There’s no single standard rate for Generative Engine Optimisation, and no independent industry benchmark yet. Based on the proposals we have seen, specialist GEO programmes typically fall between £3,000 and £20,000 per month depending on scope (a FirstMotion estimate), and there are published price points to anchor against in our guide to GEO agencies in London. What determines a sensible GEO budget is a specific set of cost drivers: how many AI platforms you need tracked, how much content needs restructuring or building, and how long you’re prepared to run the programme before judging it. Get objectives and budget right before you start evaluating vendors, and the vetting conversation gets a lot shorter.
Most B2B SaaS teams do this backwards. They start by asking agencies for a quote, then try to reverse-engineer what that quote should have bought them. This guide sets out the order that actually works: define what AI search visibility means for your business, size a budget against the work that requires, then use a short set of questions to separate specialists from agencies bolting GEO onto an existing SEO retainer.
Key takeaways
- Define AI search objectives at the platform, query-type, and competitor level before pricing anything, rather than starting from a vague goal like “improve AI visibility”
- GEO budgets should scale against platform coverage, content scope, and tracking cadence, not a legacy SEO retainer size
- Meaningful movement in AI citation rates typically takes a few months of sustained work, not weeks, and a budget needs to survive that runway
- For a Series A company, FirstMotion’s published prices put a strategy phase plus six months of retainer from £26,995 (+VAT), as set out in the Series A example below
- Vetting comes last: confirm prompt mining ability, B2B SaaS experience, and answer-first content methodology before signing
- A companion checklist exists for the deep technical vetting questions; this guide focuses on the objective-setting and budgeting work that has to happen first
Set AI search objectives before you talk to any agency
“We want more AI visibility” isn’t an objective. It’s a direction. Every agency proposal will claim to deliver it, and you’ll have no way to tell whether the one you signed actually did, because nothing was specific enough to fail against.
A usable objective names the platform, the query type, and the comparison point. “Appear in ChatGPT and Perplexity answers for security and compliance comparison queries where we currently lose out to [named competitor]” is something a proposal can be scoped against and a report can be measured against. “Improve our AI search presence” is not.
Work through three layers before you price anything:
- Platform layer — which AI surfaces actually matter to your buyers: Google AI Overviews, ChatGPT, Gemini, Claude, Perplexity. Not all of them carry equal weight for every B2B category, and platform choice changes both scope and cost.
- Query-type layer — the shape of the prompts you need to win. Category-definition queries (“what is [category]”), comparison queries (“[you] vs [competitor]”), and shortlist queries (“best [category] for [use case]”) each require different content and different tracking.
- Competitive layer — where you’re currently invisible against named competitors who are cited. This is the gap that turns “improve visibility” into a specific, trackable target.
A short worksheet makes this concrete:
| Objective element | Weak version | Usable version |
|---|---|---|
| Platform | ”AI search" | "ChatGPT and Google AI Overviews” |
| Query type | ”Relevant queries" | "Comparison queries against [competitor]“ |
| Baseline | ”We’re not visible" | "Zero citations across 40 tracked prompts” |
| Target | ”Get more visible" | "Cited in 12 of 40 tracked prompts within two quarters” |
Once objectives look like the right-hand column, the KPIs that actually matter for a GEO campaign become the measurement layer sitting on top of them. Citation rate and AI share of voice only mean something once you’ve defined which prompts you’re tracking them against.
Build a budget around GEO’s real cost drivers, not a legacy SEO retainer
Published GEO pricing varies depending on who you ask, and most of the numbers circulating online come from agencies describing their own packages rather than an independent market study. Our London GEO agency guide shows which agencies publish rates and which quote against scope, and FirstMotion’s own rates are on the pricing page. Based on the proposals we have seen, GEO programmes typically fall between £3,000 and £20,000 per month depending on scope; that is a FirstMotion estimate, not an independent benchmark. Use these as reference points, then size your budget against the variables that actually drive GEO cost up or down.
A legacy SEO retainer is usually priced against content volume and link-building effort. GEO work is priced against a different set of deliverables: prompt research and content mapping across platforms, restructuring existing pages into answer-first formats, building comparison and category content that doesn’t currently exist, and ongoing citation tracking across however many platforms you defined in the objectives stage. A programme covering four platforms and a full comparison content library costs meaningfully more than one covering a single platform and a handful of priority queries.
| Budget driver | Scales cost up | Scales cost down |
|---|---|---|
| Platform coverage | Tracking and optimising across 4+ AI platforms | Focused on one or two priority platforms |
| Content scope | Building new comparison and category pages from scratch | Restructuring existing high-performing content |
| Tracking cadence | Weekly prompt-level monitoring across competitors | Monthly or quarterly baseline checks |
| Team composition | Dedicated strategist plus technical and content resource | Single consultant managing the full scope |
| Timeline | Compressed timeline with parallel workstreams | Phased rollout across quarters |
Timeline is the driver most B2B teams underbudget for. GEO campaigns rarely show meaningful citation movement inside the first few weeks, because AI platforms re-crawl, re-evaluate, and re-cite content on their own schedule, not yours. A budget sized for a one-quarter sprint and then cancelled if nothing moves in month one is a budget that was never going to prove anything either way. Size the commitment for a few months of sustained work before you evaluate results, and build the reporting cadence to match, so you’re watching leading indicators like citation rate move before you look for the commercial outcomes covered in how to prove the business impact of AI search visibility.
If a vendor gives you a number without asking about platform coverage, content scope, or tracking cadence first, that’s worth noting. A number that isn’t built from your objectives is a guess with a decimal point.
What this looks like for a Series A company
A Series A team rarely has spare marketing headcount, so the usual shape is a fixed-scope strategy phase followed by a monthly retainer. The figures below use FirstMotion’s published prices so you can check the arithmetic. They are illustrative and not a quote, because your retainer is scoped to what you actually need.
| Stage | Illustrative cost (+VAT) |
|---|---|
| Strategy phase, about 4 to 8 weeks | From £5,995, scaling with locations and page count to a maximum of £11,995 |
| Growth retainer | From £3,500 a month |
| Strategy phase plus 6 months of retainer | From £26,995 |
| Strategy phase plus 12 months of retainer | From £47,995 |
The totals are the strategy phase starting price plus six or twelve months at the starting retainer price. A larger scope raises both figures, and the roadmap from the strategy phase is yours to keep.
In our view, a Series A budget should buy these in order:
- A baseline and prompt map. Know where you stand against named competitors across the AI engines your buyers use before committing to a programme.
- Accuracy. Check how AI describes you and fix wrong or confused descriptions at the source, because every engine that retrieves the same source repeats the same error.
- Answer-first pages for the prompts that decide shortlists. Comparison, alternatives, pricing and use-case pages that answer the questions buyers ask.
- Third-party presence. Review platforms, lists and editorial coverage that engines retrieve and trust.
- Reporting tied to pipeline. Leads and pipeline next to citation data, so a board sees more than a visibility score.
Broad tracking across every engine, and high-volume content for its own sake, can wait until you can act on the gaps. In our experience, early citation gains often appear within 8 to 12 weeks of the strategy phase finishing, and share of voice tends to compound over three to six months. We do not guarantee specific results. AI search work is also premature for pre-product companies, because third-party mentions depend on a live product with real users.
Vet agencies against your objectives, not a generic checklist
Once objectives and budget are set, vetting is a shorter exercise than most guides make it sound. Ask a handful of pointed questions rather than working through an exhaustive checklist at this stage:
- Can they show a prompt mining and content mapping process? Ask how they identify which prompts your buyers actually use, not just which keywords rank in Google. If the answer sounds like traditional keyword research with “AI” added to the label, that’s a signal.
- How do they approach answer-first content and comparison pages? GEO content needs a different structure from a traditional blog post: direct answers near the top, explicit comparisons, and content that reads well when a language model extracts a passage out of context.
- Do they have specific B2B SaaS experience? Long sales cycles, multiple buyer personas, and technical differentiation change what “visibility” needs to mean. An agency whose case studies are all ecommerce or local business work is starting from a different playbook.
- Will they scope against the objectives you already defined? A proposal that ignores the platform, query-type, and competitive targets you set in the first stage of this process isn’t listening.
This is deliberately a short list. Deep technical vetting, including how to score agencies against a fuller set of criteria, is covered in our evaluation scorecard for B2B SaaS GEO agencies, and in our companion guide on how to evaluate a GEO agency for B2B SaaS, which walks through the full technical vetting checklist in more depth than makes sense to duplicate here.
Objectives, budget, and vetting work in that order for a reason. An agency can only be evaluated against something concrete, and a budget only makes sense once you know what it needs to buy. Skip either step and the vetting conversation turns into guesswork dressed up as due diligence.