How to evaluate an AI search marketing agency

Start with proof, not a pitch deck

The fastest way to separate a credible AI search marketing agency from a rebranded SEO shop is to ask them to run a handful of real prompts against your brand right now — "best [category] for [use case]," "alternatives to [competitor]" — and show you exactly what ChatGPT, Perplexity or Gemini currently say. If they can't do this live, in the first conversation, they haven't built the muscle yet.

This matters because AI search behaves nothing like a keyword ranking report. A brand can rank well on Google and be invisible or misrepresented in an AI-generated answer, and the only way to know is to actually test it.

It's also worth noting how the agency talks about failure cases. One that can describe a prompt cluster where their work didn't move the needle, and why, is showing more real experience than one that claims universal success across every engagement.

The evaluation checklist

Beyond the live test, look at how the agency structures its own service. Vague "AI marketing" packages that blend paid and organic without separate line items are a warning sign — the skills, timelines and budgets for each are genuinely different.

• Do they separate GEO (organic citation work) from ChatGPT Ads management in scope and pricing?
• Do they check technical access for AI crawlers — OAI-SearchBot, ChatGPT-User, PerplexityBot, Google-Extended — not just traditional SEO crawlers?
• Do they track named competitor share of voice, not just your own mention count?
• Do they refuse to guarantee a specific ranking or AI output?

That last point is counterintuitive but important: no agency controls what a model generates, and one that promises a fixed outcome is either naive or dishonest.

It also helps to ask how quickly the agency can react when a model update visibly changes citation behavior — a same-week response plan is a good sign; "we'll check next month's report" is not.

What Suggesting.ai does differently during evaluation

Suggesting.ai runs the free audit before any sales conversation about pricing. It covers brand and AI presence across ChatGPT, Perplexity, Gemini and Google AI Overviews, delivered in 48 hours, so a CMO evaluating agencies gets a concrete artifact to compare against other pitches rather than a slide deck of promises.

The idea is simple: when ChatGPT is suggesting a vendor, the evaluation process itself should already be suggesting whether this agency knows what it's doing.

It's also reasonable to ask how the agency stays current as OpenAI, Google and Perplexity each change their own ad and crawler policies, since this space moves quickly enough that a static playbook from even a year ago is already outdated.

Worked example: evaluating for a trading platform

A trading platform comparing three agencies should ask each to test the same prompt set: "which platforms are licensed in [jurisdiction] and support MT5," "lowest spread broker for scalping." Compare not just whether the platform is mentioned, but whether the regulatory and feature facts each agency's audit surfaces are accurate — a wrong regulatory claim getting cited by an LLM is a compliance risk, not just a marketing miss.

The agency that flags data accuracy issues unprompted, rather than just counting mentions, is the one that understands what's actually at stake in regulated finance.

For a regulated brand, ask specifically how the agency verifies facts before publishing anything citable — a single wrong regulatory claim repeated by an AI engine can create real legal exposure, not just a marketing embarrassment.

Reporting cadence to expect after signing

Once evaluation moves to a retainer, expect monthly reporting on citation frequency by engine, share of voice against named competitors, and — where paid runs — cost per click through OpenAI's Ads Manager under CPM, CPC or oCPC bidding. Studies on AI-referred traffic report conversion rates well above average organic Google traffic, so referral quality should appear in reporting too, not just citation counts.

An agency that can't commit to this cadence during evaluation likely won't deliver it once you're a client.

Ask specifically whether reporting distinguishes between an engine simply mentioning your brand versus recommending it as the answer, since the two carry very different weight with a buyer reading the response.

Common mistakes CMOs make during evaluation

The most frequent mistake is judging agencies purely on their sales pitch polish rather than asking to see live, unscripted output for your own brand. A slick deck full of screenshots from other clients tells you almost nothing about how the agency will actually handle your specific category and competitors.

A second mistake is skipping the technical review entirely — asking only about content strategy while never checking whether the agency understands crawler access for OAI-SearchBot, PerplexityBot and Google-Extended. Without that access, none of the content strategy in the world gets seen by the engines that matter.

Ask, too, whether the audit findings get shared in full or summarized selectively — a raw, unfiltered look at exactly what each engine currently returns is far more useful for evaluation than a curated highlight reel.

Involving other stakeholders in the evaluation

Sales and customer success teams often know which competitors come up most often in real deals, and that input should shape which prompts get tested during evaluation, not just marketing's assumptions about the category. A finance or legal reviewer should also weigh in when the agency's proposed content touches regulatory claims, since accuracy there carries real compliance risk beyond marketing performance.

The most reliable comparison point across every candidate is simply whether the audit itself was free and delivered quickly, since an agency unwilling to demonstrate value before a contract is asking for trust it hasn't yet earned.