Successful SEO professionals know a lot about dealing with uncertainty – such is life when algorithms that make or break performance are kept under lock and key.
But Search Generative Experience (SGE) triggers change-related anxiety from even the most seasoned SEOs.
Simply put, it’s both a paradigm shift and a quickly moving target; Google’s incorporation of SGE has been evolving almost daily.
So what do we know, and what should we expect – and how should we prepare? In this article, I’ll take a look at:
Where do we stand on SGE?
From a UX perspective, Google scaled back on the initial look, which was taking over most of the SERP. Now it’s less in your face, which I suspect they had planned the whole time – test maximalist to force people to notice and collect data on how they behave in the new environment.
Sticking with the user perspective, not everyone is served SGE with every query. I just tried 10 queries (a mix of “what is,” “should I buy,” “top 10 options for,” and information on state governors), and none of them returned results featuring SGE.
This will certainly change as the product comes out of beta, but it reaffirms that SGE is still in the roll-out phase, and users, SEO, and Google are all learning on the fly.
For SEOs, SGE is kind of the black box within the black box of Google’s algorithm. We can make some very educated recommendations for navigating the world of SGE, but nothing is clear at this point.
How could user behavior (and SEO) shift?
I’ve spoken with many people who have recoiled at the idea of SGE taking over their SERPs. This isn’t surprising; it combines the specter of AI taking over the world with a general distrust of change.
Add that to Google’s reputation on the advertising side, taking a few PR hits lately, and you have a bit of a perfect storm.
That said, I expect Google will just shove SGE down people’s throats as they did with featured snippets, the knowledge graph, etc.
After the 100th search, it’ll just be the expected experience. And I do expect the results to get better and more useful over time.
I’m already finding it useful as a user. For example, when looking for synonyms for a given word, I used to go to Thesaurus.com.
Now, I can just type it in and ask Google to show me synonyms, and AI will spit out a list, which saves me time. Something like that is fairly linear.
But for more complex issues, you’re still better off with content written by humans.
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What kind of skills do SEOs need to capitalize on SGE?
This is where we get into speculation a bit more. I believe SGE won’t reward SEOs who practice completely different strategies than they do for keyword and query-related search. The skills will have a ton of overlap.
Having said that, I think for some SEOs, the question of how to harness SGE for your brand’s benefit might become, essentially, “How do you produce really good content that Google will use as a source for its AI,” not “How do you produce valuable content for the end user?”
Writing for AI and writing for users, after all, could have subtle but meaningful differences.
I’m looking at this question like I do with featured snippets. The goal should be to communicate trust and usefulness to Google.
The SEO content I’ve seen featured in SGE for my clients has either featured structured data (easy for Google to digest) or has been housed in pillar pages that cover the topic in-depth and act as a resource.
In short, it looks like content that ChatGPT would reference if asked a specific question, but it doesn’t sound like ChatGPT (which would add nothing to the conversation).
When I think of writing for SGE – which could have real benefits, like lifting your content from the bottom of the SERPs to the top-of-the-page SGE ranks – I think of giving the AI incentive to point the user to your site.
This might sound counterintuitive because Google’s been telling SEOs not to make content just to rank – but ultimately, my goal is to be useful to the end user, which hasn’t changed from pre-SGE days.
If there’s a net-new skill we need to add, it’s developing an understanding of how large language models (LLMs) spit out answers and what the model isn’t delivering that humans need to add.
That could be personal opinions, experience, anecdotes, etc.
AI could certainly remix those and spit them out in aggregate, but there’d be a lot lost in translation.
In short, think about the gaps in AI-produced answers, and make sure you’re addressing those gaps to add value.
Use user-generated content as an insurance policy
On the opposite end of the content spectrum, we have user-generated content (UGC).
Big September and October updates from Google kicked off a lot of chatter on X and SEO forums about the possibility of a bigger emphasis on UGC in the SERP results.
While I haven’t seen a big spike in its SERP visibility, I do think content pulled from sites like Quora and Reddit (speaking as someone with a focus on B2B/SaaS) is useful.
And it represents an extremely personal counterpoint to SGE:
If you’re looking to lean into a facet of SEO to hedge against possible erosion from SGE, UGC could be a smart – and relatively underutilized – bet.
SEO and SGE: Preparing for the future
In a meta sense, the SEO tenets of methodical testing and finding your way in a murky landscape will be more important than ever in planning a world heavy in SGE.
- Follow your favorite industry sources closely.
- Annotate changes in both the Google landscape and your own strategy to recognize trends.
- Understand the role of human insight in bringing value to the user.
It might not guarantee success, but you’ll have a solid foundation that will make strategic pivots easier to pull off.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.
