AEO pricing pages tend to answer the wrong question for an agency. They tell a business owner what an AEO vendor charges. An agency owner needs to know something else: how to price AI search work inside the retainers it already sells, what the work actually costs to deliver, and where the margin sits when a white-label partner does part of it.
AEO pricing for agencies comes down to three things: the pricing model (one-off audit, monthly retainer, or an add-on line inside an existing SEO retainer), the cost drivers behind the work, and the margin you set on top. The cost drivers are:
- Prompt count: how many buyer questions are tracked per client.
- Engines: how many AI assistants are tested.
- Markets: how many cities or regions need their own prompt set.
- Re-test frequency: how often the full set is re-run.
- Implementation: who fixes the gaps, and how many there are.
- Reporting: the monthly client report in the agency’s template.
Your margin goes on top of all six.
The rest of this article shows how to price from them.
The common AEO pricing models
| Model | What the client buys | Best for | Watch out for |
|---|---|---|---|
| One-off audit | A baseline: prompt set, engine results, gap diagnosis, and a ranked plan | Answering a client who is asking now; testing demand before committing | It sells a snapshot. Without re-tests, there is nothing to report next month |
| Monthly retainer | Ongoing re-tests, plan updates, and implementation | Clients where AI visibility is a standing priority | Scope creep, because “AI search” can absorb any task |
| Add-on line | AEO work priced as a line inside an existing SEO retainer | Agencies with established SEO clients | Under-pricing it as a free extra, which trains the client to expect it for nothing |
Which model to lead with depends on where the agency is today:
- No AEO offer yet: lead with the one-off audit. It tests demand on one account without committing the team to monthly delivery.
- Established SEO retainers, AEO questions coming in: add it as a line inside the existing retainer, scoped from an audit.
- AEO already a standing priority for a client: a separate monthly retainer, so the scope and the reporting have their own line.
For most agencies that means an audit first, then an add-on line. The audit gives the client a baseline and gives the agency a scoped plan, so the monthly price is set against real work instead of a guess.
What drives AEO cost
Know these before you quote.
- Prompt count. Each client needs a buyer prompt set, usually 10–20 prompts for one local service business in one market. Every prompt is run, recorded, and diagnosed, so more prompts mean more hours every month.
- Engines. Testing ChatGPT, Gemini, Perplexity, and Google AI Overviews separately multiplies the runs and the diagnosis, because each engine can draw on different sources.
- Markets. A business that serves three cities needs a prompt set per market. Multi-location clients are not one audit with a longer list; they are several audits.
- Re-test frequency. Monthly re-tests make sense, because AI answers vary between runs and a trend needs repeated measurement. Each re-test is a full run of the prompt set.
- Implementation. This can be the largest and most variable cost: rewriting pages with direct answer blocks, fixing schema, correcting entity details across profiles and directories, and working to get the client onto the third-party lists the engines cite.
- Reporting. A client-ready monthly report with trends, share of voice, and next actions takes time, especially in the agency’s own template.
The first four drive the cost of measurement and planning. The fifth drives the cost of delivery. The sixth, reporting, sits with measurement. Keep them as separate lines in your own costing, even if the client sees one price.
A scoping example: counting the work before you price it
Hours and rates differ by agency, so count the work first and apply your own numbers to it. The arithmetic below follows directly from the method; it is not a market benchmark.
Scoping example. Fictional client: a plumber serving one city.
| Scope item | Calculation | Monthly volume |
|---|---|---|
| Prompts | 15 buyer prompts | 15 |
| Engines | ChatGPT, Gemini, Perplexity, AI Overviews | × 4 |
| Runs per prompt | 3 runs, because answers vary | × 3 |
| Answers to record | 15 × 4 × 3 | 180 answers a month |
| Same client, three cities | One prompt set per market | 540 answers a month |
Every answer is read, recorded as named, cited, or absent, and checked for its sources. That is why prompt count and markets drive cost so directly. Put your own minutes per answer and your own hourly cost against the volume. Then add the implementation the audit turns up, quoted task by task:
- Direct answer blocks written or rewritten on priority pages.
- Schema added or corrected to match each page.
- Entity details reconciled across the profiles and directories the engines cite.
- Listings created or completed on missing citation sources.
- Outreach to best-of lists the client should be on.
Measurement plus implementation is your cost floor. Price from there.
Why published AEO prices vary so much
Published AEO price ranges often come from vendors selling AEO, and they can cover very different scopes. Some are self-serve software subscriptions that run prompts and report mentions. Some are agency retainers that include content, technical fixes, and off-site work.
That is why a published range is a poor anchor for your own price. Before comparing any figure, check three things: whether implementation is included, how many prompts and engines are covered, and whether re-tests are part of the price. Then price from your own cost drivers, not from someone else’s rate card.
Pricing AEO as an add-on to an existing SEO retainer
AEO is easiest to sell inside the retainer the client already pays for. The client already trusts the agency with search and is already asking about AI answers.
Three ways to structure it:
- A fixed add-on line. A set monthly amount for a defined scope: a named number of prompts, named engines, one market, monthly re-test, and a set number of implementation hours.
- Tiers by scope. Tiers set by answer volume, as in the scoping example above. A single-location client sits in the first tier; a three-city client, at three times the answers, moves up because the work does.
- Audit credit. Sell the audit as a fixed-price project, then credit part of it against the first months of the add-on if the client continues.
Whichever structure you use, write the scope into the retainer: the prompt count, the engines, the markets, and what implementation is included. AEO without a written scope turns into “can you also look at why we are not in ChatGPT for this” every week.
Setting your margin on white-label AEO
When a white-label partner builds the prompt set, runs the engines, writes the plan, and re-tests monthly, your cost has three parts: the partner’s fee, your team’s implementation hours, and account management. Your price to the client is built on all three:
Client price = partner fee + (implementation hours × your internal hourly cost) + account management cost + your margin
A few rules make this work:
- Price the implementation separately in your head. The partner fee is predictable. Implementation is not, and it is where under-pricing is most likely.
- Do not pass the partner fee through at cost. Your agency carries the client relationship, the reporting, and the risk. The margin pays for that.
- Set the price to the client yourself. In a white-label arrangement, the partner invoices the agency, not the client, and the agency decides what the client pays.
- Re-check margin after the audit. The audit shows how much implementation the client actually needs, which is the number that decides whether the add-on price holds.
Pitfalls that cost agencies money
- Selling guarantees. No one controls what an AI engine says, and answers change between runs. A guaranteed placement is a promise the agency cannot keep, and it turns a normal month-to-month variation into a refund conversation.
- Single-screenshot reporting. One good answer is not proof once the client runs the same prompt and gets a different result. Report the trend across a fixed prompt set.
- Pricing the audit as a loss leader. A free audit sets the value of the work at zero. A fixed-price audit is a smaller commitment than a retainer, so there is no need to give it away.
- Unlimited scope. “AI search optimization” with no prompt count, engine list, or market is a retainer that grows every month while the price stays flat.
- Ignoring implementation. The fixes are usually where the hours go. Price for who will do them.
FAQ
How much does AEO cost?
It depends on scope: the number of prompts, engines, and markets, how often results are re-tested, and how much implementation is included. A software subscription, a one-off audit, and a full-service retainer are all sold as AEO and are priced very differently, so compare scope before comparing price.
Should an agency charge separately for AEO?
Yes. Folding AEO into an SEO retainer at no extra cost trains the client to expect it for free. Price it as a defined add-on line or a separate project with a written scope.
What is included in white-label AEO pricing?
Look for the prompt set, engine testing, gap diagnosis, a ranked action plan, implementation briefs, and monthly re-tests, delivered in the agency’s branding. Implementation is usually the agency’s own team’s work and priced separately.
Who sets the price in a white-label AEO partnership?
The agency. The partner invoices the agency, and the agency sets the price its client pays.
Price it from a real baseline
Price AEO from the real work. SearchKata runs a fixed-price audit and roadmap on one client site, in your template. You set the price to your client, and SearchKata invoices you. For what the implementation side involves, see how to get cited by ChatGPT, and for how the partnership works, see white-label AEO.
Leave a Reply