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Data infrastructure makes for a fascinating case study in AI monetization. The same product could ship as fully managed, self-managed, or running inside the customer’s cloud — meaning three different cost profiles and value drivers. The product gets adopted by both people and AI agents — and the latter has spiky and unpredictable consumption.
Aiven has raised >$400M for its open source data infra platform. VP of Strategy and employee #10 Ville Lehto unpacks these monetization shifts in an upcoming Metronome webinar on June 24th. Register now to learn the new monetization playbook for data infrastructure.
You already know AI is talking about your product, and you’re probably already tracking your AI visibility. The next frontier, as I’ve talked about before, is getting AI to talk about your product in the right way.
Are LLMs mentioning your best customers and how they use the product?
Can LLMs pitch why your product is better than competitors?
Do LLMs credibly explain how your pricing works and why it’s customer friendly?
This already matters because your buyers trust LLMs as an “objective” source when making buying decisions. It’ll be even more important if (when?) AI agents starting buying products directly.
Some have argued that your website matters less if buyers don’t actually visit it when doing research. My two cents: your website is even more important and now needs to be optimized for two distinct audiences, humans and AI agents.
There’s more data to back this up. Profound noticed that ChatGPT referral traffic to monitored websites increased by >60% starting on May 7, 2026 — and has stayed there. Homepages went from 3.5% of ChatGPT referrals to ~24%. What you put on your homepage is being read by the LLM and clicked on by the human.
Today I wanted to investigate the most creative ways that early adopters are using their websites to influence AI agents (and humans). For help I partnered with Casey Hill, longtime website geek and CMO of website optimization company DoWhatWorks. We don’t have hard A/B test data on all of these tactics. But we hope they start a conversation internally about what you might test, and how you can get a head start on the competition.
Tactic: Put your best customers in the website footer
Inspiration: Clay, Sundial
Clay does something interesting in its website footer: it links directly to top customer case studies.
Does doing that have any impact on how often Clay + [top customer] is mentioned in LLM queries?
Casey decided to test it. He asked ChatGPT: “What notable brands use Clay?”
100% of the sources cited were Clay.com, specifically the brands featured in that footer list.
Then Casey ran the same prompt for other major SaaS companies like HubSpot, DocuSign, and Typeform. Even though they have plenty of customer stories, their own domains were cited less consistently when those stories were buried deeper in the site.
Our working theory: LLMs overweight structural prominence, aka what you put in your headers, subheaders, top nav, and footer.
Pages linked site-wide in global navigation or footers may be treated as more semantically important, similar to how traditional SEO values internal linking and site architecture.
There’s already some emerging AEO/SEO research suggesting footer prominence can influence LLM visibility, and it lines up with what SEO teams have known for years: important pages should be easy to find and clearly linked. I checked this with Josh Blyskal from Profound, who I interviewed last year, and he confirmed the structural prominence theory. His research into Google AI Mode found that it literally extracts your headers, summarizes the text under each one, and only the themes that win across many pages become the bold sections of the final answer.
Clay’s approach is a low-lift test. Put your strongest customer proof directly in the global nav or footer, then monitor whether it improves visibility for prompts like:
“What notable brands use [company]?”
“Who are [company]’s customers?”
“Which companies use [category/product]?”