Be the brand ChatGPT names

SEO is about ranking your product page on Google for a query a shopper types in. AEO is about being the brand that ChatGPT, Perplexity, or Google's AI Overview names when a shopper asks for a recommendation. The signals overlap, but they're not the same. Google rewards your own site. AI engines reward what the rest of the web says about you: Reddit threads, fashion press, Wikipedia, review roundups. A brand can rank #1 on Google and still be invisible in ChatGPT.

No, and anyone promising that is selling you something. We don't control what OpenAI's models output, and the citation behavior changes with every model update. What we do guarantee is the work: published third-party coverage, optimized site structure, prompt tracking, and a content corpus the models can actually use. We share the tracking dashboard so you see citation lift as it happens.

We run a tracked panel of prompts across ChatGPT, Claude, Perplexity, and Google AI Overviews on a recurring schedule. For a denim brand, that might be 80 to 120 prompts ranging from "best sustainable denim brands" to "raw selvedge jeans under $250" to "compare Buck Mason vs Taylor Stitch". We log every response, flag when your brand is named, and track citation share against competitors over time. You see the dashboard, not just a monthly slide.

If your product pages aren't ranking on Google yet and you have under 30 SKUs, fix SEO first. The two share a foundation: clean product schema, fast pages, good copy. Once Google trusts your site, AEO compounds faster because models often pull from sites that already rank well. For brands already getting organic traffic but invisible in ChatGPT, AEO is the bigger payoff per dollar. We usually scope an audit before recommending which to start with.

Mixed picture. AI Overviews and ChatGPT answers reduce click-through on informational queries because the shopper gets the answer without leaving. But transactional queries ("buy linen shirt", "navy cashmere sweater") still drive clicks because shoppers want to see the product, fit, and price. The brands getting hurt are the ones running content sites and affiliate roundups. DTC fashion brands with a real product to sell are mostly fine, but the long tail of informational traffic is shrinking.

Three formats keep showing up: Reddit threads where real customers compare brands, fashion press roundups (Vogue, GQ, The Strategist, Esquire), and brand-owned content that directly answers a category question with specifics. Vague "about us" pages and product descriptions full of marketing fluff get ignored. Pages that say exactly what fabric weight, country of manufacture, fit, and price range get pulled. We rewrite product copy to look more like a Wirecutter review and less like a brand brochure.

First, identify the source. If ChatGPT thinks your brand is based in Brooklyn when you're in Portland, the bad info usually traces back to one or two pages: an old press release, an incorrect Wikipedia line, a misquoted Reddit comment. We get the original source corrected, file Wikipedia edits where applicable, and publish authoritative pages on your own site that contradict the wrong claim. Over time the model retrains on the corrected corpus. It's slow but it works.

Not directly. ChatGPT and Claude don't index Pinterest or TikTok in any meaningful way yet. Perplexity occasionally surfaces TikTok content but rarely for fashion. What does translate: a TikTok trend that drives press coverage ("the quiet luxury TikTok aesthetic") generates editorial articles, which feed AI training corpora. So treat social as a top-of-funnel signal that earns press, which then earns AI citations. Don't expect direct attribution from TikTok to ChatGPT.

It's harder, and we're honest about it. Without press mentions, Reddit threads, or third-party coverage, the models have nothing to cite. The first 90 days are usually spent earning the first 5 to 10 third-party mentions: pitched fashion editors, guest posts on style sites, founder interviews on niche fashion podcasts, and seeded conversations on relevant subreddits. We can't shortcut the authority-building work, but we can sequence it efficiently.

llms.txt is useful but oversold right now. It tells models which pages on your site are worth indexing, which helps with retrieval-based engines like Perplexity and Claude's web search. For ChatGPT's main training, it has limited impact because OpenAI doesn't strictly honor it. We add llms.txt to every site we work on because it costs nothing and signals to crawlers, but it's not a silver bullet. The real lift comes from off-site content and structured product data.

Reddit is probably the single biggest AEO surface for fashion right now. ChatGPT and Perplexity pull heavily from r/femalefashionadvice, r/malefashionadvice, r/frugalmalefashion, r/sustainablefashion, and brand-specific subs. Wikipedia matters for entity grounding, but most small fashion brands don't qualify for a page. Fashion press (The Strategist, GQ, Vogue, Esquire roundups) is the most durable source because editorial articles stay indexed for years. We work on all three in parallel.

Tiers run from $497 to $1,497 per month. The $497 tier covers prompt tracking, schema work, llms.txt setup, and 2 published assets per month. The $997 tier adds outreach to Reddit threads, niche fashion press pitching, and product copy rewrites. The $1,497 tier adds Wikipedia work where applicable, founder PR placements, and a quarterly citation strategy review. No contracts, cancel anytime. Most ecommerce brands we work with sit on the $997 tier for at least 6 months.

More than you'd expect. Each ChatGPT model update can reshuffle which brands get named for a given prompt. Perplexity changes recommendations in real time based on what's freshly indexed. We've seen brands gain 20 citation positions one month and lose 10 the next when a competitor lands a big Strategist piece. That volatility is the reason we track weekly instead of monthly. It's also why one-time AEO work doesn't last.