Are SEOs Aligned on LLM Visibility Tools? Here’s What the Experts Say
From entity tracking to AI Overviews, SEO pros debate how to optimize for the next generation of AI-powered search.
4 min readHighlights
SEOs debate if LLM visibility tools deliver real insights or just cater to consultant hype.
Experts suggest tracking entities, brand mentions, and topics—not keywords alone.
Tools like SERPRecon and Waikay attempt to reverse-engineer LLM outputs for client-facing strategy.
Image source: Designed by Martech Scholars using Canva Pro_SEOs explore how LLM tools track brand mentions and entity relevance in modern search.
As AI-powered search continues to evolve, so too must SEO. Tools that measure Large Language Model (LLM) visibility are becoming more common—but are they really helpful, or just shiny distractions? A spirited discussion on LinkedIn recently revealed deep divides in how SEOs view the utility and future of these LLM-focused SEO tools.
The Spark: Are These Tools Worth It?
It all started when SEO expert Joe Hall posted a provocative question on LinkedIn, questioning the value of tools that claim to track visibility within LLM-driven environments. He emphasized the contextual fluidity of LLM responses, pointing out that their subjective, dynamic nature challenges traditional SEO logic.
“Even if you could track them, how can you reasonably connect performance to business objectives?” — Joe Hall
Joe’s critique wasn’t entirely dismissive—but it definitely opened the floor for skepticism, especially among SEOs focused on data integrity and ROI.
A Paradigm Shift in Measurement
Joshua Levenson responded by suggesting that the current SEO mindset is outdated.
“People are using the old paradigm to measure a new tech.” — Joshua Levenson
That single line resonated. It pointed to a broader tension: many SEOs are trying to apply traditional KPIs—click-through rates, rankings, keyword usage—to LLMs, which don’t behave like static search results. LLMs respond with narrative answers, not lists of links.
Joe Hall replied with one word: “Bingo!”
Lily Ray’s Take: It’s All About Entities
Prominent SEO strategist Lily Ray brought a more balanced view. She acknowledged the complexity but pointed out that LLMs rely heavily on entities and brand associations when generating responses. According to her, these are measurable patterns.
“If you ask an LLM the same question thousands of times per day, you’ll be able to average the entities it mentions.”
The insight? It’s not about chasing exact keywords anymore. Instead, it’s about ensuring your brand and content topics are aligned with what LLMs see as relevant, trustworthy entities.
When asked by Hall how this benefits clients, Lily explained:
“There are actionable recommendations in the data… but it’s not as easy as ‘add this keyword to your title tag.’”
Tools on the Table: Waikay and SERPRecon
Several SEO toolmakers chimed in with how their platforms tackle the LLM challenge.
Dixon Jones introduced Waikay (short for What AI Knows About You), a tool focused on entity and topic extraction. It provides gap analysis to help users optimize for the topics AI tends to prioritize.
Meanwhile, Ryan Jones explained the mechanics behind his platform, SERPRecon. His tool uses two methods:
- API Monitoring: Scraping LLM responses, extracting key entities and themes.
- ISP Data Tracking: Monitoring real user queries where the brand shows up—though he admits this is costlier.
“The focus isn’t on the exact wording but the topics and themes it keeps mentioning—so you can go optimize for those.” — Ryan Jones
In another post, Jones added:
“AI Overview tries to reverse engineer [LLM logic] using the same logic/math as their patents, but it can never be 100%.”
He’s upfront about the tool’s limitations—but also its value.
“If I enter 25 queries, I want to see who IS showing up there and what topics they’re mentioning.”
Not Everyone Is Convinced
Some SEOs remain skeptical. Hall emphasized that LLM outputs aren’t fixed and are influenced by various contextual triggers, making them hard to forecast or strategize around. Traditional search, he argues, was far more consistent.
But others, like Billy Peery, pushed back on that.
“I guess I disagree with the idea that the SERPs were ever static.”
Peery argues that, ironically, LLM behavior may be more stable than traditional SERPs in some ways.
“With LLMs, we’re able to better understand which sources they’re pulling from… even if the words change.”
His insight reframes the problem. Instead of chasing rankings or keyword placement, focus on becoming a trusted source. If AI consistently pulls from your content, you win—even if your name doesn’t show up in blue links.
The Real KPI: Are You a Trusted Entity?
What’s emerging is a new type of SEO, where visibility isn’t measured by clicks alone, but by mentions, citations, and knowledge inclusion within LLM-generated answers.
That means shifting focus to:
- Building strong entity relationships (through structured data and content).
- Establishing brand authority in specific topics.
- Monitoring which sources LLMs reference and modeling your content accordingly.
The Optimization Challenge
Lily Ray is right: it’s no longer about stuffing keywords. It’s about developing rich, topic-driven content that aligns with what AI considers authoritative.
That’s why tools like Waikay and SERPRecon may not be perfect—but they bridge the gap between visibility and strategy in an AI-first world.
Are We Optimizing for AI or for People?
A deeper question underlies all of this: Should we be optimizing for LLMs at all? Or should we focus on helping users, knowing that LLMs are trained on user-centric content?
For now, it’s a blend of both. As LLMs shape how users find information, being absent from the AI narrative could mean being absent from the future of search altogether.
Final Thoughts
The SEO industry is clearly in transition. While some are still hesitant about LLM visibility tools, others are already building new optimization playbooks around them.
Here’s what we know so far:
- LLMs value entities, not just keywords.
- Brand trust and mentions carry weight in AI-generated responses.
- Tools that help analyze these signals are still maturing—but they’re getting better.
Whether you’re skeptical or all-in, one thing is certain: understanding how LLMs process content is becoming essential for forward-looking SEO strategies.
As AI continues to evolve, so too must our approach to visibility, content quality, and what it truly means to rank.
