How Should a DTC Brand Actually Hire a GEO Agency?

Start by testing your own visibility, not the agency's pitch

Before evaluating any GEO agency, spend twenty minutes asking ChatGPT and Perplexity the questions your own shoppers would ask — "best sustainable running shoes under $150," "which skincare brand uses reef-safe sunscreen." If your DTC brand never appears, you now have a concrete baseline any agency's proposal has to move.

This step also filters out agencies pitching generic content packages that have nothing to do with your actual gap. A brand invisible because of thin review coverage needs a different fix than one invisible because its product feed lacks structured data. This upfront diagnostic work costs nothing but time, and it consistently separates founders who negotiate well from those who accept the first proposal at face value. It also pays to ask how an agency handles seasonal catalogs, since a holiday or limited-run product line needs faster iteration than an evergreen SKU. A short trial project — a single category rewrite, scoped to a few weeks — is often a better way to evaluate fit than a long conversation alone, since it shows real work rather than promised work.

What DTC-specific GEO work actually involves

Unlike a B2B software company, a DTC brand's AI visibility depends heavily on product feed structure, review-site presence, and comparison round-ups written by third parties. Models pull ingredient lists, materials, sizing, and price points from structured product data and cross-check them against what review sites and forums say. A feed audit alone often surfaces gaps that have existed for years without anyone noticing, simply because nobody was testing against AI prompts before. A brand selling internationally should ask specifically how the agency handles market-by-market differences in review platforms and comparison sites, since coverage that works in one country rarely transfers automatically. It's also worth remembering that a great GEO fit for one DTC category — beauty, apparel, home goods — may not transfer cleanly to another, since review platforms and comparison norms differ by vertical.

• Structured product schema (materials, price, availability) on every SKU page
• Active presence and accurate facts on the review sites your category actually uses
• Comparison content addressing "X vs Y" prompts for your top competitors

Questions to ask a candidate agency

Ask them to run a live test: type a real prompt from your category into ChatGPT and Perplexity while you watch, and have them explain why your brand does or doesn't appear. An agency that can diagnose in real time, rather than promising a generic audit deliverable in three weeks, understands the mechanics rather than selling a template.

Also ask how they'll handle your product feed specifically — many DTC brands run Shopify or a similar platform where feed structure is a template setting, not a content problem, and a GEO agency unfamiliar with that distinction will waste budget on blog posts instead. The same discipline applies whether the catalog has ten SKUs or ten thousand — the diagnostic scales, even if the fix work doesn't scale identically. Price is one input, but the more useful comparison across proposals is how each agency sequences the work — technical fixes first, content second, off-site third, or some other order they can defend. Ultimately the hiring decision should feel less like buying a marketing service and more like hiring a specialist who happens to understand both e-commerce platforms and how language models read the web.

What Suggesting.ai does for DTC catalogs

Suggesting.ai's free 48-hour audit tests a sample of your actual product prompts across ChatGPT, Perplexity, Gemini, and Copilot, checks your feed and review-site coverage, and flags the specific SKUs or categories where competitors are currently winning the AI answer you should own. The output is a prioritized list, not a 40-page generic report. None of this guarantees a specific outcome, but it does guarantee the agency relationship starts from evidence rather than a sales pitch. None of this needs to feel adversarial; a founder who arrives informed tends to get a more honest, more specific proposal in return.

Worked example: a comparison-driven category

Even outside DTC retail, the same evaluation logic holds. A regulated trading platform choosing between broker comparison content faces an identical test: does the candidate agency understand that a buyer's AI prompt ("which broker has the lowest minimum deposit for a beginner") depends on structured, accurate, and current facts — deposit minimums, licensing, spreads — rather than generic brand copy. The mechanics of good GEO hiring transfer across DTC and B2B alike; only the specific data being structured changes. A DTC founder who runs this process once tends to bring the same rigor to every future vendor conversation, not just GEO. The founders who get the most out of this process treat the first ninety days as a joint diagnostic exercise with the agency, not a set-and-forget handoff.

Reporting you should insist on

Reject any proposal that reports impressions or a generic visibility score with no underlying prompt detail. Insist on: which specific prompts were tested, which engine answered which way, month-over-month change, and — where trackable — the conversion rate of AI-referred sessions versus other channels. Studies report AI referral traffic converting several times better than average organic search traffic, so this comparison is worth demanding from day one.