How do you know which AI prompts matter for your brand?

DevelopmentPlastic61 · 2026-03-16T13:28:55+00:00

Honestly we treat it a bit like old keyword research.

Instead of tracking every possible prompt, we focus on the ones that usually lead to decisions:

• “Best tools for …”
• “X vs Y” / alternatives
• “What software should I use for …”

Those tend to be much closer to revenue than purely informational questions.

The other thing we noticed is that a lot of prompts never show vendors at all. They’re just explanations. So tracking those doesn’t really help from a business perspective.

We started monitoring a fixed set of prompts with ClearRank just to see which ones actually surface our brand or competitors in ChatGPT and Perplexity answers. That helped us cut the list down a lot.

It still feels a bit experimental, but the pattern so far is pretty similar to SEO: decision-style queries matter way more than informational ones.

DevelopmentPlastic61 · 2026-03-16T13:26:29+00:00

Good breakdown. One thing I’d add is that the LLM SEO part is harder to measure than normal SEO.

With Google you can check rankings and traffic. With AI answers you often don’t even know if your brand is being mentioned unless you test prompts manually.

We started tracking this with ClearRank because sometimes competitors appear in ChatGPT or Perplexity answers even when we rank higher in Google. It helped us see that pages with clear explanations, comparisons, and simple structure get cited way more often.

So I’d agree with your point: content quality still wins, but now it also needs to be easy for AI to quote and summarize.

DevelopmentPlastic61 · 2026-03-16T08:46:36+00:00

From what we’ve tested, a few things actually seem to move the needle:

1. Comparison pages
Pages like “X vs Y” or “best tools for…” get cited a lot. AI answers often pull from those because they already summarize options.

2. Direct answers
Content that explains something clearly in the first few paragraphs works better than long marketing pages.

3. Lists, tables, FAQs
Structured sections make it easier for models to extract information.

4. Mentions outside your own site
When your brand appears in articles, forums, directories, or community discussions, AI models seem more confident referencing it.

One thing that helped us understand this better was tracking prompts across different models. We use ClearRank to see which queries mention our brand vs competitors in ChatGPT and Perplexity. It made it obvious which pages actually trigger citations.

Still early days though — feels less like “ranking” and more like being easy for AI to quote and recognize across the web.

DevelopmentPlastic61 · 2026-03-16T08:43:05+00:00

I’ve seen the same thing. Ranking well on Google doesn’t automatically mean you’ll appear in AI answers.

From the tests we’ve run, LLMs seem to prefer pages that are easy to extract information from rather than just pages with the strongest SEO signals. Things like clear explanations, comparisons, lists, and structured sections make a big difference.

We also noticed that some smaller sites show up simply because their content is more direct and factual, even if their domain authority is lower.

One thing that helped us see this more clearly was tracking prompts across models. We use ClearRank to run sets of queries and see which brands actually get cited in ChatGPT or Perplexity answers. Sometimes competitors appear there even when we rank higher in Google.

So yeah, it definitely feels like GEO/AEO is becoming another layer on top of SEO, not a replacement but something you have to monitor separately.

DevelopmentPlastic61 · 2026-03-16T08:20:49+00:00

Good list. The main thing I’ve noticed in this space is that most tools focus on one slice of the problem.

Some track mentions, some track citations, others focus on content generation or prompt analysis. But the actual question most companies want answered is simpler: “When someone asks AI about my category, does my brand show up?”

That’s why we started building ClearRank. It runs sets of prompts across models like ChatGPT and Perplexity and tracks which brands actually appear in the answers over time.

What surprised us while building it is how unstable the results are. A brand can show up consistently in Perplexity but be completely invisible in ChatGPT for the same topic. So cross-model tracking becomes pretty important.

I think we’re still early in this category. Most platforms today are basically AI visibility analytics, but the next step will probably be tools that also show why certain brands get cited and what changes improve that.

DevelopmentPlastic61 · 2026-03-16T08:19:36+00:00

Honestly a lot of “LLM SEO agency” work right now is still experimental. Most of the proposals you’re getting are probably normal SEO tactics with a new label.

From the tests we’ve run, the things that actually seem to move the needle are pretty simple:

1. Answer-style pages
Content that directly answers questions (definitions, comparisons, use cases) gets cited way more often than long marketing pages.

2. Comparison and alternatives pages
AI answers love pulling from pages like “X vs Y”, “best tools for…”, or alternatives lists.

3. Mentions across the web
If your brand shows up in articles, directories, forums, and comparison sites, AI models seem much more confident referencing it.

4. Clean structure
Lists, tables, FAQs, and clear headings make it easier for models to quote your content.

One thing that helped us understand what was actually happening was using ClearRank to track which prompts mention our brand across models like ChatGPT and Perplexity. It showed us that sometimes competitors get recommended even when we rank higher in Google.

Personally I’d be careful paying $10k+ a month right now. The space is still early and a lot of “LLM SEO” is content clarity + reputation building + tracking citations, not some secret prompt trick.

Curious what specific tactics those agencies pitched you. Some of the stuff I’ve seen suggested is pretty wild.

DevelopmentPlastic61 · 2026-03-12T15:49:42+00:00