## The short answer

Generative engine optimization services cover six kinds of work: technical retrievability, on-page answer structure, entity and schema, content, earned authority, and measurement. The label is not standardised. Two proposals at the same price routinely buy different halves of that list, so get the deliverables named in writing before you compare a single number.

**Key takeaways**

- The evidence points at the two ends of the list. Retrieval failures drive over 70% of chatbot errors, and 84% of AI citations point at earned media. So technical retrievability and earned authority carry most of the load. The middle of a typical proposal carries least.
- Three line items that appear on GEO proposals are things Google says are unnecessary: an llms.txt file, pre-chunked content, and AI-specific rewrites of pages you already have.
- Some measurement you are quoted for is free. Microsoft publishes your Copilot citation data in Bing Webmaster Tools at no cost, so ask what a paid report adds on top.
- Almost nobody publishes a scope. One provider in our check publishes both a GEO price and a named deliverable list, which is the exception in this category.
- The cost nobody quotes is your own team’s time. Unless the contract says otherwise, implementation lands on your developers and writers, and that line is usually missing.

A note on where this comes from. I spend my time on why some content gets cited and some does not. ...

## What are generative engine optimization services?

Generative engine optimization services are paid work to make a brand appear, and be cited, in answers produced by generative engines rather than in a list of links. In practice that means a bundle of technical, editorial and public-relations work, plus the measurement to tell whether any of it landed.

## The six things a GEO engagement actually delivers

Here is the inventory. Every proposal we are asked to review draws from these six groups, and the useful question is which ones a given provider is actually staffing.

**Technical retrievability.** Crawl access for AI agents, server-rendered answers, clean robots rules, site structure a machine can follow. This is the plumbing, and it is covered properly in [crawlability for AI](/content/blog/crawlability-for-ai/index.html).

**On-page answer structure.** Front-loaded H1s, question-shaped headings, direct answers beneath them, FAQ blocks that earn their place. The practical version is in [how to structure content for AI citation](/content/blog/how-to-structure-content-for-ai-citation/index.html).

**Entity and schema.** Consistent naming, organisation and article markup, internal links whose anchors describe the destination. Our view on what markup still earns its place sits in [schema markup](/content/blog/schema-markup/index.html).

**Content.** New pages, refreshes, and original material a model cannot reconstruct from someone else’s page.

**Earned authority.** Third-party coverage, comparison pages, communities, and the seeding work behind [getting mentioned and cited in LLMs](/content/blog/llm-seeding-an-ai-search-strategy-to-get-mentioned-and-cited/index.html).

**Measurement.** Prompt tracking, cited-URL reporting, competitor share of voice, and the honest statement of what cannot be attributed.

**Where this falls short:** the grouping is ours, not an industry standard, so a provider may slice the same work differently. Ask them to map their proposal onto these six and watch which ones come back thin.

## Which deliverables are load-bearing, and which are decoration

This is the part no pricing guide answers, and the published evidence is unusually clear about it.

A Stanford-led evaluation published in May 2026 found that “retrieval, not reasoning, failures drive over 70% of all errors” in commercial chatbots. ...

## Three line items Google says you do not need

Now the part that should save you money, and it comes from Google rather than from us.

In May 2026 Google published consolidated guidance on optimising for generative AI in Search, and it retired several things that still appear as billable GEO deliverables.

Its wording, verbatim.

- On machine-readable files, including [llms.txt](/content/blog/llms-txt-explained/index.html): “You don’t need to create new machine readable files, AI text files, markup, or Markdown to appear in Google Search.”
- On chunking: “There’s no requirement to break your content into tiny pieces for AI to better understand it.”
- On rewriting for machines: “You don’t need to write in a specific way just for generative AI search.”
- On markup: “Structured data isn’t required for generative AI search, and there’s no special schema.org markup you need to add.”

If a proposal bills separately for any of those four as an AI-specific deliverable, ask what it buys beyond what Google says is unnecessary.

Then hold the other half of the thought, because a literal reading goes too far. Google is describing Google. Schema still earns its place for rich results and entity clarity, and other engines publish no equivalent guidance at all, so we keep schema on client sites. We just stopped selling it as an AI citation lever.

**Where it falls short:** this is documentation, not a ranking commitment. It tells you what is unnecessary for Google. It does not promise what works anywhere else.

## What you can already get for nothing

Ask what a paid measurement line adds on top of the free baseline, because there is one now.

Microsoft shipped AI Performance in Bing Webmaster Tools as a public preview in February 2026. It reports which of your URLs get cited in AI answers and which queries triggered them, across Copilot, Bing AI summaries and select partner integrations. It costs nothing.

That does not cover ChatGPT, Perplexity or Google, so it is a baseline rather than a solution. ...

## How we scored the deliverables

Four criteria, weighted before we ordered the stack. This is also the test I would apply to any line item on a proposal.

| Criterion | Weight | What a deliverable has to demonstrate |
| --- | --- | --- |
| Published evidence that it moves citation | 40 | A 2026 primary source connects this work to being retrieved or cited, rather than a vendor asserting a best practice |
| Removes a known failure mode | 25 | It fixes something that demonstrably stops a page being found or used, instead of improving something already working |
| Not contradicted by engine guidance | 20 | No engine has publicly stated the work is unnecessary, and where one has, the proposal explains why it is still worth doing |
| Verifiable output | 15 | You can tell it was done by looking at something other than the provider’s own report |

## GEO services at a glance, by scope

| Scope | What you should get | Published price | Where it falls short |
| --- | --- | --- | --- |
| One-off audit | A findings document across the six groups, with prioritised fixes and no implementation | Rarely published. Consulting rates in the wider market run $150 to $300 an hour | Ends at the report. Organic work compounds, so an audit with nobody to implement it ages fast |
| Monitoring only | Prompt tracking, cited URLs, competitor share of voice. Software, no people | Published and cheap. Platform tiers run from free to roughly $500 a month | Sees the problem and fixes none of it, and the entry tiers meter prompts tightly |
| Retainer, published scope | Named deliverables across most of the six groups, with volumes and an implementation owner | WebFX publishes GEO from $3,000 a month, with named deliverables including LLM monitoring, competitor benchmarking and performance tracking | Tiered scopes fit unusual sites badly, and any retainer can drift into reporting |
| Retainer, unpublished scope | Whatever the discovery call produces | Not published by most providers in the category | You cannot compare scopes before committing to a sales process |
| Pepper, separate row | All six groups, with the platform your team runs and a growth team attached doing the work alongside them | Not published | We do not publish pricing, so budget discovery is a conversation rather than a page |

## What you pay, and where the real cost hides

Three costs, and proposals reliably name only the first.

**The fee.** Published GEO prices are scarce. The verified example above starts at $3,000 a month, and monitoring software runs from free to a few hundred. Beyond that, most of this category quotes after a call.

**Your own team’s time.** This is the line that goes missing. Unless the contract says the provider ships changes to your site, your developers and writers absorb the implementation. A proposal full of technical fixes can quietly cost more internally than externally.

**The earned-media half.** If 84% of citations come from third parties, then coverage, original research and digital PR are not an optional upsell. They are most of the opportunity, and they are the slowest and most expensive part of the list.

## What a good first 90 days looks like

Sequence matters more than volume here, because the groups depend on each other. Fixing retrievability after commissioning twenty articles wastes the articles.

## What to ask before you sign

I would not open with price. I would ask the provider to map their proposal onto the six groups above and say which ones they are staffing. ...

## What nobody should promise you

Nobody should promise a citation or a position in an AI answer. Google advises against exactly that kind of guarantee, because no external party has access to the ranking systems.

**What is not here.** No industry-wide figure for what GEO services cost, because we found no primary research measuring it. ...

## Frequently asked questions

**What do generative engine optimization services include?**

Six groups of work: technical retrievability, on-page answer structure, entity and schema, content, earned authority, and measurement. The term is not standardised, so ask any provider to name which groups they are staffing and which they are not.