In this episode of ThriveCast, we speak with Hank Azarian, founder of Hank Azarian Consulting and an enterprise SEO & AI consultant working with publishers and PE-backed brands. Hank explains how AI-first discovery is scrambling attribution, walking through how a website's job has shifted from "brochure" to source of canonical truth, why traffic and rankings are becoming vanity metrics as click-through rates collapse, and why the real budget question isn't SEO-versus-AEO but which channels are actually closest to revenue. This conversation is essential for CMOs, Growth Leaders, and SEO practitioners rethinking how marketing dollars get allocated in an AI-first discovery landscape.

Key Insights

* AI is capturing a growing share of discovery. Recent Similarweb data found that among users who use both AI and search, 35% preferred AI as their discovery mode versus only 13% who preferred search — roughly a two-to-one shift.

* Discovery and attribution have decoupled. A buyer’s first touch may happen on AI, but the resulting relationship often gets credited to whichever channel they eventually click through — social, organic, or paid — even though AI influenced it further upstream.

* The website’s job has changed. It’s no longer the “brochure” that drives discovery; it’s now a source of canonical truth that validates the claims other AI surfaces are already making about you.

* Rankings can hold while revenue quietly collapses. A keyword that once delivered a 10–12% click-through rate at a top-three ranking can now deliver roughly 1%, even though the ranking itself hasn’t moved.

* “Key person SEO” beats keyword SEO. A specific returning-user segment came back four times more often, consumed five to six pages per visit instead of one to two, and showed a 17x increase in lifetime value once they signed up for email.

* Traffic loss isn’t evenly distributed. In Hank’s experience, the roughly 20% of visitors who are genuinely engaged can represent 80–95% of a business’s actual revenue from that traffic — so recovering that slice matters more than the headline traffic number.

* Start with the ICP, not the channel. Before assigning budget, define who your business serves best, then build revenue-driven objectives around that customer — not around a channel line item.

* The budget conversation should start at the marketing level, not the SEO level. AI is disrupting SEO, paid, and social simultaneously, so treating AI as strictly an “SEO problem” misframes it — it’s a marketing problem.

* Comparative “best-of” content can backfire. If you’re not the clear category leader, publishing roundups that rank your competitors alongside you effectively validates their claims and can lower your own perceived standing.

* Consensus content adds nothing. If your content just repeats what ChatGPT and competitors already say, AI systems have no reason to cite you — differentiation requires your own IP, data, or point of view.

* Some early-stage businesses shouldn’t invest in SEO at all. Understanding the real buyer often needs to come before any SEO spend, not after.

* The new north-star metrics are revenue-proximity metrics — SEO cost of user acquisition versus other channels, return on ad spend variation, and incrementality — not impressions, clicks, or rankings.

Actionable Takeaways

* Audit your returning-visitor segment separately from one-time traffic — measure pages-per-session and email-signup lifetime value, not just total visits.

* Map your ICP explicitly before allocating any channel budget.

* Replace ranking and impression dashboards with revenue-proximity metrics: channel CAC, ROAS variance, and incrementality.

* Test small distribution bets (a few hundred dollars across a handful of campaigns) before committing bigger budget to validate what resonates.

* Reframe your website’s role from lead-capture to proof-and-validation — build content that verifies your claims rather than content built purely to attract clicks.

* Avoid publishing comparative “best-of” roundups unless you’re the clear category leader.

* Build content around proprietary data, IP, or point of view instead of restating AI/consensus answers.

* Bring the SEO budget conversation into a holistic marketing-budget conversation instead of treating it as an isolated line item.

* Re-evaluate whether SEO is even the right first investment for early-stage or pre-PMF products.

* Coordinate messaging across channels — Reddit, social, search — so the brand narrative stays consistent instead of each channel being optimized in isolation.

Resources Mentioned

* Similarweb — Web analytics data cited for the shift in user preference between AI and search discovery.

* Profound — AI visibility platform referenced as an example of a company building comparative brand-ranking models.

* PickFu — A low-cost tool for quick audience testing before scaling a paid campaign.

For CMOs and growth leaders, Hank's message cuts through the noise: the fight over SEO versus AEO/GEO budget lines is the wrong fight. The real work is figuring out which channels are actually closest to revenue for your specific ICP, and building your website — and your metrics — around proof and conversion rather than rankings and impressions.

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