The Rise of the Modern Mad Scientist (Now with Slide Decks)
In an age where the phrase “marketing science” once meant throwing spaghetti at the wall to see what stuck, we now live in a time where control groups, A/B tests, and incrementality reports have become the new creative briefs.
According to WARC’s Future of Measurement 2025 report, the number of marketers using experiments to measure effectiveness has doubled in the last year — from 18% to 36%. That’s not just a trend; it’s a full-blown identity crisis for every marketer who once relied on vibes.
A visual metaphor for the marketing industry’s shift from instinct to insight—where laptops run experiments and dashboards become oracles.
From Attribution Myths to Causality Worship
Marketers have finally started whispering what scientists always knew: correlation isn’t causation. Traditional attribution models, once the sacred cows of digital marketing, are now being slowly escorted off the measurement stage.
Experiments are stepping in with their nerdy glasses and impeccable methodology to isolate variables and declare, with empirical flair, that yes, your campaign might have done something useful.
“Once considered the preserve of advanced advertisers, the next 12 months in marketing measurement will be defined by a growing democratisation of tools and methods.” — Paul Stringer, WARC
Translation: welcome to the party, everyone. Even if you brought Excel and a nervous intern.
Why the Sudden Obsession?
1. Platforms Finally Decided to Help (Sort Of)
Meta and Amazon now offer built-in experiment tools. So even if you don’t know what “incrementality” means, you can now click a button and look like you do.
2. AI Makes Testing Less Painful
AI can now test more variations of creative than your creative team can dream up on caffeine. Faster, cheaper, and without complaining about the brief.
3. Because ROI Still Feels Like a Mirage
Despite having more data than ever, most marketers still feel like they’re shouting into the void. Experiments offer something rare: clarity. Or at least the illusion of it.
What Experiments Actually Get Right
- Causality: Finally, a way to prove your campaign did more than just coincide with a seasonal uptick in sales.
- Incrementality: You get to measure actual lift, not just wishful thinking wrapped in a dashboard.
- Courage: You can finally try something weird, measure it, and not get fired. Probably.
“Experiments are a gateway drug to real marketing insights.” — Every data nerd ever
Let’s Not Romanticize Too Quickly
1. Experiments Are Snapshots, Not Sagas
They give you a view of now, not the long-term impact of brand-building. Spoiler: Your experimental uplift won’t tell you what happens in Q4.
2. Platform Experiments = Black Box Theatre
You’re still at the mercy of Meta’s definitions of success. And good luck comparing across platforms.
3. Still No Unified View of ROI
Cool, your test worked. But what about your radio ads? Your PR stunt? Your SEO?
Best Practices (That Make You Sound Smart in Meetings)
- Have a Hypothesis: “Let’s just see what happens” is not a strategy.
- Measure What Matters: Use success metrics tied to business outcomes, not vanity KPIs.
- Mix It Up: Combine experiments with marketing mix modeling (MMM) and brand health tracking.
- Build a Learning Agenda: Connect one experiment to the next. Otherwise, you’re just playing Whac-A-Mole with your budget.
The Future: More Nerds, Fewer Gut Calls
High-performing marketing teams (the ones actually overachieving on revenue goals) are leading the charge in using both AI and experimentation.
What’s next?
- Hybrid AI-human measurement frameworks
- Integrated experimentation + MMM dashboards
- And a CMO who asks for a Bayesian prior instead of a TikTok brief
Final Thoughts (and a Measured Mic Drop)
The 18% to 36% leap isn’t just a stat — it’s a cultural shift. Measurement isn’t just about proving ROI anymore; it’s about learning. Marketers are trading superstition for substance, and in doing so, becoming a little more like scientists and a little less like street magicians.
So here’s to more controlled chaos, beautifully randomised trials, and never again launching a campaign without asking, “What exactly are we trying to prove?”