How to Choose an AI Search Optimization Agency

Start with what the category actually covers

An AI search optimization agency should be able to explain, without jargon, the difference between three distinct services: paid placement inside ChatGPT's ad auction, organic generative engine optimization (GEO) that earns citations in AI answers, and ongoing brand-presence auditing. Many agencies rebrand old SEO packages with AI language and can't actually speak to how citation selection works inside a model's retrieval layer. That gap usually shows up the moment you ask a follow-up question — a genuine practitioner can go two or three levels deeper, while a rebranded SEO shop repeats the same talking point.

If a sales call can't clearly separate these three services and explain how each is measured differently, treat that as a warning sign, not a nuance. This is a pattern worth watching closely, since the gap between brands that adapt early and those that wait tends to compound rather than stay fixed. That distinction sounds subtle in the abstract, but it shows up clearly the moment two competing brands are compared side by side in the same AI answer.

The evaluation checklist that actually matters

Beyond the sales deck, ask for specifics: which AI engines do they track (ChatGPT, Perplexity, Gemini, Google AI Overviews, Copilot)? How often do they re-audit content? Do they touch technical crawlability — allowing OAI-SearchBot, ChatGPT-User, and PerplexityBot while separately deciding on training crawlers like GPTBot? An agency that skips the technical layer is only doing half the job, since a brand can have perfectly written content that's still invisible to AI crawlers because of a robots.txt misconfiguration nobody checked. Teams that treat this as a one-time project rather than an ongoing discipline usually see early gains fade within a couple of quarters. Getting this right early avoids a costly redo later, once a brand has already built months of content on the wrong foundation.

• Ask which specific AI engines they measure, not just "AI search" generally
• Confirm they audit crawler access separately from content strategy
• Request a sample report from an existing client (anonymized is fine)
• Clarify whether pricing is retainer, project, or performance-based

Red flags that should end the conversation

No legitimate AI search optimization agency can guarantee a specific ranking or guaranteed appearance in a ChatGPT answer — model outputs are non-deterministic and change with every retraining or retrieval update. Anyone promising a guaranteed top mention is either misunderstanding the technology or misrepresenting it. Similarly, be wary of agencies that can't explain how they'd measure success beyond "mentions" — mentions without context (sentiment, position, accuracy) tell you little, since being mentioned unfavorably next to a competitor is a very different outcome from being the recommended choice.

Watch for vague case studies too. If an agency can't name the client, the prompt tested, and the before/after citation state, the result may not be reproducible for your brand. The underlying mechanics differ by platform, but the core principle — write for direct extraction, not persuasion alone — holds across all of them. The difference tends to compound: a small early edge in citation share often grows rather than shrinks as more buyers repeat the same research pattern.

What Suggesting.ai does differently for evaluation

Suggesting.ai's process starts with a free brand and AI presence audit delivered in 48 hours — before any commercial conversation about retainers. That audit shows exactly where your brand currently appears (or doesn't) across ChatGPT, Perplexity, Gemini, and AI Overviews for the prompts your actual buyers ask, plus a crawlability check against the citation bots that matter. Prospective clients get to see, in writing, exactly which competitors are winning the citations they wanted before agreeing to spend a dollar fixing the gap.

The idea is simple: when ChatGPT is suggesting a vendor in your category, you should see the evidence for whether that's you before you spend a dollar on the fix. None of this replaces good judgment about your own market; it simply gives that judgment a new channel to act through.

Worked example: choosing an agency as a forex broker

A licensed forex broker evaluating agencies should specifically ask how the agency handles regulatory facts — licensing jurisdiction, spread disclosures, leverage limits — since these are exactly the specific, verifiable claims that make AI models trust and cite a source. An agency with no financial-services experience may default to generic marketing language that AI models are less likely to surface for a compliance-sensitive query like "which broker is licensed to operate in Saudi Arabia." A broker's compliance team should also be part of the vetting conversation, since any AI-facing content still has to satisfy the same regulatory review as everything else the brand publishes.

Ask for a sample audit on a competitor broker before committing, so you can see the agency handle regulated, comparison-driven content in practice. Smaller teams in particular benefit from this kind of prioritization, since it prevents scarce content resources from being spread too thin.

Pricing and what it should include

Market pricing for AI search/GEO retainers runs from roughly $2,000/month for a single-market, narrower scope up to $10,000+/month for enterprise engagements that include digital PR and multi-market coverage. Any agency's quote should map clearly to deliverables — number of pages optimized, audit cadence, reporting frequency — rather than a flat number with no breakdown. A quote with no itemization is difficult to benchmark against a competing proposal, and even harder to defend internally if a finance team later asks what the retainer actually bought.

Suggesting.ai scopes and prices every engagement after the free audit, once the actual gap between your current AI presence and your competitors' is visible. It's worth revisiting this work on a regular cadence, since competitor content and model behavior both continue to shift over time.