Where Paid Media Strategy Meets Statistical Reality
Field-tested tactics, honest measurement, and frameworks teams can apply the same week.
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.
HOW WE Help
Where Paid Media Meets AI (Without the Hype)
Strategy & approach
Shawn understands the intersection of platform automation, AI-assisted media buying, and the fundamentals that still decide whether a campaign is profitable. He helps organizations figure out which automation to adopt, which to constrain, and how to tell the difference using their own data. He speaks regularly about where the leverage in paid media has moved: away from manual levers, toward the quality of the inputs and the rigor of the read.
BidWaves & scale
His approach is pragmatic and spend-tested, he runs real budget through unproven channels and publishes what did and didn't work, including the losses. BidWaves, his local and small-business arm, serves companies whose entire monthly budget is smaller than an enterprise test cell. Shawn works in both which in practice means enterprise-grade measurement rigor applied to small budgets, and small-budget frugality applied to large ones.
Teaching & outreach
Very few strategists work at both ends; the ones who do stop assuming a tactic that worked at one scale will work at the other. Shawn tutored the Google Ads Challenge at RMIT University Melbourne, helping students and working specialists launch and improve live campaigns with real budget. The same instinct carries into his conference and podcast appearances: he'd rather leave a room with practitioners who can run the play themselves than an audience that was impressed.
Signature Speaking Topics
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.
Key outcomes for the audience
Attendees learn how to size a test against their actual traffic volume, how to recognize when a result is safe to act on, and how to introduce a validation step into workflows where automation wants to move immediately.
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
What attendees will walk away with
A pre-test sizing method and a plain threshold for when a result is worth acting on.
How the leverage in paid search moved from bidding levers to input quality
About this talk
This session takes on the assumption that automation has made paid search strategy obsolete. Shawn breaks down what Smart Bidding and Performance Max actually optimize toward, why that frequently diverges from business outcomes, and where deliberate manual control still produces measurable advantage — built around real account diagnostics rather than platform talking points.
Problem it solves
Teams hand budget to automated campaign types, watch the platform report success, and lose the ability to diagnose why revenue isn't following. Without visibility into what the algorithm is being fed, poor conversion signal gets amplified at scale — and reporting looks fine the entire time.
Key outcomes for the audience
Attendees leave with a framework for deciding what to automate and what to control, plus a repeatable method for auditing the conversion signal their automation depends on.
Who it's ideal for
- In-house paid media managers and leads
- Agency practitioners running automated campaign types
- Founders and marketing leaders who own the budget
Key takeaways
- What automated bidding is actually optimizing for, and how that diverges from business goals
- How to audit conversion signal quality before scaling spend
- Where manual structure and exclusions still beat automation
- How to brief and constrain a Performance Max campaign so it stays accountable
What attendees will walk away with
A conversion-signal audit checklist and a clear decision framework for which levers to keep, which to hand over, and what to monitor after you do.
How a paid media team shipped its own auditing and budget-management platforms without a dev team
About this talk
Shawn built AuditIQ by BidWaves, an automated Google Ads auditing tool that scores accounts and returns prioritized reports, and the BidWaves Campaign Manager, the platform his team uses to manage client budgets. Both were vibe coded. This session covers what's now realistically buildable by a marketer with coursework-level development knowledge, where the real difficulty sits (data plumbing and API authentication, not code), and how to choose a first project that survives contact with production.
Problem it solves
Marketing teams work around gaps in their tooling for years because building software feels out of reach and vendors don't serve the specific workflow. Meanwhile the workaround costs hours every week.
Key outcomes for the audience
Attendees leave able to judge which of their own workflow gaps are now solvable in-house, and how to scope a first build that doesn't stall.
Who it's ideal for
- Agency and in-house marketing leaders with recurring tooling gaps
- Practitioners curious about building rather than buying
- Ops teams evaluating build-vs-buy
Key takeaways
- What's realistically buildable now versus what still needs engineers
- Why API authentication and data modeling, not code, are the actual bottleneck
- How to choose a first project with a real user and a narrow scope
- What breaks when a vibe-coded internal tool meets real client data
What attendees will walk away with
A scoping method for a first internal build and an honest read on the effort involved. Live example: AuditIQ by BidWaves.