Many of the fundamental techniques of good SEO are evergreen. But not everything about the search industry is static from month to month or from year to year – after all, SEO in 2023 is a very different beast to SEO in 2013, or even 2018.
For SEOs, there is a pressure to keep up with industry trends in order to make sure that they remain abreast of these changes and on the cutting edge of optimisation.
Shifts in search also mirror shifts in the wider web, with the search experience part of much of the nascent discussion around generative AI, for example. So what are the current trends shaping search, and what should SEOs do to respond to them?
Head over to part 2 for: the long tail and multi-modal search.
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SEOs have spent years using the mantra ‘E-A-T’ – or Expertise, Authoritativeness and Trust – to guide their work, knowing that these factors are all integral to the way that Google’s Search Quality Evaluators assess them, according to the search giant’s guidelines. However, in late 2022, Google added an extra ‘E’ – standing for Experience. From its Search Central blog:
“Does content also demonstrate that it was produced with some degree of experience, such as with actual use of a product, having actually visited a place or communicating what a person experienced? There are some situations where really what you value most is content produced by someone who has first-hand, life experience on the topic at hand.”
This addition seems as though it could be a response to the increasing quantities of spammy reviews and also AI-generated content populating search results, which Google has previously aimed to tackle with updates like the August 2022 Helpful Content Update (HCU). One of the points in the HCU guidance seems like a clear forerunner to Google’s extra ‘E’:
“Does your content clearly demonstrate first-hand expertise and a depth of knowledge (for example, expertise that comes from having actually used a product or service, or visiting a place)?”
While Google has previously stated that it has no issue with AI-generated or AI-assisted content as long as it offers genuine value, this is one way of distinguishing content that is more likely to offer that value in certain contexts. And by codifying Experience as part of (E-)E-A-T, Google is making it clear that this first-hand, hands-on knowledge is central to its evaluation and ranking of all search results.
SEOs who are already paying attention to E-A-T are unlikely to run into any difficulties with the additional E, as they are already likely to be producing (or overseeing) content that is designed to be genuinely informative and answer searchers’ queries rather than simply ranking for the sake of ranking.
However, it’s an additional reminder of the importance of real knowledge (whether it’s expertise-driven knowledge, or first-hand knowledge) underpinning content, rather than simply the appearance of ‘knowledge’ from an AI’s recycling of information.
Speaking of AI, I’d be remiss not to cover one of the most talked-about trends currently dominating marketing – and innumerable other industries.
We’ve done a few dives into the intersection of AI-generated content and search, including one on how AI copywriting intersects with Google’s HCU, and another on the potential for AI-generated content farms. Google has repeatedly emphasised the importance of writing “for people, not for search engines” and stated that this is more definitive than whether the article was authored (in whole or in part) by AI; Danny Sullivan, Search Liaison at Google, wrote on Twitter:
“We’ve said, pretty clearly, content written primarily for search engines rather than humans is the issue. … If someone fires up 100 humans to write content just to rank, or fires up a spinner, or a AI, same issue…”
However, Google is reportedly still developing a policy regarding how AI-generated content fits into E-E-A-T, according to a summary of Google’s announcements and responses to questions at Search Central Live Tokyo in June, written by SEO Suzuki Kenichi. Google has also cautioned against publishing AI content without review from a human editor, given the known issues with large language models (LLMs) and factual accuracy. (This is also likely true for unreviewed machine translations of content).
In July, Google’s Gary Illyes also posted to LinkedIn to warn against using LLMs as an SEO tool to diagnose prospective site issues. “LLMs have a very high wow factor, but they have no clue about your website; don’t use them for diagnosing potential issues with it.
“Also remember that LLMs will hallucinate; pressed in the right way, they WILL give you information that’s completely detached from reality because the predictions on the word order make sense.”
LLMs and generative AI are a fast-evolving area and it’s worth keeping tabs on the announcements about them from Google and others (Bing, for example, has gone all-in on generative AI as a part of its search engine with Bing Chat, as part of Microsoft’s new ‘copilot for the web’ approach), but we can expect the core approach to stay the same: Google is interested in ranking content with genuine value to searchers, not content that exists purely to game the search results.
LLMs can also be expected to continue having a loose relationship with the truth, with Sundar Pichai saying that “No-one … in the field has yet solved the hallucination problems”, making it important to check their outputs carefully – and preferably add to them with genuine expertise.
Google is known to be developing and refining its own generative AI technology with its PaLM LLM and generative AI chatbot Bard. It is also creating a new version of the search experience that incorporates generative AI answers and summaries, which was reported to be internally codenamed Project ‘Magi’, and externally has been referred to as a Search Generative Experience, or SGE.
Microsoft introduced the same functionality a few months ago via Bing Chat, which allows searchers to chat with a generative AI bot that can summarise and explain information using natural language (complete with links to sources). Despite pipping Google to the post, however, Bing’s market share of search has not increased since it introduced generative AI (and even appears to have gone down), and so as ever, all eyes are on Google’s next move in this area for the true impact on SEO.
Everything is still very much in the testing stages for SGE, but Google is previewing the new experience through its incubator, Labs, which was previously active between 2002 and 2011, and has been brought back in 2023 to offer early access to SGE. (Maybe there’s hope yet for other discontinued Google ventures…?)
For the moment, access is US-only, and Google has stated that early access will be offered for a “limited time” only (as yet unspecified).