What is generative engine optimization (GEO) and why should marketing agencies care?
Generative engine optimization (GEO) is the practice of getting a brand named, linked, and recommended inside AI-generated answers from ChatGPT, Perplexity, Gemini, Claude, and DeepSeek. It is adjacent to SEO but plays by different rules: there is no ranked list, citations replace clicks, and the engine summarises sources before the user ever sees them. For marketing agencies, it is the next billable retainer line.
What GEO actually means in practice
When a buyer asks ChatGPT "what is the best HR software for a 50-person agency?", the engine returns a paragraph naming two or three vendors, sometimes with footnoted links. GEO is the work of making sure your client is one of the named brands, not one of the ones the engine silently skipped.
The mechanics are different from search. There is no organic ranking position. The engine reads many sources, synthesises an answer, and decides which brands to mention. That decision is influenced by what is written about the brand across the open web, the structure of the brand's own site, and how often other trusted pages reference it by name.
Why agencies should care
Three reasons:
- Client search behaviour is shifting. Buyers who used to compare on Google now ask Perplexity or ChatGPT for a shortlist. If a client is invisible in those answers, the funnel narrows at the top before any of your paid or SEO work fires.
- It is a new retainer line. GEO sits alongside SEO and content but does not compete with them. Most agencies can layer a $1.5k-$5k monthly GEO line onto existing clients without expanding headcount, using tools to do the monitoring and reporting.
- Early-mover positioning. The category is two years old. Pitching GEO in 2026 is what pitching paid social was in 2014: clients have heard of it, most agencies do not offer it, and the ones who do get to set the price.
What GEO is not
GEO is not a renamed SEO retainer. The deliverables look different: brand-mention monitoring across five engines, citation-source audits, structured-data and entity-anchor work, AI-readable content pages, and prompt-level competitor tracking. A standard SEO audit will not tell you why ChatGPT cites a competitor and ignores your client.
It is also not a black box. The same content engineering, PR placements, and structured data that help GEO also help traditional SEO. Most of the upstream work overlaps. The measurement layer is where it diverges.
A concrete example
Take a B2B SaaS agency running a $4k/month retainer for a payroll-software client. The client ranks #3 on Google for "payroll software for accountants" but is never named by ChatGPT when a buyer asks the same question. The agency runs a GEO scan, sees that ChatGPT cites G2, a Forbes Advisor listicle, and the client's two largest competitors. The fix is not more blog posts. It is getting the client onto the G2 category page, fixing schema on the homepage so the engine can identify the entity cleanly, and placing one analyst-style write-up that the engine will treat as a citable source. That work is a 60-day project and a recurring monitoring retainer. It would not exist as a service line without GEO as a category.
How to start offering it
Two paths. Run it yourself: pick a GEO platform that tracks prompts across the five major engines, train one strategist, productise a 30-day audit and a monthly retainer. Or partner: white-label the monitoring layer and resell, while focusing your team's hours on the content and PR work the audit surfaces. Either way, the first move is to scan a few existing clients so you have real data before you sell.