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AI Marketing 5 min read

GEO vs SEO: Why AI Search Is Rewriting the Rules for B2B and B2C Brands

By Jessica, Founder, Twigs&Ink · Updated

What is the difference between GEO and SEO?

SEO earns a ranking that a buyer might click. GEO (generative engine optimisation) earns a citation inside the answer an AI tool writes, such as ChatGPT, Perplexity or Google AI Overviews. GEO rewards answer-first writing, specific facts, structured data and original research. Most brands now need both.

Last week a client showed me their analytics dashboard. Organic traffic was down 18% year-over-year. Their SEO agency's response was to recommend more blog posts. Their CFO's response was to ask why marketing had a budget at all.

The answer neither of them wanted to hear: their buyers had stopped using Google for the part of the journey where this client used to win. Pre-purchase research (comparing options, understanding categories, reading reviews) has migrated to ChatGPT, Perplexity, and Google's own AI Overviews. The clicks didn't disappear. They got intercepted.

This is the moment SEO becomes one of two disciplines, not the only one. The new sibling is GEO (Generative Engine Optimisation) and AEO, Answer Engine Optimisation. Different mechanics, different playbook, same goal: be the source the buyer trusts when the answer arrives.

The shift: from "rank for the keyword" to "be the citation"

Classic SEO is a click economy. You write the page, it ranks, the buyer clicks, your tracking fires. GEO is a citation economy. You write the page, the model reads it, the model uses your content to answer a buyer's question, and may or may not show your link. Sometimes the buyer clicks through. Often they don't.

If that sounds bad, look closer. A citation inside ChatGPT is a recommendation from the most-trusted advisor your buyer has ever consulted. The conversion rate of "ChatGPT told me to look at Twigs&Ink" beats almost every channel in your stack. The catch: you have to actually be cited.

What GEO actually optimises for

The signals that earn citations from large language models overlap with classic SEO but rank differently. From what we've tested across client accounts:

  • Declarative answers, not setup paragraphs. Models prefer pages that answer the question in the first 200 words. Kill the throat-clearing intro. Lead with the answer.
  • Specific numbers and named examples. "Most CFOs distrust attribution" loses to "73% of CFOs in a 2024 Gartner survey said marketing attribution is the metric they trust least." Models repeat what's quotable.
  • Structured data, ruthlessly applied. FAQ schema, HowTo schema, Article schema, Product schema. The models don't need it to read your content, but it dramatically improves citation accuracy.
  • Original primary research. Models prefer content that other sources cite. Your survey, your benchmark, your dataset, your case study with real numbers.
  • Clean information architecture. Clear H2s, short paragraphs, lists. Anything that lets the model extract a clean quote without context contamination.

What changes for B2C and what changes for B2B

For B2C brands, the answer-engine layer mostly intercepts the consideration stage. "What's the best moisturiser for sensitive skin?" "Which mattress is worth $2,000?" The model returns a list, often without links. Your brand needs to be in the list, ideally with a quotable distinguishing claim.

For B2B, it's deeper. Buyers ask the model to compare vendors, summarise pricing models, explain implementation timelines. If your competitor has thoughtful content about their onboarding process and you don't, the model will recommend them by default, even if your product is better. The B2B losing pattern in 2026 isn't "we have less brand awareness." It's "we have less indexable expertise."

Where to start this week

Three concrete moves you can make in the next five working days, in order of impact:

  1. Audit which answer engines currently cite you. Take ten high-intent questions your buyers ask. Run them through ChatGPT Search, Perplexity, Google AI Overviews, and Claude. Note what gets cited. That's your competitive map.
  2. Pick your three highest-value pages and rewrite the intros. Lead with the answer, not the setup. Add a short FAQ schema block. Watch citation frequency over 30 days.
  3. Publish one piece of original primary research per quarter. A survey, a dataset, a benchmark. This is the single highest-leverage activity for getting cited at scale.

SEO isn't dead. It's just no longer alone in the room. The brands that figure out how to be visible in both places (the indexed web and the answer layer above it) will own the next five years of organic discovery.

Key takeaways

  • Pre-purchase research is moving from Google results to AI answers, so clicks are being intercepted, not lost.
  • AI tools favour pages that answer in the first 200 words, cite specific numbers and use clean headings and schema.
  • B2C brands need to appear in AI shortlists; B2B brands need indexable expertise on pricing, onboarding and comparisons.
  • Start by auditing ten buyer questions across the main answer engines.

Frequently asked questions

Is SEO dead because of AI search?

No. Google still drives large volumes of traffic and AI tools often draw on pages that already rank well. SEO is now one of two disciplines, alongside GEO and AEO.

What does GEO stand for in marketing?

GEO stands for generative engine optimisation: the practice of making your content and brand easy for generative AI tools to understand, trust and recommend by name.

How do I know if AI tools cite my brand?

Run your top buyer questions through ChatGPT, Perplexity, Google AI Overviews and Claude, and note which brands get named. Repeat monthly to track change.

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