Resumo aquí los key Tips and predictions que me parecen más interesantes del SEOFOMO de Aleyda Solís en su hub.seofomo.co
Key SEO Tips and Predictions for 2026 by +32 Top SEO Specialists
https://hub.seofomo.co/surveys/seo-predictions-tips-expectations/
- Google volume loss, mainly on informational queries.
- More of the user journey will happen offsite (llms, AI platforms), resulting in less direct website traffic.
- Avoiding “shiny object syndrome.”
- SEO remains SEO, even with AI components layered on top.
- More AI involvement in results and interfaces, creating both risk and differentiation opportunities.
- Content will increasingly be consumed through machine-mediated interfaces, not websites.
- AI becomes a core layer of search, but not a wholesale replacement of traditional search results.
- Attribution challenges as user journeys fragment across platforms.
- ROI, attribution, and business outcomes will outweigh rankings and raw traffic.
- Schema to be “huge,” especially for structuring data for llms.
- Semantics, entities, and deeper intent understanding.
- Structured, machine-readable content becomes increasingly necessary for visibility.
- A renewed appreciation for human marketers and strategists.
- Many AI tracking tools will disappear.
- Traditional keyword tracking tools to lose relevance.
- The more you know about your customers—their needs and their objectives—where llms can be really helpful in supporting this, the better your results are going to be.
- Focus on the SEO fundamentals and on what will move the needle and help achieve your business goals.
- A lot of the user journey is going to take place offsite, in llms and other AI platforms.
- Humans will become more important than AI
- There will be more AI involvement in search results, both on the algorithmic side and on the UX side.
- If you manage to keep up with everything, you have the opportunity to stand out compared with more generalist marketers who can’t stay on top of SEO.
- People will need to build more business cases. There are so many new things—AI search, for example—and many people struggle to prioritize. If you don’t build these cases, you’ll end up working on many things that have no real impact. By the end of the year, you might feel like you’ve done a lot of work, but ultimately there will be no meaningful impact on the business.
- The most important aspect is semantics: entities and understanding what users are really searching for.
- Schema adds structure to an otherwise unstructured mess, which is what llms and similar systems deal with. So start re-implementing schema as much as possible and mark up everything you can.
- Traffic for the sake of traffic isn’t what they really want.
- A strong focus on structuring data and content so that llms and search engines can use as few tokens as possible to understand the core message. That will mean removing a lot of the “digital jazz hands” we’ve built into websites simply because they look nice or people like them, even though users may not actually experience them. I think people will experience content less through websites themselves and more through other interfaces, where machines play a bigger role. The portal through which people consume your content won’t necessarily be your website, and we need to start adjusting to accommodate that.
- Focus on fixing the problems users have.
- To master feeds and first-party data sent to platforms like Google and openai to avoid misrepresentation.
- Investing heavily in proprietary data.
- To confront GA4 and attribution data to understand organic search’s real business value.
- Brand recognition, topical expertise, and product relevance.
- Get yourself, your website, and your business ready for the AI agentic web.
- Protect yourself from generative results that could distort or misrepresent you.
- The user journey is becoming more multimodal, so you really need to dig into attribution and advertising reports.
- More emphasis on understanding their audience.
- They’ll [llms] want to save tokens and understand what an entity is and what something means in as little time as possible. That’s where schema comes in: it tells them what the entity is, provides the context, and helps them understand the format and structure of the content.