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Shawn Walker is
A paid media strategist with over 13 years of experience helping organizations turn automated ad platforms into accountable growth channels.
As a speaker, he pairs hands-on platform execution with executive-level media strategy, showing leaders and practitioners where automation genuinely outperforms and where it quietly wastes budget. Shawn works both ends of the market, enterprise programs at Symphonic Digital, a Google Ads Premier Partner, and small local businesses at BidWaves, across B2B and B2C. He is known for bringing statistical discipline to a field that increasingly assumes the machine has already done the thinking.
Paid Media Leadership Built for Accountability
Shawn's range is unusual: monthly budgets from $1K tests to multi-million-dollar accounts, B2B pipelines and B2C purchase behavior, enterprise stakeholder complexity and single-owner local businesses. That spread is what shaped his standard of proof, the same result can be a clear win at one scale and statistical noise at another. He has worked on multiple award-winning campaigns.
He's known for the accounts nobody wants to inherit: broken conversion tracking, structures that cannibalize themselves, automation running unsupervised on bad signal. But the failure his teams find most often in audits isn't technical, it's a confident decision made on a sample that could never have supported it. Closing the gap between what a report claims and what the numbers actually establish is most of the job.
Significant, or Just Noise?
Why automated optimization makes statistical rigor more important, not less
About this talk
Machine learning now makes optimization decisions faster than any team can validate them. Shawn covers what statistical significance actually requires at real account volumes, why most paid media tests get called before they're readable, and what a defensible test design looks like when the platform is already acting on partial data.
Problem it solves
Teams kill winning creative and scale losing campaigns because they're reading noise as signal. Automation accelerates the damage, it acts on thin data instantly and at scale, and the performance report that follows appears to confirm the decision. Nobody in the chain is incentivized to question the original read.
Who it's ideal for
Paid media practitioners running creative, landing page, and structure tests
Analysts and reporting owners
Marketing leaders who shift budget based on test results
Key takeaways
What sample size your account volume can realistically support
Why most paid media tests get called two to three weeks too early
How to design a test that platform automation won't contaminate
The significance failures that surface most often in audits