Know What Works
Practical Advertising Measurement
Learn how to find out whether your advertising is actually creating sales—not just taking credit for them.
Google, Meta, TikTok, Amazon and other platforms provide enormous amounts of performance data. But seeing that someone bought after seeing or clicking an ad doesn't tell you whether the advertising caused the sale.
Know What Works is a practical live workshop for marketers who want to make better advertising decisions using better metrics, causal analysis and controlled experiments.
October 13, 2026 | 1:00–5:00 PM ET | Live Online | Limited to 25
Early registration: $495 through September 15 | $595 thereafter
No advanced statistics background required.
Stop Asking the Platforms to Grade Their Own Homework
ROAS, attribution and platform reporting can help manage campaigns. But they don't necessarily answer the question that matters most:
What happened because I advertised that wouldn't have happened otherwise?
Know What Works teaches you how to evaluate the evidence and make better decisions about what to scale, maintain, cut—or test further.
What You'll Learn
How to choose metrics that reflect real business outcomes
Why ROAS and attribution can give misleading answers
How to distinguish correlation from evidence of causation
What you can learn from pre/post analysis, matched markets, synthetic controls and other causal methods
When controlled experiments are—and aren't—the right approach
How to evaluate Google, Meta, TikTok, Amazon and other advertising investments
How to test a new channel before committing significant budget
How to turn measurement into a decision: scale, maintain, reduce or retest
The goal isn't to turn you into a statistician. It's to help you make better advertising investment decisions using stronger evidence.
Test Before You Become Dependent
Businesses are understandably reluctant to turn off advertising they already depend on.
So start somewhere else.
Test your next channel before you become dependent on it.
Considering TikTok, Amazon, CTV, Performance Max or another new investment? Learn how to establish an independent measurement approach from the beginning—before platform-reported performance becomes the basis for scaling your spend.
Who Should Attend
Designed for business owners, ecommerce and DTC marketers, growth and performance marketers, agency practitioners, consultants and analysts who want a better answer to:
"Is our advertising actually working?"
Learn It. Apply It. Prove It.
Level 1 — Learn
Attend the live workshop and build a practical foundation in modern advertising measurement.
Level 2 — Apply
Bring a real advertising question to Central Control for a guided measurement project. When experimentation is appropriate, use Experiment Designer (ExD) with expert support to design and analyze the test.
Level 3 — Prove
Demonstrate your ability to evaluate evidence, choose appropriate measurement methods and translate results into sound advertising decisions to earn Central Control certification.
Inaugural Live Workshop
October 13, 2026 | 1:00–5:00 PM ET | Live Online
A four-hour, instructor-led working session for marketers who need to know what their advertising is actually causing—not just what their dashboards say.
This isn’t a four-hour webinar. You’ll work through real measurement problems, examine cases where conventional advertising metrics give the wrong answer, and learn how to choose and design tests that produce evidence you can act on.
The workshop is live online via Zoom. Participants will receive the workshop recording, transcript, presentation materials and worksheets afterward.
During the workshop, you'll:
Diagnose where ROAS, attribution and platform reporting can mislead
Learn when randomized experiments are the right tool—and when they aren't
Work through practical examples of geo experiments, matched markets and synthetic controls
Learn how to choose business outcomes and KPIs that answer the question you actually care about
Practice turning an advertising question into a testable hypothesis and measurement design
Apply the framework to a real measurement question from your own organization
You'll leave with:
A practical framework for evaluating advertising measurement claims
A method-selection framework for choosing the right measurement approach
Experiment-design worksheets and reference materials
A first-pass measurement plan you can use with your own team
Certificate of completion
Meet Your Instructors
Rick Bruner
— CEO
Rick has led research and product organizations at Google, DoubleClick, Viacom and Marketing Evolution and worked on advertising measurement and causal inference with leading brands and platforms for decades. He is Vice Chair of I-COM and founder of the Research Wonks community.
John Chandler, PhD
— Head Scientist
John is a statistician specializing in geo-experimentation, MMM and incrementality testing. Formerly Research Director at Microsoft Advertising, he pioneered multitouch attribution and invented Microsoft's GRP & Reach Forecaster. He is also Assistant Professor of Data Science at the University of St. Thomas.
Talgat Mussin
— Senior Consultant
Talgat has led geo-experimentation and incrementality work at Google, Amazon, TikTok and X, running more than 100 experiments covering hundreds of millions of dollars in media spend. He advises senior executives and marketing teams on turning rigorous measurement into better investment decisions.
Limited to 25 participants.
Early registration: $495 through September 15
Regular registration: $595
Register for the October 13 Workshop →
Want to bring Know What Works to your team? Private workshops are also available for companies and agencies.
Ask About a Private Workshop →
Why Central Control?
Central Control specializes in evidence-based advertising measurement and randomized controlled experiments. Our team has experience building and applying measurement systems at companies including Google, Microsoft, Amazon and IAG.
We created Rolling Thunder, a geographic randomized controlled trial methodology for measuring advertising incrementality without PII or individual-level tracking.
Advertising works. It's measurement that's broken.
And the risk isn't just wasting money on advertising that doesn't work.
It's cutting something that's actually working because your measurement got it wrong.