LLMs and their influence on traffic to a brand’s website are a major topic in our client conversations. Everyone wants to know what’s happening, how they can do better, and what the best practices are.

My recommendation to brands right now is to start with the data and focus on what they can know for sure.

To glean insights into how LLM traffic is influencing key metrics, we analyzed our dataset of LLM prompt referral traffic in Google Analytics across our customer base over the last 13 months (Jan. 1, 2025 to Feb. 7, 2026). 

We focused on traffic from various LLM models to brand sites and the conversion events closest to true business outcomes. In some cases, that’s a purchase. In others, it’s a generated lead.

When we look at this dataset, four major findings rise to the surface:

• LLM referral traffic is still small.
• LLM traffic is growing fast.
• The sources referenced in responses are shifting.
• LLMs convert at a very high rate compared to other channels

LLM referral traffic is still small

LLM referral traffic accounts for less than 2% of total referral traffic on average, according to our dataset. In other words, fewer than 2 out of 100 visitors to a site come from an LLM referring source.

The range is 0.15%-1.5% of referral traffic coming from various LLMs, including ChatGPT, Perplexity, Gemini, and Claude.

So while this is a major topic of conversation, it isn’t the highest priority for near-term bottom-line impact for many businesses.

LLM traffic is growing fast

LLMs, as a referral source, are growing quickly, according to our data. Comparing the first half of 2025 with the second half, we saw an average growth rate of 80% in LLM referral traffic.

There was a wide range across the dataset. Some companies saw just 10% growth, while others experienced 300% increases.

Below is the aggregate referral traffic by month in 2025. It shows a steady month-by-month increase, building to 3x referral traffic growth from January to December.

That means it’s not enough to understand your volume of LLM traffic. You also need to monitor the velocity of that growth.

LLMs are expanding as consumer adoption grows, and prompt algorithms keep changing. Between those two variables, you can see dramatic swings that you need to monitor.

Dig deeper: LLM optimization in 2026: Tracking, visibility, and what’s next for AI discovery

Sources referenced in responses are shifting

The sources cited in LLM responses are changing quickly.

Here’s a look at our dataset since September of last year. The data comes from monitoring more than 5,000 prompts and their responses across various LLM APIs, including Gemini, ChatGPT, and Perplexity.

YouTube links and citations have increased over the last 30 days. Reddit saw similar growth, though that traffic recently leveled off.

These shifts in citations and links will affect the traffic that eventually reaches your site, and they may also influence your ad and content strategies.

If you don’t monitor this data, you won’t see these changes. LLMs don’t provide this information directly — you can only access it through a third-party tool.

LLMs convert at a very high rate compared to other channels

This is likely the most interesting and important finding. When you compare conversion rates alongside the total percentage of traffic, the contrast becomes clear.

LLM referrals are the highest-converting traffic source across our customer base, with an approximate 18% conversion rate. That’s higher than any other tactic, including paid shopping, SEO, and PPC.

However, they account for the lowest percentage of total traffic to a brand’s website, about 25 times less than SEO or direct.

Dig deeper: How to better measure LLM visibility and its impact

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What brands should do next

Based on these findings, you should take the following actions to prepare for the evolving LLM landscape.

1. Establish dedicated monitoring

While LLM traffic volume is still low, its growth rate and volatility, including shifts between sources like YouTube and Reddit, make monitoring essential.

• Track velocity: Don’t just look at volume. Monitor the rate of growth in LLM referrals to understand when this channel crosses a meaningful threshold for your business.
• Monitor citation sources: Use available third-party tools to understand which LLMs and which types of platforms, including forums, videos, and news, are driving the most citations and subsequent traffic.

2. Capitalize on high-value traffic

An 18% conversion rate suggests LLM-referred users are highly qualified. They often arrive with clear intent or after their query has already been answered or validated by the LLM.

• Analyze high-converting journeys: Review the user journey for LLM referrals. What content are they landing on? What queries are being answered that lead to conversion?
• Optimize for intent: Focus content and landing page optimization on the high-intent needs reflected in the LLM’s citation context. Treat this traffic as a premium audience.

3. Plan for future growth

Given rapid LLM adoption, today’s low traffic volume won’t last.

• Develop a content strategy for AI: Build a strategy that anticipates how LLMs summarize, cite, and reference your material. This isn’t traditional SEO. It’s about being the authoritative source LLMs choose to link to.
• Allocate budget: While this may not drive immediate bottom-line impact, dedicate a small budget to tools and resources focused on understanding and optimizing the LLM referral channel.

This space is evolving fast. Hopefully, this dataset shows how things are progressing and motivates action within your organization.

This is a time of change. If you innovate, stay focused, and use data, you have a clear opportunity to outperform your competition.

Dig deeper: LLM consistency and recommendation share: The new SEO KPI

From emerging channel to strategic signal

LLM referral traffic is still a small share of overall volume, but it’s growing fast, shifting where it cites, and driving strong conversions.

Don’t overreact. Monitor the trend lines, understand where citations come from, and watch how this audience behaves once it lands. This space is moving fast, and if you stay close to the data, you’ll be better positioned as it evolves.