Your next customer may not be Googling you. They may be asking ChatGPT.
More shoppers now start their research with a question typed into an AI assistant rather than a search engine: “what’s a good skincare brand for oily skin in Jakarta,” “which coffee chain has the best loyalty program,” “recommend a reliable e-commerce platform for my business.” The answer they get back was written by an AI model, not ranked by a search algorithm, and it may or may not mention your brand at all.
This shift is what’s driving a new discipline called GEO, or Generative Engine Optimization. If you’ve spent years optimizing for Google, it’s worth understanding how this is different, and why ignoring it could mean losing visibility with an entire generation of AI-first searchers.
GEO vs. SEO: what’s actually different
Traditional SEO is about ranking. You optimize a page so it appears higher in a list of ten blue links, and the searcher decides which one to click.
GEO is about being the answer. When someone asks an AI model a question, the model synthesizes a single response, often naming two or three brands by name, sometimes just one. There’s no list to scroll through. Either you’re part of that answer, or you’re invisible to that customer entirely.
This changes what “optimization” means. It’s no longer just about keywords and backlinks. It’s about whether large language models like ChatGPT, Claude, Gemini and Perplexity can actually access your content, understand what your brand stands for, and trust it enough to recommend it.
Why brands go missing from AI answers
Three problems tend to explain why a brand doesn’t show up, or shows up incorrectly, when AI models are asked about its category.
The content is technically unreachable. AI crawlers, like search crawlers, read a site’s robots.txt file to decide what they’re allowed to access. A single blocked path can make an entire model unable to “see” a website, even if the content itself is excellent. Most brands have never checked whether ChatGPT’s or Gemini’s bots can actually reach their pages.
The information is thin or scattered. AI models build their understanding of a brand from what’s publicly available: the website, reviews, articles, directory listings. If a brand’s value proposition, differentiators and audience aren’t clearly and consistently stated anywhere, the model either skips the brand or fills in the gaps with guesses, some of which are wrong.
Nobody is monitoring it. Even brands that are visible today have no way of knowing if that stays true. Models get updated, competitors publish new content, and AI’s answer to “best loyalty app in Indonesia” can shift without any signal reaching the brand’s marketing team.
What AI visibility actually looks like
Rather than treating this as a vague concern, it helps to break AI visibility into a few measurable pieces:
- Visibility score and share of voice. How often does your brand get mentioned when AI models are asked about your category, and how does that compare to competitors getting mentioned in the same conversation?
- Gap analysis. Where does what the AI says about your brand diverge from what you’d actually want a prospect to hear, and how much does each gap matter?
- Brand alignment. Does the AI accurately describe your value proposition, your audience and what makes you different, or has it filled in the blanks incorrectly?
- Multi-model access. Can ChatGPT, Claude, Gemini and Perplexity all actually crawl and read your site, bot by bot? A single blocked path can make a brand invisible to one model while remaining visible to others, and most teams never think to check the difference.
Once you can see these numbers, GEO stops being abstract. It becomes a set of specific fixes: unblocking a crawler, rewriting a page to state a claim more clearly, publishing content that closes a known gap.
A quick check you can do right now
Before investing in a formal audit, try this: open ChatGPT, Gemini or Perplexity and ask it a question a real customer might ask about your category, without naming your brand. See if you come up. If you do, check whether the description is accurate. If you don’t, ask a follow-up naming your brand directly and see what the model says about you when prompted.
This isn’t a substitute for a full visibility audit, but it takes five minutes and often reveals more than teams expect, sometimes in an uncomfortable way.
Why this matters more in Indonesia, not less
It’s tempting to assume this is a problem for global brands with global search volume, and that AI search adoption will take longer to matter locally. But the more consumers rely on AI assistants for everyday recommendations, restaurants, skincare, retail, and the earlier a brand establishes accurate, well-structured visibility, the harder it becomes for competitors to displace it once AI models have “learned” who the trusted names are in a category. Waiting until GEO is mainstream means competing for a position that others may have already claimed.
The brands that get found first tend to stay found. The question worth asking isn’t whether GEO is relevant yet. It’s whether your brand can currently answer the question a customer is already asking an AI, right now, about you.
