Research-driven marketing isn't new to me. The channel is.
I'm Dan Russell. I spent nine years running a conversion rate optimization agency, unlocking $50 million in revenue for clients through neuromarketing tactics grounded in behavioral science research. Now I'm applying that same research-first approach to the newest channel in marketing: AI search.
Nine years of research-driven optimization
For nearly a decade, I ran a CRO agency built on a simple principle: don't guess what works—measure it. We used neuromarketing and behavioral science to understand why people made decisions, then tested those hypotheses with data.
I built a team around research and testing. We ran thousands of experiments across dozens of verticals. The result was $50 million in measurable revenue unlocked for our clients—not from hunches or best practices, but from statistically validated findings specific to each business.
That experience taught me something that most marketers never learn: generic advice is almost always wrong for your specific situation. The only way to know what works is to measure it, longitudinally, in your context.
Everyone's chasing citations. Nobody's studying what makes them stick.
There's a massive surge of interest in getting cited by AI engines. Companies are investing real money in AEO and GEO services. But almost nobody is asking the harder question: once you get a citation, how do you keep it?
I watched the same pattern play out in CRO for years. Companies would invest heavily in driving traffic, then watch conversion rates decay because they never invested in understanding why things worked. They'd optimize once and move on. The gains would evaporate.
AI citations are the same problem in a new channel. Up to 60% of citations turn over every month. If you're not studying what persists and why, you're investing in a leaky bucket. You're paying to get cited today, and losing those citations next month.
Quoted exists to fix that. We bring the same research-first, data-driven methodology I used in CRO to the world of AI search. The goal isn't just to get you cited—it's to make sure your investment in AI visibility actually compounds over time instead of decaying.
CRO principles applied to AI search
Research over guesswork
In CRO, we never launched a test without a hypothesis backed by behavioral data. At Quoted, we never make a recommendation without longitudinal citation data behind it. The principle is the same: measure first, then prescribe.
Specificity over best practices
Generic CRO advice ("add urgency," "reduce form fields") was always wrong for specific contexts. Generic AEO advice ("add schema," "use answer-first") is the same. What works depends on your vertical, your competitors, and your buyers.
Compounding over one-time fixes
The best CRO programs weren't one-time audits—they were ongoing testing programs where each experiment informed the next. Quoted works the same way: every week of data makes your playbook more precise.
Let's talk about your AI search visibility
I built Quoted to help companies protect their investment in AI citations. If you're spending money to get cited and want to make sure those citations stick, I'd like to hear about your situation.