95% of Inbound Leads from AI: A B2B Content Strategy Case Study
95%
3 years
of SEO content now driving AI-powered discovery
Lower
cost per acquisition, with no reduction in lead volume
Overview
Our UK B2B agency had published for three years and was unsure which channel was bringing in the most buyers. One question on a contact form redefined our content strategy.
The situation
Column, our UK B2B content and communications agency had a three-year publishing record: blog posts, thought leadership articles, and service pages. Traffic was healthy, client work was strong, and inbound enquiries came in at a steady pace. But our team had a limited view of which channels drove those enquiries. Standard analytics tracked sessions and referral sources, but they couldn’t explain why a buyer decided to reach out.
The approach
We added one question to the contact form: “How did you hear about us?” Then we tracked every response across 12 months of inbound leads. The data gave us a clearer picture of where buyers were actually coming from, and the answer surprised us.
Key finding
We had spent three years writing for search engines. Perhaps unsurprisingly, we’d also been writing for AI.
What changed
We stopped treating the blog as a pure traffic play and started treating it as an AI discoverability asset. We audited existing articles for authority signals and restructured them for clearer answers to high-intent queries. We tightened the internal linking architecture to reinforce topical depth, and steered the content calendar away from volume toward precision: fewer topics, covered more thoroughly, with AI discovery in mind.
The outcome
95% of inbound inquiries over a 12 month period were attributed to AI tools, based on self-reports on the contact form and during discovery calls. Cost per acquisition dropped, and we now publish with a better view of where our buyers come from and what kind of content puts us in front of them.