Generative engine optimisation (GEO) has gone from a niche experiment to a real budget line item for e-commerce brands and service businesses alike. With ChatGPT, Perplexity, and Gemini now sending measurable traffic and influencing purchasing decisions, the question is no longer "should we do this?" but "what does it actually cost and what do we get for our money?"
The honest answer is: it depends enormously on who you hire, what they actually do, and how well your site is currently structured for AI crawlers. Let's break it down properly.
What GEO work actually involves
Before you can evaluate pricing, you need to understand what you're paying for. Generative engine optimisation is not simply a rebrand of traditional SEO. The goals overlap in places, but the technical work is distinct.
Traditional SEO focuses on ranking signals: backlinks, page speed, keyword density, meta tags. GEO focuses on something different: making your content machine-readable so that large language models (LLMs) can extract, trust, and cite your information when answering user queries.
In practice, that means work across several areas:
- Schema markup implementation - Adding structured data in JSON-LD format so AI systems understand exactly what your products, services, reviews, and business details are. This is the foundation of almost all GEO work.
- Content restructuring - Rewriting or reformatting content so it answers specific questions clearly. LLMs prefer direct, factual sentences over flowery marketing copy.
- Entity building - Ensuring your brand is clearly defined across your site, including consistent use of organisation schema, author schema, and linked data that connects your brand to verifiable facts.
- Crawl access auditing - Checking that AI bots (GPTBot, PerplexityBot, ClaudeBot, and others) can actually access your site and are not being blocked by your CDN, robots.txt, or middleware.
- AI answer monitoring - Tracking how and when your brand appears in AI-generated responses, then iterating based on what's working.
A provider quoting you for "GEO" should be able to explain which of these they cover. If they can't, that tells you something.
GEO pricing tiers you'll actually encounter
The market in 2026 is fragmented. You'll find everything from £200 one-off audits to £5,000+ monthly retainers. Here's what each tier typically looks like in practice.
Entry level: £150 to £500 (one-off audits and reports)
At this price point, you're usually getting a report. Someone runs your site through a schema validator, checks your robots.txt against known AI crawler user agents, and hands you a document listing what's missing. Some providers will include a priority list of fixes.
This is useful if you have an in-house developer who can implement recommendations, or if you're simply trying to understand your current position. It is not useful if you want the work done.
Quality varies wildly here. Some agencies sell "AI SEO audits" that are really just Screaming Frog reports with a different cover page. Ask to see a sample before buying.
Mid-tier: £500 to £2,000 per month
This is where most small to mid-sized e-commerce brands will land. For this budget you should expect schema implementation (not just recommendations), some level of content optimisation, and monthly reporting on AI visibility metrics.
On Shopify specifically, good providers at this tier will implement product schema, offer schema, review schema, and organisation schema across your catalogue, plus structured FAQ content on key landing pages. That work alone can meaningfully shift how AI shopping tools present your products.
Be cautious of providers who promise "AI-first SEO" at this price but are really just adding a few FAQ blocks and calling it done. Ask what schema types they implement, how they test them, and how they measure success.
Premium tier: £2,000 to £6,000+ per month
At this level you're typically getting a fully managed service. Think ongoing schema maintenance as your product catalogue changes, continuous content adaptation based on how LLMs are responding to your category, AI monitoring dashboards, and proactive recommendations as the AI search landscape shifts.
For brands selling in competitive categories (supplements, electronics, fashion, finance adjacent products) this level of ongoing management can be genuinely worthwhile. AI model updates happen frequently. What worked in January may need adjustment by April.
At FlinnSchema's pricing page you can see exactly what's included at each tier, which is worth reviewing as a benchmark for what properly scoped GEO work looks like in practice.
Enterprise: bespoke pricing
For large catalogues (10,000+ SKUs), multi-market brands, or businesses where AI-driven revenue is already measurable and significant, bespoke engagements make more sense than packaged tiers. These typically involve a scoping call, a technical audit, and a proposal built around your specific situation.
What drives the price up or down
Several factors push the cost of GEO work higher or lower for any given business.
Catalogue size
A Shopify store with 50 products is a very different job to one with 5,000. Schema needs to be implemented at scale, ideally through automated templates, and tested across a representative sample. More products means more complexity and more ongoing maintenance.
Platform and technical access
WordPress gives providers fairly direct access to implement JSON-LD. Shopify is more constrained but workable. Custom or headless platforms can add significant complexity and cost. If your site is built on a proprietary CMS, expect to pay more for implementation.
Current state of your structured data
If you're starting from zero, there's more upfront work. If you already have some schema in place but it's incomplete or malformed, the provider needs to audit what's there before touching anything. Running a free AI visibility audit before you engage any provider is a smart first step. It gives you a baseline and prevents you from paying for work you've already done.
Content vs. technical split
Some GEO providers are primarily technical (schema, crawl access, structured data). Others lead with content strategy. The best ones do both. If a provider only does one, you'll likely need to supplement with the other, which adds to your total cost.
Red flags in GEO pricing proposals
The GEO market is new enough that there are providers selling the idea of AI optimisation without the technical depth to deliver it. A few things to watch for:
- "We'll get you featured in AI answers" guarantees. No one can guarantee placement in AI-generated responses. LLMs make probabilistic decisions and update constantly. Anyone promising specific rankings is overselling.
- No mention of schema types. If a proposal talks about "AI-optimised content" but never mentions JSON-LD, structured data, or specific schema types, ask what the technical implementation actually involves.
- Vanity metrics only. If reporting focuses on "AI readiness scores" from proprietary tools with no connection to real business outcomes, push for clarity on how success is measured. You want to see brand mention tracking in AI responses, referral traffic from AI sources, and ideally conversion data.
- Locked-in long contracts with no performance milestones. Twelve-month contracts with no review points are a risk in a fast-moving space. Reasonable providers build in quarterly reviews.
How to evaluate whether GEO investment makes sense for your business
Not every business needs a premium ongoing GEO retainer right now. Here's a rough framework for thinking about it.
If your customers are already using AI tools to research purchases in your category, GEO is worth prioritising. Run some test queries in ChatGPT and Perplexity for your main product types and see what comes up. If competitors are being cited and you're not, that gap is costing you.
If your category is still dominated by traditional search results in AI responses, you have a window to get in early before it becomes competitive and expensive.
If you're in a category where AI assistants actively recommend products (supplements, tech, home goods, software tools), the ROI case is much clearer. A £1,000 per month investment that results in consistent AI citations in purchase-intent queries can easily pay for itself.
The FlinnSchema client results page has real examples of what measurable improvement looks like after GEO work, which is worth reviewing before you build a business case internally.
Building a realistic 2026 GEO budget
For most e-commerce brands getting started with GEO in 2026, a sensible approach looks something like this:
- Start with a proper audit to understand where you stand. This costs £0 to £500 depending on whether you use a free tool or pay for a more detailed review.
- Invest in a one-off implementation sprint to get core schema in place across your key pages and products. Budget £500 to £2,000 depending on catalogue size and platform.
- Move to a lighter ongoing retainer (£500 to £1,000 per month) for monitoring, content iteration, and maintenance as your catalogue and the AI search environment both evolve.
Total first-year spend for a mid-sized Shopify brand: roughly £7,000 to £15,000, with the majority front-loaded in the implementation phase. That's comparable to what many brands spend on a single paid social campaign, but with compounding returns as AI models continue training on your structured content.
If you want to understand what the work looks like before committing, booking a walkthrough call is the lowest-friction way to get a clear picture of what's involved for your specific site.
Frequently Asked Questions
Is generative engine optimisation the same as SEO?
They overlap but are not the same. Traditional SEO targets Google's ranking algorithm through signals like backlinks and keyword usage. GEO focuses on making your content understandable and citable by LLMs like ChatGPT and Perplexity. The technical methods are different: GEO relies heavily on structured data, JSON-LD schema, and content clarity rather than link building.
How long does it take to see results from GEO work?
It varies. Schema implementation can be picked up by AI crawlers within days of going live, since bots like GPTBot crawl frequently. Seeing consistent brand citations in AI responses typically takes four to twelve weeks, depending on how competitive your category is and how much content your site has. Monitoring from day one is important so you can track progress and adjust.
Can I do generative engine optimisation myself?
Some of it, yes. Adding basic JSON-LD schema to key pages is well-documented and doable if you're comfortable with code. Platforms like Shopify have apps that handle some schema automatically. Where it gets more complex is in testing, scaling across large catalogues, monitoring AI responses systematically, and adapting as LLM behaviour changes. Most brands find a hybrid approach works well: do what you can internally, bring in specialists for the technical heavy lifting.
What's the difference between a cheap and expensive GEO provider?
At the low end, you're often paying for a report and a recommendation list. At the higher end, you're paying for implementation, ongoing maintenance, and active monitoring. The other major difference is depth of technical knowledge. GEO done properly requires understanding how specific LLMs process structured data, which schema types influence which AI systems, and how to test and validate that your markup is actually working. That expertise takes time to develop and is reflected in pricing.