We recently studied how brand content performs across different AI platforms. LLMs are probabilistic, and each platform weighs different factors when deciding what’s worth citing. With that in mind, we wanted to get a better look at which environments viewed brand content most favorably.
We found that Google’s AI products — especially AI Overviews and AI Mode — surfaced brands in their responses more often than other AI platforms.
But what does this mean for the teams that are actually creating content with the goal of appearing more in AI responses? Here’s what the data says about framing and measuring content for AI visibility on different platforms.
Methodology
As a refresher, our analysis involved looking at how 245 stories performed on six AI platforms in the four weeks after they were distributed on the Stacker Newswire.
We used a metric called response presence rate, which measures whether a brand is present in a platform's response, either because:
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the brand was mentioned by name (known as a mention),
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its domain was cited by the AI engine (which we call a brand citation),
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or a Stacker-distributed story was cited instead (called a network citation).
Meeting any of these three criteria means that the brand is considered "present" in the response. It's presented as a percentage to reflect how frequently the brand appeared in all of the platform’s responses to a particular prompt.
Here’s how the platforms stacked up:
How should your content strategy account for the differences between platforms?
If you’re part of a brand content team with improving AI visibility as a goal, there are a few things you can take away from this study:
Build for the long game
Content distributed through a publisher network becomes more likely to be cited by LLMs over time, not immediately. Measuring visibility in the first week after distribution is likely to give misleading results. Some platforms, like Google AI Overviews and AI Mode, spike early and then normalize at a slightly lower level. On the other hand, Claude compounds authority over time. 118 of the 132 stories that had presence on Claude saw that presence grow between the first and fourth weeks after distribution. It’s best to wait for Week 4 after Stacker distribution to get the full picture — especially for results from Claude.
Create content that’s geared towards a specific need
AI platforms are designed to answer questions, so your content should, too. It also helps to put that question in the headline: Our analysis found that pieces framed as a question outperformed statement-style headlines on every platform except for ChatGPT. Think “How is X changing in 2026?” rather than “The State of X.”
We also found that content that compared two or more similar items or that helped readers decide whether a product was worth buying tended to appear more often in AI responses than other content types.
Use your SEO best practices as a guide
Since Google’s AI products use the same ranking systems as traditional search, having a strong SEO play is an advantage when it comes to performing well on Google AI Overviews and AI Mode (the two platforms that cite brand content most often). Aligning your content towards user intent — through specific keywords as well as specific prompts — means it’s ready for both AI-driven and traditional search.
Always optimize for credibility — not for one particular platform
Our analysis found that the content that performed well across platforms was data-driven and original. It also structured those unique insights in a way that was easy for readers to scan and for AI engines to parse. Stories that had an average response presence rate of over 20% (75 of the 245 stories analyzed) performed well across all of the platforms, not just one. They averaged 40%+ on Google AI Overviews and AI Mode, 36% on Claude, and 30% on Perplexity.
The characteristics that drive AI visibility are the same across platforms, but presence grows at different rates and on different timelines. And getting your content in front of these engines — by distributing it to high-authority publisher sites — is the important first step.
Madeline Stone is the Content Manager for Editorial & Insights at Stacker. She was previously a longtime business and tech journalist at Business Insider and a content and communications consultant for tech startups.
