Fixing Hallucinations: How to Correct Wrong Brand Info in ChatGPT & Perplexity

"I asked ChatGPT about our enterprise plan, and it said we don't have one." "Perplexity thinks our CEO is still the guy who left in 2023." "Gemini is recommending our competitor's product when users ask for our specific feature set."

Welcome to the headache of Brand Hallucination.

In traditional SEO, if Google had wrong information, you updated your website, requested a re-index, and it was fixed in days. In the world of Large Language Models (LLMs), bad data can be "baked in" to the model's weights, or retrieved from outdated third-party sources during RAG (Retrieval-Augmented Generation).

Correcting this requires a new discipline: Brand Entity Management.

Why LLMs Hallucinate Your Brand

To fix the problem, you must understand the source. AI "wrong answers" come from two places:

1. Training Data (Long-Term Memory): The model read an article from 2022 during its training phase. It "knows" that facts as truth. Changing this requires the model creator (OpenAI/Google) to retrain or fine-tune the model, which happens only every few months.
2. RAG Failure (Short-Term Memory): The model tried to search the web for live info, but it found:
   • An outdated review site that ranks higher than your pricing page.
   • A hallucinated synthesis of two unrelated facts.
   • Nothing (because your site blocked the bot via robots.txt).

The "Knowledge Injection" Framework

You cannot "edit" ChatGPT. But you can overwhelm the bad data with good data. We call this Knowledge Injection.

Step 1: The "Source of Truth" Audit

First, ensure your own house is in order. LLMs prioritize structured data.

• About Page: Rewrite it to be fact-dense. "Founded in 2018, Company X provides Y."
• Pricing Page: Use clear tables. LLMs read tables better than complex CSS pricing grids.
• Schema Markup: This is critical. Use Organization, Product, and Person schema to explicitly tell bots who you are.

{
  "@context": "https://schema.org",
  "@type": "Corporation",
  "name": "Acme Corp",
  "url": "https://acmecorp.com",
  "logo": "https://acmecorp.com/logo.png",
  "sameAs": [
    "https://twitter.com/acmecorp",
    "https://linkedin.com/company/acmecorp"
  ],
  "description": "Acme Corp is the leading provider of AI Security solutions, founded in 2020..."
}

Step 2: The "Satellite" Strategy

If ChatGPT is citing a 2021 TechCrunch article saying you are a "struggling startup," you need new, high-authority content to displace it.

LLMs trust authority domains (Wikipedia, Crunchbase, G2, Capterra, Major News Outlets) more than they trust your marketing copy.

Action:

1. Update Crunchbase & LinkedIn: These are top-tier sources for RAG. Ensure your employee count, funding, and description are current.
2. Press Releases: Issue a press release on a major wire service (Business Wire) announcing your current positioning. "Acme Corp Announces 2026 Enterprise Pricing..."
3. Review Sites: Update your profiles on G2/Capterra. RAG agents love reading "Pros and Cons" from these sites.

Step 3: Direct Feedback Loops

In 2026, major AI platforms have introduced feedback mechanisms for verified brand owners.

• Google Knowledge Graph Claiming: Ensure you have claimed your Knowledge Panel. Gemini relies heavily on this.
• OpenAI Brand Manager (Beta): Upload your brand guidelines and "Key Facts" documents to OpenAI's publisher interface (if you are on the trusted partner list).

Case Study: Fixing a Pricing Hallucination

The Problem: A SaaS client raised prices in 2025. ChatGPT kept quoting the 2023 pricing ($49/mo instead of $99/mo), causing sales friction.

The Diagnosis:

• The client's pricing page was behind a login (invisible to bots).
• The top search result for "Client Pricing" was a 2023 blog post by a third-party affiliate.

The Fix:

1. Public Pricing Page: Created a public /pricing page with a clear HTML table.
2. Schema: Added PriceSpecification schema.
3. Displacement: Wrote a blog post "2026 Pricing Update" and linked it internally.
4. Affiliate Outreach: Asked the affiliate to update their post (or 301 redirect it).

Result: Within 3 weeks, Perplexity and Bing Chat updated. ChatGPT (GPT-5) took 2 months to reflect the change in its base model knowledge, but its "Browse" feature got it right immediately.

Monitoring Your "Share of Sentiment"

You need to actively query LLMs to check your health.

Prompt for Testing:

"What are the pros and cons of [Your Brand] vs [Competitor]?" "How much does [Your Brand] cost?" "Who is the CEO of [Your Brand]?"

If you see hallucinations, treat it as a Brand Crisis.

The Wikipedia Factor

Wikipedia remains the "root of truth" for many models. If you have a page, keep it protected from vandalism. If you don't, do not try to force one (it will get deleted). Instead, focus on Wikidata.

Wikidata is a structured knowledge base that powers Wikipedia. It is easier to edit and is machine-readable. ensuring your Wikidata entry is accurate is a high-leverage move for Entity SEO.

Conclusion: You Are the Steward of Your Entity

In the AI age, your brand is not just a logo and a tagline. It is a Data Entity—a collection of vectors in a high-dimensional space.

If those vectors point to the wrong information, you lose revenue.

By adopting a strict regimen of Schema markup, Satellite updates, and Knowledge Injection, you can train the AI to see you clearly.

For more on technical entity management, read our Entity SEO Guide and Optimizing for Perplexity.