Who Speaks for a Brand When the Brand Doesn't?

When a brand doesn't publish its own deals in a way AI can find, the AI asks someone else.

I asked an AI chatbot for Nike discount codes after seeing a question on Reddit about whether large language models hallucinate brand URLs.

Nike is a company with over $46 billion in annual revenue, a dedicated promotions page, a student discount program, a military discount, and a membership tier. They have every resource, every piece of infrastructure, every reason to be the definitive answer when someone asks an AI how to save money on their products.

Groupon. CouponFollow. SimplyCodes. Garage Gym Reviews. Student Beans answered.

Nike.com appeared twice out of eight citations.

How this started

Last week, someone posted a question in r/SEO_for_AI asking whether vanity URLs increase the likelihood of LLM hallucinations. The full question: if an international site has a special sale at something like domain.com/special-sale that redirects to discounted products across multiple regional pages, could LLMs pick up on those URL patterns and hallucinate more often?

That got me thinking about URL pattern hijacking as an attack vector. If a brand has predictable vanity URL patterns, could someone register a similar domain, get it into the training corpus through press releases and blog posts, and wait for the LLMs to pattern match and confidently recommend fabricated URLs? Most retrieval systems weight domain authority heavily, and entity recognition is strong for major companies, so it would be hard to pull off against a big brand. But for smaller brands with less established graphs, maybe more of a chance.

Then I started thinking about it from the other direction. Not about whether someone could hijack the URL pattern, but about what the model actually retrieves when a brand's promotional content is outdated, inconsistent, or not structured for extraction.

So I tested it. I picked Darc Sport, specifically their Wolves line. I asked several AI chatbots for spring promos, current coupon codes, active deals.

The brand site rarely showed up. Instead I got citations for sites like Wethrift, SimplyCodes, Knoji, Dealspotr, and JoinCheckmate. Affiliate and coupon aggregator sites with dedicated Darc Sport pages, structured to be the first thing an AI finds. When the AI couldn't find a clean retrieval path to the brand itself, it defaulted to the safest generic advice it had: sign up for their email list.

The Nike test

After seeing the Darc Sport results I wanted to see if the same thing happened with a brand that has more resources. Nike seemed like the obvious choice.

When I asked Perplexity for Nike discount codes, it didn't just cite a few third-party sites. It built an entire shopping workflow around them. Five numbered sections. Section one was to check Nike's own promo page. Sections two through five involved coupon aggregator sites, stacking member perks, timing purchases, and a literal step-by-step that told the user to open two to three coupon site Nike pages and copy codes.

The AI took Nike's own page and made it the first step in a process that funnels the user through Groupon, CouponFollow, and SimplyCodes before they ever complete a purchase. The brand's own site became one input in a workflow the brand had no part in building.

Nike didn't author that workflow. Nike wasn't consulted. The AI just decided that the most helpful answer involved routing the customer through three intermediaries, and the customer has no reason to question it because the AI presented it with the same authority it presents everything.

The same query on Gemini

I ran the same queries through Google's Gemini. Same brands, same phrasing.

Gemini sent the user directly to Nike.com/Sale. It described the discount structure, explained the membership perks, walked through how to apply a code at checkout. For Darc Sport, it named specific athlete and ambassador codes, described the rewards program, and pointed to the Secret Sale and SMS alert system on the brand's own site. Rakuten appeared once as a supplementary mention. The rest came from the brands.

Nothing about the query changed. Nothing about the brands changed. The system did.

Gemini appears to draw from Google's index, including structured data that brands have been submitting through Google Merchant Center and Shopping feeds for years. That data was built for Google Shopping, not for Gemini. Gemini inherited it. Pricing, availability, promotions, eligibility. The kind of information an AI needs to answer questions about offers without guessing.

The brands didn't optimize for Gemini. They optimized for Google's commerce infrastructure, and Gemini benefits from that work by default.

Perplexity and ChatGPT rely on publicly crawlable, extraction-friendly pages, exactly the terrain affiliate sites are built for. Same brand, same question, different system, different answer.

None of this suggests these systems are being gamed. They're doing exactly what they're designed to do when the brand hasn't given them something clear to work with.

When brands don’t clearly and consistently publish authoritative, machine-legible representations of their own offers, AI systems substitute the most legible available proxy.

What the citations actually mean

I pulled up the pages the AI was actually citing and compared them to what the brands had.

Affiliate sites like Wethrift and CouponFollow have dedicated pages for every major brand, sitting at clean URLs like /nike or /darc-sport. They have answer-first content, with codes and deals above the fold before any other text. They have FAQ schema that mirrors exactly how someone would ask an AI for this information. They have recency signals. "Updated February 2026." "Last verified today." They have social proof, community verification, success rates, user-submitted codes.

The brands, in most cases, have none of this. No dedicated, indexable promotions page. No structured data around deals. No recency signals. Nothing at a predictable URL that an AI can reach for and find.

The affiliate sites are engineered for AI retrieval. The brands are not. And the AI, doing what it's designed to do, goes where the information is structured, current, and easy to extract.

The second-order problem

When someone asks an AI for a brand's deals and gets routed to affiliate sites with potentially expired codes, the next thing they do is predictable. They ask for alternatives.

"Best alternatives to Darc Sport with discount codes."

And the AI is happy to answer that one too. In testing, Perplexity generated a detailed comparison table of seven direct competitors, complete with where to find their deals and which ones were currently running promotions.

The path looks like this. User wants Darc Sport deals. AI sends them to affiliate sites. Codes don't work or feel unreliable. User asks for alternatives. AI provides a competitive comparison with active deals. User buys from a competitor. Darc Sport could have been in that conversation with a dedicated promotions page, structured markup, and current recency signals. They weren't.

As of early 2026, this is what the customer journey looks like for any brand that hasn't structured its promotional content for AI retrieval. A rough financial estimate put the impact at $52,000 annually for a $50 million DTC brand, and that was measuring discount queries alone.

What's actually being lost

This isn't about optimization tactics or technical SEO. The question underneath all of this is simpler than any of the technical details suggest.

When a customer turns to AI for help with a purchase decision, and increasingly that is where they turn, does your brand get to participate in that conversation?

For Nike, the brand appeared in two out of eight citations. The rest came from affiliates. For Darc Sport, the brand's own site appeared once across multiple tests.

And the thing about AI-mediated conversations is that the customer doesn't see who was consulted. They don't see a list of results and choose which one to click. They see an answer. The answer feels authoritative because the AI delivered it with confidence. The customer acts on it.

That's what's being lost. Not traffic. Not rankings. The opportunity to be present when someone is deciding whether to buy from you.

The fix is not complicated. A dedicated promotions page at a clean URL, structured data, current recency signals, linked from the site's core navigation. It's the kind of routine maintenance that most brands already do for search engines. They just haven't done it for the AI layer yet. Ironically, AI automation tools could handle most of it.

Most brands haven't started yet.