How significant is AI chatbot traffic in B2B?
Mini case study
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The first commercial power plant had only 59 customers when Thomas Edison built it in 1882. 18 years later, access to electricity had already expanded to 3.8 million US Americans (5% of households).1 From there, power grid access grew exponentially:
8% in 1907
35% in 1920
68% in 1929
We stand at the doorstep of a comparable technology: AI.
Chat GPT is the 2nd fastest growing consumer product.
Capital expenditures of hyperscalers could exceed $300 billion in 2025.2
AI already makes consultants, writers, and financial experts more efficient.
A joint report by Semrush and Statista found that 1 in 10 US internet users go to gen AI for search first before exploring search engines.
But when is the right time for B2B companies to invest in AI chatbot visibility? For companies with limited resources, investing in technology too early can be a costly distraction (pets.com). Being too late can cost even more (Kodak). B2B is a particularly interesting case for three reasons: 1/ longer sales cycles, 2/ high competition and 3/ AI chatbots answer a lot of information queries directly that used to bring traffic from Google. E-commerce, for example, is different because searches either start on Amazon directly or shopping is natively integrated (see Perplexity shopping or Google’s new experience).
I analyzed referral traffic from the biggest AI chatbots to 6 B2B companies with a combined traffic volume of over 1 million monthly visits. The data shows an average of 0.14% when comparing AI chatbot referrals to organic visits. That’s one referral for every 714 organic visits. Peanuts. But in the next 3 years, AI chatbot referral traffic could make up over 35% of organic traffic. As a result, companies would do well to develop playbooks for growing visibility now to benefit from first-mover advantages.
How much traffic do AI chatbots send?
In my case study of 6 B2B companies, referral traffic from AI chatbots has grown from an average of 250 visits / month in the first half of 2024 to over 1,300 in November (+5x). The drivers are growing usage of AI chatbots, more links to sources and OpenAI’s introduction of its AI search engine, Chat GPT Search.
Almost unsurprisingly, Chat GPT sends the most referral traffic, with almost 50%. Perplexity comes in 2nd at 21.7%. Gemini sits in a surprisingly distant 5th place. Even Bing and Copilot send more traffic, even though Gemini was built by search monopoly Google. It’s unclear whether usage or design is responsible for Gemini’s low referral traffic.
Even though AI chatbot referral traffic is growing rapidly, it makes up only 0.34% in comparison to organic traffic. For some companies, it’s as low as 0.09%, and for others, it's as high as 0.9%. It’s easy to dismiss referral traffic from AI chatbots because of their miniscule size. Every smart manager would categorize such a small customer acquisition channel as a distraction. And yet, it’s a mistake.
Referral traffic from AI chatbots grows at a staggering monthly average of 25.6%. As humans, we’re inherently bad at understanding compound growth because most of our environment is linear (distance, time, etc.). An annual growth rate of 7% seems harmless until you realize it doubles growth in 10 years.
Only 14% of US Americans have tried Chat GPT.3 They’re early adopters. Over 170 million more could join the trend in the next years (assuming 334 million Americans minus ~35% for age), which should skyrocket referral traffic even more. And that’s just the US.
On the flipside, organic traffic is flat to down for many B2B companies. In my sample set, Organic traffic grew only 1.1x between January and November on average.
When considering constant growth rates, over 1/3 of organic traffic could come from AI Chatbots in 3 years. In the sum total, AI chatbot referrals would make up over 34% of traffic. Two companies in my set of 6 are projected to get more than double as much traffic from AI chatbots than from search engines.
Referral to organic traffic ratio projections:
Today: 0.14% (January - November)
In a year: 0.79%
In two years: 5.7%
In three years: 52%
Note that we don’t yet know whether AI chatbots cannibalize search engine usage one-to-one or whether we’ll do both. I have a hunch it’s going to be the latter because AI adoption will happen in phases, and overall usage could increase because LLMs are so capable. That’s also why my projection chart has a higher total as AI chatbot adoption grows in year 3, which means more potential traffic for B2B companies instead of less.
Of course, this is a small case study of only 6 B2B companies and growth rates likely won’t stay constant. Most projections are wrong, but this exercise helps to put in perspective how quickly the status quo can change.
Implications
My advice is clear: don’t bank on steam engines. Bank on the power grid. AI chatbots show early signs of compound growth that could become significantly fasterer than we can intuitively grok.
Here is what I tell my (B2B) clients:
Monitor LLM crawlers, referral traffic, and conversions by landing page to figure out which content gets crawled and performs well in AI chatbots.
Track your keywords as questions with a house made, API-based tracking system or proprietary LLM tracking tools. Monitor visibility Chat GPT, Perplexity, Copilot/Bing and Gemini because we don’t yet know whether “AI chatbot optimization” will lead to the same results for all chatbots, similar to how SEO is very similar for Google and Bing or whether they will reward different approaches.
Test net-new content and content adjustments to provide better answers in AI chatbots. Now is the time to write the playbook.
Keep doing classic SEO since AI Chatbots still lean heavily on their results to ground answers.
My hosting is blocking almost 90% of the LLM bot traffic. I wonder do you see the same in your server? And what’s your thought on this as LLM bot is known to be very aggressive. Do LLM bots need to be granted full access to our site for full visibility potential?
Which tools would you recommend to help with tracking LLM crawlers and appearances in AI chatbots? At the minute is it just a case of checking GA for typical metrics or is there something more I could be doing?