Heard this framework at BrightonSEO and it killed half my client assumptions: 8 yes/no questions before you spend a cent on GEO or SEO
Picked this up from a BrightonSEO talk and then heard Malte Landwehr frame it again on a podcast, and it's reorganized how I scope every project. The idea is dead simple: most people start at the wrong end. They jump straight to "let's optimize and measure" when the actual reason they're invisible is three gates back.
It's a sequence of yes/no questions. You have to be brutally honest, and the rule is you don't move to the next one until the current one is a real yes. The first no is your actual project. Everything downstream is a waste until you fix it.
- Is there demand? Are people actually asking AI tools and search engines about your category at all? Some categories just have no query volume, nobody is asking ChatGPT to recommend your kind of thing yet. If no, GEO can't manufacture demand that doesn't exist. Stop here.
- Is the space winnable? If demand exists, is the answer space already locked up by giants, marketplaces and Wikipedia, or is there room? Going up against Amazon and three billion-dollar incumbents for a head term is not winnable. Find the slice that is.
- Do you have content? Do you actually have content that answers the buyer-intent questions being asked? Not a homepage and three service pages, real answers to the real questions. If no, that's your project, go make it.
- Is the content indexable and retrievable? This is the one GEO breaks on that SEO people forget. Can the AI crawlers actually reach it? Are you blocking GPTBot/ClaudeBot/PerplexityBot in robots.txt, is critical content rendered only in JS the bots don't execute, do you have any machine-readable structure at all. Great content the model can't retrieve is invisible.
- Do you have visibility? Are you actually showing up now, even occasionally, in answers and results? This is your baseline. If you've never been cited once, that's a different starting line than slipping from page one.
- Are you differentiated? If a model lined you up next to five competitors, is there an actual reason to pick you, or are you interchangeable? Models (and people) don't recommend the undifferentiated option. If you can't finish "we're the one that…", that's not a marketing problem to optimize, it's a positioning problem to solve first.
- Do you have social proof? Is there third-party validation the model can find, reviews, mentions, being listed where your category gets discussed? Models build recommendations from consensus across sources, not from your own claims about yourself.
- Do you have positive brand sentiment? When AI describes you right now, is it positive, neutral, or quietly damaging? You can be visible and still be described in a way that loses you the deal. Negative sentiment is a fix-first, not an optimize-later.
Only when all eight are an honest yes do you earn the right to the last step: optimize and measure. That's the part everyone wants to start with, and it's the part that only works once the foundation under it is real.
The reason I like it is that it kills wishful thinking. Half the time someone asks me why AI doesn't recommend them, the honest answer isn't a clever GEO tactic, it's that they failed gate 2 or gate 6 and no amount of schema fixes that. The framework makes you say the uncomfortable thing out loud before you waste three months.