Are fixed prompts enough to measure AI search visibility?
Many brands measure AI search visibility by running a predefined list of prompts and counting how frequently they appear in the answers.
For example, a SaaS company might track prompts such as "best CRM software," "top CRM platforms," and "CRM tools for sales teams."
These prompts provide a useful starting point, but buyers often ask more specific questions based on their requirements.
Someone might need a CRM for a 10-person team, while another is looking for software that integrates with Salesforce or supports complex enterprise workflows. Each scenario can produce a different set of recommendations.
Tracking prompts across buyer segments, use cases, and purchasing stages can reveal where a brand appears consistently and which competitors are recommended for particular requirements.
How are you selecting the prompts used to measure your brand's AI visibility? Are they based on actual buyer questions or a fixed keyword list?
Replies
The way I always put it: the prompts a brand tracks are a sample. There are hundreds of thousands of other questions buyers ask that we can’t track, and may never even know about. So treat the predefined set as a proxy for that bigger universe. How you pick that set is a different story altogether. We use several data points as proxies to find the prompts that best represent real demand.
On how many times: an action plan built on a single run is built on a snapshot, and I don’t think it’s wise for any brand to act on that. Run the same prompt at least 5 times, and up to 20 in fast-moving niches, to find the pattern. Don’t chase the exact words of an answer. Chase the patterns: how often your brand gets cited but not mentioned or recommended. Then work backwards to improve that ratio.
And being cited, being mentioned and being recommended are three separate things that need to be read differently. There are cases where a brand is cited every single time and never recommended. That’s the lowest-hanging fruit, by the way: the engine already trusts your content, it just isn’t naming you as the answer.
@masabgadit Hi, couldnt agree more.
For example, the prompt said that we track, we divide into 5 intent buckets: discovery, comparison, persona, feature, and price. We also run it multiple times to find the pattern. The pattern also has variance baked in, depending on the category of the company.
For example, a marketing operations company would have more variance because it'll have more breadth of companies to consider. A dedicated EOR company will have fewer ins and outs, so its variance is bigger. The patterns can also be set in multiple ways and completely aligned with your third paragraph.
A mix of both is what's worked for me. The fixed list is useful as a baseline because you can track it week to week, but it's rarely how buyers actually phrase things.
For the rest, I pull the exact wording people use in live chat conversations (Intercom). Those tend to be long and specific ("X for a 10-person agency that already uses Y"), and that's often where the recommendations differ most from the generic "best X" answers.
I'd also group them by stage. Early questions ("how do I...") and comparison questions ("X vs Y") often surface completely different brands, so one blended visibility score can hide where you're actually losing.
@rich186 You can also pull in long-term, long-tail queries from your Google Search Console to know which queries you are ranking for and create content around them.
Also, yes, I agree with the implied intent of the prompt. That is why we track across two prompts:
Brand-inducing queries, where a person is actually searching for a recommendation.
Top-of-funnel queries, more informational prompts, just to see which are the topical authorities as per the LLM.
@swati_paliwal Tracking prompts come in different types and cover different topics related to your offerings. They include branded, non-branded, and industry prompts. A keyword list isn’t useful because it’s tied to search volume and doesn’t reflect your niche or context. You can go deeper by starting with topics, then exploring user queries and related queries, depending on how many you want to track and where your business and organic presence are today.
@swati_paliwal @aimarketer_deepti Yes, that is why we track prompts across two sets of different objectives and, within those sets, multiple subcategories. This way, both our users can get direction on how to select the prompts, and the analysis and further actionables have merit.
Both, but I'd add two sources of real wording that are free. First, Search Console: the long queries that already show impressions for your pages are how people actually phrase the need, and they are usually longer than any keyword list. Second, language and country: the same question asked in a smaller language market often returns a different set of brands, and sometimes no brand at all, so a prompt set built only in English can overstate your coverage. I keep a small fixed baseline for week-to-week comparison and refresh the rest monthly from those two sources.
@ksanyokm Google Search Console tells you the queries you are already ranking for, but there are other ways to find queries that might be relevant to you but are not discovered via Search Console because you never rank for them.
Your language-specific point is interesting, and we are aware of it. That's why we're focusing our business (for now) where our prospective clients would be in an English-speaking demography.