Chris Byrne shares that other than sometimes using LLMs to summarise long articles / research (which some might consider lazy and not the optimal way to learn), he is also using Anthropic's Claude or Google's Gemini in his day-to-day work with simple quick prompting in the following ways (mostly without using 3rd party data and without using MCPs) for qualitative data analysis. Talking points include: How do you actually spot and report those fake lead-gen agencies disguising themselves on Google Maps? What steps do you take to flag misleading business profiles through Google Search Console spam reports? How can you use Claude to catch fake or incentivized reviews on Trustpilot? What are the legal risks under UK law regarding undisclosed incentivized reviews and reporting them to the CMA? How do you structure a prompt to analyze competitor backlink profiles for hidden PBN footprints? What indicators do you look for when checking if a backlink is non-compliant with search engine guidelines? How do you use AI for qualitative data analysis without getting bogged down in complex tools or MCPs? How can you feed official Google retail UX playbooks into Claude to audit an e-commerce site? What are the most effective ways to combine simple prompting with raw data to audit competitor websites? Why is quick, day-to-day AI prompting often more practical for qualitative SEO analysis than complex third-party setups?

Jenna Hannon suggests that you forget keywords. AEO is about going deep: build public documentation on your site that answers every specific question a prospect might ask at each stage of the buying journey. Key talking points: What sort of public documentation are you referring to? How do you know the specific questions that your prospects might ask? How do you prioritise the questions to answer? How do you know the volume and type of content required to answer a question? How do you know how the questions map to the different stages of the buyer journey? How do you go about mapping the answers? Read the full transcript of Jenna's interview at https://majestic.com/seo-in-2026/additional-insights/jenna-hannon Watch the original SEOin2026 series: https://www.youtube.com/playlist?list=PLOr75FiG9ta37FH130S-qu3H9N0h7Ly0I Watch more SEOin2026: Additional Insights: https://www.youtube.com/playlist?list=PLOr75FiG9ta3j5bYmsVBggEsBxwhGSX41

Kseniya Dvarakouskaya says that the biggest mistake in international SEO in 2026 is treating localization as the last step — real ranking growth in new markets starts with local keyword research from scratch, not translating what already works in English. Talking points include: Why translation is not localization when it comes to SEO — and where teams lose ranking potential - What local keyword research actually looks like (native speakers, local SERPs, market-specific search intent) - Cultural differences in search behavior — examples from Japanese, Korean, German, Spanish markets - Common mistakes: word-for-word translation of English keywords, ignoring local competitors, mixing Simplified and Traditional Chinese, using LATAM Spanish for Spain - Real case: what changes when the localization team is involved from day one vs at the end of the launch - How localization teams and SEO teams should collaborate in practice