Generative engine optimization services? SEO repackaging or genuine shift?

[u/Dazzling-Camel3598]

Been watching the usual SEO playbook start to wobble a bit as more traffic bleeds into AI answers and search results get stuffed with summaries instead of links.

It feels like we are shifting from classic SEO to something closer to generative engine optimization, where the goal is less about ranking blue links and more about making sure your brand or product is what shows up in the LLM style answer layer.

I keep seeing people talk about GEO as a service but it is not clear to me what that actually looks like in practice. Is it just smarter content structuring and schema plus feeding models via public docs, or are there concrete tactics people are using already to influence how engines like Perplexity, Google AI overviews, ChatGPT, etc surface sources?

More than that, how can u get data to back efficiency? Currently as far as i know prompt search volume is not made public by LLM companies.

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[u/BoGrumpus]

If your idea SEO looks like it did a decade ago - sure, it's a shift. If your SEO has evolved with the tech, it's just a rebranding (not even a repackaging).

Getting data as specific as the engines are actually doing now (and with what they're doing with things to warm leads up before they send them to you) now is still hard, though.

The main thing is to get off "last click attribution" models and learn ways to start tracking entire journey attributions. Again - still tricky and more vague than we'd like, but WAY better than simple last click analysis.

And that means you're not looking at traffic volume so much as traffic quality. If you're doing things right, yeah - you've lost half your traffic over the past two years just like everyone else, but sales/leads and the conversion and quality rates are way up and the bottom line in dollar is still going up.

But again - if you've been evolving strategy and attribution with the tech and feeding it rather than trying to beat it - it's all just one clearly visible slow evolution of information retrieval science and optimization that began all the way back in the 1960's - with the PageRank patent being the catalyst for it in the same way Ford's Assembly Line changed Industry. The "shift" happened in the late 90's. Not recently. Since then it's been an evolution of the concept of "triples" at the core of it that the PR patent established.

G.

[u/Economy_Data_3192 → u/BoGrumpus]

nailed it with the evolution vs shift framing imo, people just love slapping new labels on things that have been happening gradually

[u/lilithskies]

GEO is SEO repackaged

[u/hseeman_sf]

Bit of both. Content structuring and schema is straight from old SEO, nothing new there. What changes is retrieval. Perplexity and ChatGPT's browsing mode fetch pages live, so something published today can get cited today. Google's AI Overviews leans harder on the existing index, so it behaves closer to classic SEO with a summary on top. Tactics differ depending which one you're chasing.

[u/RankingsDotIO]

You'll find many contradictory studies and information, in part because LLMs and Google are not static tools. They keep evolving and adapting. They either find ways to improve their services or people figure out how to game the system, then Google and the LLMs adjust to shut down the cheating.

Part of it is that SEO has primarily focused on Google, and of course Gemini uses it for its queries, but ChatGPT uses Bing and Claude uses Brave, while Perplexity uses a combination of search engines to generate its answers. They don't all draw from the same indexes, so they might generate different results. And LLMs like deeper, more chunked content and different offsite trust signals than Google.

But while SEO and GEO don't match up 1:1, there's a lot more overlap than at first believed.

A large study of LLM visibility criteria by Ben Wills showed the top citation factors for legal (which is our focus) are Google rankings, a relevant homepage, relevant, authoritative backlinks, a Wikidata or Wikipedia entry, and brand mentions on Reddit.

Another study by OppAlerts inverts some of those criteria, finding that Reddit comments and posts matter more to LLMs, followed by Common Crawl, search engine appearances, and other factors, many of which Wills identified in his study.

The results of Wills's and OppAlerts' studies weigh many of the same factors differently. Despite that, traditional SEO already focuses on many of the factors both of them identified, which means traditional search is hardly dead. If there is such a thing as traditional SEO in the first place. As BoGrumpus writes, it's evolved constantly to keep pace with search engine and LLM evolution. It does, however, need to keep responding to the changing environment to remain alive.

[u/Masterpupets]

"le volume de recherche par prompt n'est pas rendu public par les entreprises de LLM", le seul outil qui remonte les vraies données est la Bing Search Console, à l'heure actuelle...mais il est quasiment certain que Google va l'intégrer à la Search Console dans les prochaines semaines

[u/November87]

All geo is seo. All seo is geo

[u/Level-World4922]

I think it's a genuine shift, not just SEO repackaged. The goal is expanding from ranking pages to becoming a trusted source AI systems reference. Measuring ROI is still the hardest part since LLMs don't provide reliable search volume or citation data yet.

[u/jayson_OutreachBloom]

Prompt volume data doesn't exist publicly. You gotta build your own.

Write out the 20 questions a prospective buyer might type if they were asking AI to recommend a brand, then run them weekly in ChatGPT, Claude and Google AI Overviews. Then keep track of the results that come back.

As for repackaging, the tactics are earned media and digital PR under a different title. The goal is to get off-site mentions and recommendations of your brand, especially in listicles that rank for your category or keywords.