrics that really matter
The 2 metrics that really matter are visibility and share of voice. Each work like acquainted Search engine optimization metrics, besides they measure affect as an alternative of clicks.
| Metric | What it solutions |
| Visibility | Are you talked about in any respect for a goal immediate? Binary — you are within the reply otherwise you’re not. |
| Share of voice | How usually does AI point out you versus opponents throughout these solutions? |
You may be seen in a single reply and nonetheless maintain low share of voice if opponents present up in practically all of them.
We observe each throughout ChatGPT, Google AI Mode, and AI Overviews, amongst different platforms, utilizing Enterprise AIO.
However the metrics solely imply one thing measured on the appropriate prompts.
Monitoring “AI instruments” tells you little or no.
Monitoring “finest AI visibility instruments for enterprise groups” tells you whether or not you present up precisely when somebody is selecting an answer.
Get talked about for prompts like that, and you have entered the customer’s consideration set in the meanwhile that issues — with out paying for an advert.
Our optimization framework
We nonetheless use the identical five-step framework we constructed at first. What’s modified is the main focus inside it. Here is the method and methods to replicate it.
Step 1: Determine your goal prompts
Begin by hand-picking the bottom-funnel prompts your group and stakeholders really care about — the buying-intent queries the place a purchase order determination is in play.
We started with 39 prompts, like “finest enterprise AI visibility platform,” as a result of they replicate actual shopping for selections. As we speak we observe 726. However the greater shift is the combo, not the quantity.
We weighted the set towards buying-intent prompts, the place AI is almost certainly to suggest a particular software. We additionally saved a smaller set of informational prompts. These not often identify any model, so they will not transfer share of voice — however they present whether or not AI treats Semrush as an authority on the broader matter, not only a vendor to checklist.
The precept beneath all of it: The prompts you observe are a tiny pattern of every part individuals ask.
So we optimize for the intent they signify, the best way you’d goal a subject in Search engine optimization moderately than a single key phrase. Prompt research is how we decide those price monitoring.
To trace your personal set, use the customized immediate characteristic in Enterprise AIO. Beginning with out instruments? Check variations manually throughout ChatGPT, Google AI Mode, and Perplexity.
Step 2: Set up baseline measurement
Arrange monitoring and measure the place you stand earlier than altering something.
Once we first measured, we sat at 13% share of voice for AI visibility prompts — confirming what we suspected. LLMs did not know we had AI instruments on this house.
That 13% mirrored our authentic 39-prompt set. Because the work matured, we re-scoped to the bigger 726-prompt set, weighted towards tougher, higher-intent queries. The 2 units aren’t straight comparable, so we reset the baseline to match the brand new scope: roughly 15% to begin.
Enterprise AIO automates this, monitoring your visibility and share of voice throughout AI platforms so you are not logging mentions by hand — which will get unmanageable quick.
Then observe it every day.
Bear in mind AI solutions are non-deterministic. Every day knowledge is what tells you whether or not a shift is actual or simply noise. Learn each quantity as a variety — a share of voice that swings between 20% and 40% over a day is regular, so “30% ± 10%” is the sincere technique to report it.
Step 3: Audit and improve your present content material
Audit the content material you already personal and discover the pages the place you’ll be able to naturally strengthen your presence in AI solutions.
The primary transfer is pure product mentions.
Discover content material that already discusses the issues your instruments remedy. Work them in the place they genuinely match. We had a submit on how to get LLMs to mention your brand. We up to date it with a piece on how Enterprise AIO‘s Supply Impression Evaluation reveals which sources LLMs really cite — introducing the software precisely the place a reader would need it.
(No enterprise plan? The AI Visibility Toolkit does the identical at a smaller scale.)
The second transfer is format.
We have been remodeling dense articles into cleaner buildings — direct solutions up entrance, clear headings, comparability tables — which helps readers and the AI programs that pull from well-organized pages.
The third is the largest shift in how we work.
Once we discover a content material hole, we deepen our protection of the entire matter behind it throughout our owned pages. That manner, we present up nonetheless somebody phrases the query.
The check is at all times the identical: The point out ought to assist the reader. If it would not, depart it out.
Step 4: Broaden past your area
Your personal web site is not sufficient. LLMs pull from throughout the net — Reddit, Quora, LinkedIn, Medium, and business publications.
At first, Reddit appeared like the apparent place for us to begin. However it’s a separate undertaking in its personal proper, one which wants actual technique, assets, and possession. Its quotation share additionally swings onerous, as we noticed in our most-cited domains study, so we have scaled again our focus there whereas we maintain testing what works.
We’re additionally testing LinkedIn and Medium, the place we will publish straight. LinkedIn issues particularly — it is a rising quotation supply throughout AI platforms.
The piece that issues most is accuracy. Among the pages LLMs cite most will not point out you, or will get you unsuitable — and AI programs reuse that very same context throughout many solutions, so one unsuitable declare can cascade.
That is why we have began scaling outreach in-house, constructing direct relationships with the house owners of extremely cited pages.
We’re after one factor: accuracy. Truthful criticism is one sign AI weighs in opposition to every part else; an inaccuracy will get repeated throughout reply after reply till it turns into the story. That is the actual threat.
Step 5: Create contemporary, citable content material
Create new content material that straight solutions your goal prompts, in codecs AI can pull from simply, like listicles and comparisons. Make it authoritative and data-driven: actual solutions backed by specifics.
Listed here are the writing ways our content material group makes use of:
- Mirror the heading in your first sentence. If the heading asks “What’s AI visibility?”, open with “AI visibility is …”
- Reply the query fully in that first sentence, the place readers and LLMs can discover it quick.
- Again claims with specifics. “Cited in Three of 10 responses for a goal immediate” tells a reader excess of “our visibility improved.”
- Skip analogies, idioms, and metaphors. Write “AI visibility is crucial for discovery,” not “AI visibility is the north star guiding ships by digital fog.”
- Hold antecedents clear. “Enterprise AIO tracks model mentions throughout AI platforms. The software highlights new citations” reads cleanly; “It highlights new citations” leaves readers guessing.
- Select readability over flourish. AI has to know and extract your level quick.
Outcomes: What labored and what did not
The strategy labored, and it saved working as we raised the bar.
On the tougher 726-prompt set, we have grown our share of voice from 15% to 25%. The good points reached past AI-specific subjects, too: throughout roughly 1,000 Search engine optimization-related prompts, share of voice rose from 49% to 55% over six months — an indication that sturdy Search engine optimization and AI visibility transfer collectively.
We will not totally isolate which tactic drove what, since we ran them without delay, although increasing past our personal area constantly appeared like a serious lever.
Two issues genuinely stunned us.
The primary was velocity — we noticed motion in days, generally hours, far sooner than Search engine optimization. However velocity cuts each methods: Content material decays simply as quick, so a web page dropping visibility cannot sit in a backlog.
The second is what nonetheless would not work — income attribution. Separating AI’s affect from paid search, e mail, and every part else is genuinely onerous.
The info is enhancing (Microsoft now experiences AI efficiency in Bing Webmaster Instruments, together with how usually Copilot cites your pages), however we’re not there but.
What this implies for Search engine optimization groups
We’re all figuring this out collectively, however some classes are already clear.
A yr in the past, I tracked weekly rating experiences like everybody else. Now I examine AI visibility every day, and I care as a lot about how AI describes us as about the place we rank.
Here is what I would inform one other Head of Search engine optimization beginning out:
- Anticipate your top-funnel content material to lose site visitors. Folks will not click on when AI solutions them straight, so measure visibility, not simply clicks.
- Your personal area is not sufficient, and accuracy issues as a lot as presence. Present up on the websites AI cites, and ensure they signify you appropriately — a unsuitable declare spreads throughout solutions.
- Put together stakeholders for brand spanking new metrics earlier than you want finances. Your CEO nonetheless expects site visitors, however your finest outcomes might not present up in Google Analytics.
- Construct content material processes for velocity. When visibility drops, the repair cannot wait in a backlog.
- Do not construct your personal AI visibility monitoring. The API prices, repairs, and knowledge reliability points make purpose-built instruments the higher funding.
That is an extension of Search engine optimization, not a separate self-discipline. The identical fundamentals — authority, clear construction, related content material — resolve whether or not you present up, whether or not an individual or a machine is doing the wanting.
Google now says so outright. In its guidance on AI features, Google states that optimizing for generative AI search options continues to be Search engine optimization, and that foundational Search engine optimization is the idea for visibility in its AI experiences.
So the work is not unique. Monitor the brand new metrics, cowl your subjects the best way good Search engine optimization at all times has, and keep near the information because it shifts.
We’re nonetheless studying. However this a lot is obvious: groups that begin now can be forward when everybody else is scrambling to catch up. Higher to begin measuring than to attend for excellent readability.
