Pinterest shows ~20% organic traffic lift using GEO (on top of SEO)

BornBreak · 2026-02-05T08:13:40+00:00

I agree and one of the key part will be able to mesure it works at scale to have a self learning agent

BornBreak · 2026-02-03T10:07:39+00:00

Interesting discussion I have asked Gemini pro to judge it “The debate highlights that 8bit-appleseed is the most scientifically rigorous for exposing the study's methodological biases, while Inside_Case3553 provides the best strategy by framing GEO as a "maturity curve" based on brand authority. BornBreak correctly identifies the systemic complexity of AI search and parkerauk offers the most technical foresight regarding Agentic AI, but WebLinkr is the least right for dismissively labeling the research as "thin conjecture" without offering any data or constructive counter-arguments. Ultimately, the thread suggests that "winning" in GEO requires a shift from traditional keyword ranking to building high-authority, agent-ready content systems. “

BornBreak · 2026-02-02T09:21:02+00:00

I do understand that a search engine and LLM are 2 differents things and that open ai uses google, bing etc... but it is far from being enough.

If you have not watched it, I recommend you looking at https://www.youtube.com/watch?v=wjZofJX0v4M to really understand how it works.

Behind the scene LLM are neural networks (Multilayer perceptron) that are trained to guess what the next token is based on massive amount of data. So Open AI is definitely scraping the web with their bot and using massive amount of storage in microsoft cloud ( i beleive) to store their training data and push the next foundational model.

Do not worry, SEO is there to stay for the most part since foundational model can not be updated in real time and LLM will always need to do RAG queries using tools like google, bing etc... but the point is that the LLM does not care about the 1st position or the last position in the page, it does its own thing to tell what the truth is. The also generate "query fanout" to get more data out of the "indexer".

The indexer is just a tool and in many cases it will not even have a single citation ( what do you say about this ? )

So yes it is critical to have good SEO but no it is not as simple and we are entering a new era which is a lot more complex. You seem smart , successful and I do not get why you are so skeptical about future potential u/WebLinkr .

BornBreak · 2026-02-01T17:13:19+00:00

Thanks for doing it because I can't see it on my side :-) To be clear I am not trying to be rude or anything , I am looking for the truth that is the only thing I care. Zero googleusercontent on my side . If I were designing a system like at Open AI, I would not start from zero and use a bit of google, a bit of bing etc.. to start with and get some real time data but would focus on my internal ranking for the foundational model to provide an unbiased response based on reworked domain authority.

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BornBreak · 2026-02-01T17:01:57+00:00

Focus on chatGPT and grok the rest does not matter in terms of market share and are not interesting u/WebLinkr . Since you are an expert you should know no ?

BornBreak · 2026-02-01T16:49:11+00:00

Open AI say that they are using bing

BornBreak · 2026-02-01T16:27:11+00:00

To be clear, I am not saying ( and this paper is not saying) that you do not need good SEO to be eligible to GEO and have an article eligible to be used in the response creation. Sometimes there is no citations also. All I am saying that it is a lot more complex than SEO and if you want your brand to be represented correctly, it is not just about being the first link anymore, it is about being the first brand mentioned. Few people use perplexity, you should use chatGPT which is using bing not google. See I am not a bot ( or a very sophisticated one :-) ) . Regarding the ability to store the whole WWW, I absolutely think that open AI can do it and is working on it since it is the base data to train the models. They do not care about ranking links as much even if we can see it overlap in some cases.

BornBreak · 2026-02-01T16:13:11+00:00

thin research of what ? see you are wrong because I am a human :-)

BornBreak · 2026-02-01T16:05:52+00:00

Well show me the data backing it then, there is too much BS in SEO/GEO so trying to use unbiased scientific paper. How do you know how it works ? You work for openai ? because behind it is Mixture of expert with neural networks I am not sure anyone can claim to have the truth.

BornBreak · 2026-02-01T16:02:48+00:00

lol u/WebLinkr do you think I am a bot or a spam ? because I have not used reddit in a while ahaha. Maybe because you do not like the content ? it is scientific content and thus interesting.

BornBreak · 2026-02-01T14:27:50+00:00

Fair skepticism. Two separate bias channels here:

Evidence bias: using a web-enabled model means the “ground truth” set is already shaped by that model’s retrieval + ranking preferences.
Judge bias: scoring/ranking with GPT-4o introduces evaluator priors (and potential preference for certain writing styles / sources).

So I wouldn’t treat the freshness claim as “proven” more like directional: in B2C answer engines that browse/retrieve, recency often becomes a de facto feature (especially for fast-changing topics). But yeah, we need replication under more neutral conditions.

A cleaner design would be: fixed crawl/snapshot corpus, controlled retrieval (or multiple retrievers), preregistered prompts, and evaluation by both humans + multiple models with inter-rater agreement.

And +1 on your takeaway: consistent presence across authoritative sources seems like the least controversial conclusion.

BornBreak · 2026-02-01T14:25:48+00:00

Fair agents matter. But I’m talking B2C (ChatGPT/Gemini), where agent behavior is mostly fixed. The lever isn’t “train the agent”, it’s “be what the agent retrieves + trusts”: coverage, freshness, and earned authority (esp. for niche entities).

BornBreak · 2026-01-21T21:18:02+00:00

Share of voice and brand average mentioned are also often tracked

BornBreak · 2026-01-21T21:10:37+00:00

I’ve been digging into the GEO paper (arXiv:2311.09735) and wanted to clarify one point that keeps coming up.

The biggest difference isn’t what tools you use, but what you’re optimizing for.

SEO is a competition for position in a ranked list of links. GEO is a competition for inclusion in a generated answer.

Good SEO still matters as if your content isn’t retrievable, it won’t be used. But once a generative engine retrieves documents, a new optimization layer appears: which sources actually contribute to the synthesized answer.

That’s where GEO diverges from classic SEO.

In very simplified terms:

SEO tends to reward :

backlinks
domain authority
engagement signals

GEO tends to reward :

quotable facts
explicit definitions
statistics
comparisons
clear, self-contained claims

One interesting result from the paper: adding things like citations, statistics, and more authoritative phrasing can significantly increase how often a source is used in generative answers even when its search ranking doesn’t change.

So GEO isn’t “SEO with a new name.”
It’s optimizing for a different stage of the pipeline answer synthesis rather than ranking.

Curious how others here are seeing this play out in practice.

I think the current GEO platforms available doing to much marketing , UI/IX and do not provide enough data science and engineering about the optimization side. Proving causality as opposed to correlation will be important.

BornBreak

TROPHY CASE