What algorithms are actually trying to do
At their core, algorithms like Google’s and Meta’s are designed to answer a single question: what should this user see, right now?
Google does this in response to a search query. It attempts to understand what someone is looking for and presents the most relevant, useful, and trustworthy content to meet that need. Meta operates differently: without a direct query, it predicts what a user is most likely to engage with and structures a feed designed to retain attention.
Despite that difference in approach, the underlying principle of such algorithms is the same. Both systems continuously evaluate relevance, quality, and trust within the context of an individual user and their expectations in that moment. Their objective is to maximise user satisfaction in a way that encourages continued use. For Google, this means providing the right answer quickly. For Meta, it means creating an experience that sustains engagement over time.
In that sense, algorithms attempt to approximate human judgement, assessing what feels useful, credible, and worth attention.
Contextual systems limit technical SEO potential
Over the past three decades since Google’s inception, this approach has shifted significantly: early algorithms relied on relatively simple signals such as keywords, links, or chronological order. Today, they operate as dynamic, learning systems that interpret intent, evaluate context, and continuously adapt based on user behaviour. It is precisely this shift that makes designing solely for technical SEO insufficient.
Technical SEO elements such as metadata, crawlability, and page speed ensure that a website can be accessed and interpreted. However, in isolation they do not determine whether content deserves visibility. A technically sound website that lacks clarity, relevance, or differentiation will still underperform, because algorithms no longer reward technical correctness alone. Pure technical optimisation assumes a static checklist, while algorithms continuously evaluate context. It is entirely possible to optimise every page and still fall short of the algorithm’s objective: matching the right content to the right user at the right moment. When positioning and content are unclear, technical refinement cannot compensate.
There is also a clear diminishing return when evaluating technical SEO. Once baseline technical standards are met, further optimisation yields limited gains. Performance then becomes constrained by how clearly a brand communicates, how consistently it appears across channels, and how effectively it reinforces its relevance and authority.
Seen in this light, SEO is no longer a technical layer that can be addressed in isolation. It is the outcome of a broader system; one in which content, structure, visibility, and positioning all interact. Weakness in one area does not always cause failure, but it does reduce clarity. And reduced clarity limits how both users and algorithms respond.
Technical SEO remains necessary, but it is no longer decisive. It enables visibility, but it does not create it. Focusing on it in isolation results in a site that performs well in theory, yet underperforms in practice, because it does not align with what algorithms ultimately evaluate: clarity, relevance, trust, and the overall coherence of a digital presence.
Optimising for intent changes everything
When optimisation is approached from the perspective of user intent, this dynamic changes. By aligning content with what users are actually looking for, you are inherently aligning with what algorithms are designed to achieve. In that context, optimisation becomes less reactive. Instead of adapting to every algorithm update, you are operating on the same principles those updates are moving towards.