For years, the WordPress SEO stack has been pretty straightforward.
Install Yoast, Rank Math, AIOSEO, or something similar. Set your titles and descriptions. Generate a sitemap. Add schema. Fix your redirects. Make Google happy.
That still matters.
But ChatGPT, Gemini, Perplexity and other AI answer engines introduce a slightly different problem:
What does an AI crawler actually receive when it visits your page?
We recently compared five WordPress plugins through that lens:
- Rank Math
- Yoast
- AIOSEO
- LovedByAI
- Squirrly
Full comparison of the best GEO plugins for WordPress
Disclosure before getting into it: I'm part of the team behind LovedByAI, so don't treat this as an independent ranking. What I think is more interesting than the ranking itself is what we found when comparing how these tools approach AI discovery.
SEO and GEO are solving different problems
Traditional SEO plugins are primarily designed around search engines indexing a page and returning a link.
You optimize things like:
- Meta titles
- Canonicals
- XML sitemaps
- Structured data
- Redirects
- Internal linking
- Keyword usage
GEO, or Generative Engine Optimization, is trying to influence a different outcome.
Instead of:
"Can Google rank this URL?"
The question becomes:
"Can an LLM understand this page well enough to use the business as part of an answer?"
That means page structure, entity clarity and machine readability become much more important.
The architectural difference I found most interesting
Most WordPress SEO plugins are what I'd call passive optimization.
They improve the existing page.
Rank Math might inject schema. Yoast adds metadata. AIOSEO adds LocalBusiness information.
But when an AI crawler visits the site, it still receives the underlying WordPress page.
Depending on the site, that can mean a pretty messy combination of:
Theme HTML
Page-builder markup
Navigation
Popups
JavaScript
Tracking scripts
Widgets
Cookie banners
Actual content
More JavaScript
For a human browser, that's fine. The browser knows how to render it.
For a machine trying to quickly determine:
What does this company do?
Who is it for?
Where does it operate?
What services does it provide?
Why is it different?
there's potentially a lot of noise.
The alternative is an active rendering layer.
Instead of only modifying the original WordPress HTML, you create a machine-oriented representation of the same page.
Something closer to:
<h1>Acme Accounting</h1>
<p>
Acme Accounting provides bookkeeping and tax services
for small businesses in Austin, Texas.
</p>
<h2>What services does Acme Accounting offer?</h2>
<ul>
<li>Bookkeeping</li>
<li>Business tax preparation</li>
<li>Payroll management</li>
</ul>
alongside structured entity data.
The information hasn't fundamentally changed.
The representation has.
That is the approach we took with LovedByAI's LLM view.
So do you replace Yoast or Rank Math?
I don't think so.
This was probably the biggest conclusion from the comparison.
A GEO plugin and an SEO plugin shouldn't necessarily compete for the same slot.
Rank Math is very good at things like:
- redirects
- sitemap management
- schema
- on-page SEO
- 404 monitoring
Yoast remains extremely strong for:
- editorial workflows
- readability
- metadata
- mature SEO infrastructure
AIOSEO has particularly useful features for local businesses.
Those problems don't disappear because ChatGPT exists.
The stack increasingly looks more like:
WordPress
↓
Traditional SEO layer
↓
Yoast / Rank Math / AIOSEO
↓
AI visibility layer
↓
Machine-readable content + entity data
In other words, SEO hygiene + GEO infrastructure, rather than SEO vs. GEO.
llms.txt has gained popularity, but it's not the right answer
Another thing worth mentioning.
There has been a lot of attention around llms.txt.
It's an emerging convention, but generating an llms.txt file doesn't suddenly make a site optimized for AI.
The actual page still matters.
An AI system needs to extract clear facts, relationships and answers from your content.
Things like:
- clean semantic structure
- descriptive headings
- direct answers
- Organization and Service schema
- consistent entity information
- crawlable content
are much harder to fake with one text file.
How I'd evaluate a WordPress GEO plugin
After working on this space, I think the useful questions are less about how many "AI features" appear on the pricing page.
I'd look at:
1. What does an AI crawler actually receive?
Inspect the output, not the marketing copy.
2. Does it improve machine readability or just generate content?
An AI writing assistant and an AI-search optimization layer aren't the same thing.
3. Does it produce useful structured data?
Not just generic Article schema.
4. Does it work alongside the existing SEO stack?
Replacing a mature SEO setup just to add GEO rarely makes sense.
5. How much work does it require after installation?
For SMBs especially, a dashboard containing 47 recommendations isn't necessarily a solution.
The bigger shift
The web has historically been optimized primarily for two consumers:
Humans
Googlebot
We're adding a third:
Humans
Search crawlers
AI crawlers / answer engines
And they don't necessarily want information presented in exactly the same way.
I suspect the WordPress stack will increasingly reflect that.
SEO plugins will continue handling technical search hygiene. A new layer of tools will focus specifically on making sites easy for AI systems to parse, understand and cite.
I also created a free GEO auditor that you can run and see the type of suggestions that we are talking about.
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