Articles exploring Behavioral Economics through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
20 articles
If you're running experiments under pressure, the hardest part isn't ideas. It's bet sizing: deciding how big a bet to place based on expected value, and how much traffic to risk.
If you've ever run a quick test without an experiment brief template that somehow turned into six weeks of meetings, rework, and second-guessing, you're not alone.
If stakeholders keep rewriting your experiment doc, it's not because they're picky. It's because your brief doesn't answer the questions they get judged on.
If you run home pregnancy tests frequently after a suspected conception, you'll feel the temptation: the result looks promising on day three, excitement is building, and you want the confirmation. Or the opposite, the home pregnancy test result is negative, and you want to pull the plug before you "waste" more on excessive testing frequency.
Stakeholder pressure in business strategy doesn't break your metric tree because people are unreasonable. It breaks because the tree isn't tied to a decision anyone is willing to defend. I've been in the room when revenue misses, the board wants answers, and every exec grabs the nearest metric to justify their plan.
When my experiment backlog gets long, my decision quality drops fast. Everything looks "important," every stakeholder has a favorite, and the loudest idea starts to win. That's when I fall back on the expected value framework. Not because it's fancy, but because it forces one thing: dollars first, o
If your team runs experimentation, you already know the ugly part: the results meeting turns into a debate about which metric "matters." Someone points at conversion. Someone else points at retention. Finance wants revenue. Product wants engagement. When you don't have a single North Star Metric, ev
Your top navigation is the set of street signs on your website.
Your consent banner is the bouncer at the door.
Most B2B SaaS onboarding doesn't fail because the product is hard.
Most B2B SaaS sites lose high-intent visitors in silence.
A good in-app upsell prompt feels like a helpful suggestion from a teammate.
A demo request form is a lot like a front desk at a busy office. If it asks visitors to fill out a binder before they can talk to someone, many will walk out. If it asks for nothing, you get prank calls, spam, and meetings that go nowhere. The goal for 2025 is balance: [ ]
Your pricing page is the decision engine for trial starts and demo requests.
Most SaaS teams already send trial onboarding emails. Few treat that flow as a focused conversion engine. If your inbox journey is an afterthought, you are leaving money on the table. Smart onboarding email ab testing can move trial-to-paid by double digits without more traffic or longer trials. Thi
Most signup funnels do not break at the big call to action. They leak in the tiny moments in between, like half-typed emails, abandoned password fields, or paused trial signups. That is where micro conversion optimization wins. Instead of staring at one top-line signup rate, you tune every small beh
Why do some A/B tests barely move your conversion rate while others unlock huge gains from the same traffic? You change a button color, move a headline, run the stats, and end up with a tiny lift that no one cares about. The problem usually is not your toolset. It is that most tests only [ ]
Every click on your site is shaped by cognitive shortcuts your visitors do not even notice.
A/B testing separates guesswork from evidence-based decisions.
The $20,000 Question - You're sitting across from a hiring manager. The offer is $140,000.