Anne is Head of Marketing at AI Findr. She has led marketing for both multinational corporations and high-growth startups, including Run:ai (acquired by NVIDIA), Sage, Arthur Cox, Fields the Jeweller, and Boxever (now Sitecore CDP).
What's inside
What to do when AI gets your product wrong, and hands the win to someone else.
A marketer’s worst nightmare
A Digital Channels Director came to us last week with a disturbing discovery. He had asked ChatGPT to compare his company vs the competitor, and it cited the competitor’s (very biased) comparison page. Not only did it repeat the competitor’s false claims, but it also missed key benefits his company has offered for years, ones they’re known for. Is this what prospective customers were seeing?
Unfortunately, yes. And this is happening more often. Across industries, LLMs are becoming consumers’ first stop when researching purchases. When your product gets misrepresented (or left out entirely) you can lose a customer before they even land on your site.
Could this happen to your brand?
Ask yourself:
- Do you have individual product pages with clear feature breakdowns?
- Do you show up in Perplexity or ChatGPT when people ask about your category?
- Are you helping buyers understand how you compare to the competition?
- Is your structured data current and complete?
If you answered “no” or “not sure” to any of these, there’s a good chance your product is at risk of being misrepresented or skipped in public LLMs.
Why it’s happening: you’ve been ignoring the machine layer
You’ve invested in blogs, thought leadership, and landing pages. You’ve done your SEO homework. So why is an AI hallucinating facts about your business? Because you’ve optimized for humans, not machines.
Here’s what might be going wrong:
- You haven’t implemented or maintained structured data using schema.org standards
- You don’t have a llms.txt file
- You haven’t built enough authority through press coverage or backlinks
- Your site doesn’t directly answer the kinds of product questions buyers are asking
- Reddit or Quora threads are filling the vacuum with misinformation
LLMs rely on what’s clear, structured, and available. And if your competitor’s content is easier to parse and quote? They win the answer.
What you can do right now if an AI misrepresents your brand:
Submit feedback to the LLM directly
Most platforms (like ChatGPT or Claude) offer a thumbs-down or feedback button. Use it. Be specific:
“This feature is incorrectly attributed to [Competitor]. Our product has offered [Correct Feature] since [Date].”
Publish a clear, structured correction
Add a page that explicitly states your differentiators and addresses the misrepresented claim. Use headings, schema, and JSON-LD.
Create your own comparison page
If a competitor’s biased page is being cited, publish your own version. Clear, factual, structured content often wins.
Check Reddit, Quora, and forums
If public threads are spreading misinformation, jump in (transparently) or encourage happy customers to share their experience.
Launch an llms.txt file
Add a /llms.txt file to your root domain. It’s like a sitemap but for LLMs, pointing them to your most accurate, structured content.
Use tools to monitor your brand in LLMs
If it happened once, it’s probably happening elsewhere. LLM Findr tracks your brand's presence in LLMs, identifies inaccuracies, and benchmarks you against competitors.
LLM optimization (LLMO) for long-term results
LLMO isn’t a one-time project—it’s an ongoing discipline. Every time your product features shift, your pricing updates, or your policies change, your structured data needs to reflect it. If it doesn’t, LLMs risk serving outdated or inaccurate information which quietly erodes trust and performance over time.
If you have SEO and UX experts on your digital team, establishing your initial LLMO efforts in-house makes sense. But as you add content, launch new products, roll out more apps, and expand into new markets, this manual approach becomes impossible to scale.
The easy button: let AI fix the AI problem
At AI Findr, we built a system to solve the LLM problem with…more AI.
Instead of forming a cross-functional task force to manually tackle LLMO, we use automation to make your existing content LLMO-ready.
AI Findr ingests all your content (product specs, help center articles, blogs, policies, etc.) and turns it into a structured knowledge base for your own custom LLM. It allows visitors to ask detailed questions in natural language, returning highly accurate answers and product recommendations.
LLM Findr repackages that content into the optimal formats for LLMs to lift and cite it. LLM Findr tracks your citations and mentions across major LLMs, compares you to competitors, and provides actionable insights to improve your visibility.
Frequent content updates? No problem. Upload them to your AI Findr knowledge base or enable content auto-enrichment. Your digital team will thank you.
AI Findr + LLM Findr work together to make sure your product story is the one being told. Accurately. Everywhere that matters.
