If you're running multiple projects in Chatbeat, or comparing notes with a colleague in a different industry, you've probably noticed that the sources cited by AI models can look completely different from one project to another. This is expected, and it's actually one of the most important insights Chatbeat provides.

It's tempting to look for a single formula: "get listed on Reddit and G2, and AI models will cite you." But the reality is more nuanced. The sources that influence AI responses depend on three factors that interact with each other.

Industry. Different industries have entirely different citation landscapes. For a SaaS brand monitoring tool, AI models might rely heavily on review sites like g2.com, competitor blogs like sproutsocial.com, and community discussions on reddit.com.

For a furniture brand, the picture looks completely different. AI models might draw from interior design portals, local e-commerce platforms, and lifestyle magazines instead.

There is no one-size-fits-all list of "important sources." What matters for your brand depends entirely on your category.

Even within the same project, each AI model draws from different sources. For example, in a furniture-related project, ChatGPT might favor Wikipedia and established e-commerce sites, while Perplexity leans toward niche design blogs and local furniture shops.

This means optimizing for one model doesn't guarantee results in another. Each has its own retrieval logic and source preferences.

The questions you track also affect which sources appear. A prompt like "What are the best social listening tools?" will pull from listicle-style blog posts and comparison pages. A prompt like "How to monitor brand reputation?" might surface more educational content and guides. The more varied your prompts, the more diverse your source landscape will be.

The language of your prompts has a direct impact on which sources get cited. If you ask questions in English, AI models will predominantly cite English-language pages. If you ask in Polish, as in the IKEA project above, you'll see Polish domains like architecturaldigest.pl, mebleoutlet.pl, and allegro.pl appearing in the results.

This is why the IKEA Demo project shows so many local Polish sources. The prompts were written in Polish with a Polish geolocation, so AI models naturally reached for Polish-language content. If the same project used English prompts, the source landscape would look entirely different, likely dominated by international domains instead.

Because sources vary by industry, model, and prompt, the only reliable way to understand what influences your brand's AI visibility is to look at your own data. Chatbeat gives you that view, broken down by model and over time, so you can build a content strategy based on what actually works in your specific space rather than following generic advice.

To explore your project's sources, go to the Sources tab in your sidebar. For tips on improving your presence in AI-cited content, visit the GEO Playbook or check out our guide at chatbeat.com/ai-seo-rank-in-chatgpt.