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is thoughtfully curated or crafted by a human, for a human. We spend hundreds of hours every month speaking to experts with decades of experience. Our blogs are more a journalistic report on the state of experimentation than a single perspective article. Enjoy!
Let’s set the stage. A CRO team runs an A/B/n test with one control and four variations, tracking three success metrics across each layout. One metric on Variant C clocks in with a p-value of 0.04. The team declares a winner, ships the change, and waits for the revenue to...
If you have experience running experiments, you’ve probably noticed this: You design a variation, build it, and launch the experiment. Traffic starts coming in, but four weeks later, the platform returns a single word: Inconclusive. But after some time has passed, you try again, and four weeks later, the result...
Picture this: A team runs a textbook A/B test. The set up is clean and they don’t peek. Instead, they wait for significance and it never comes, so they call it a loss, ship the control, and move on. What they never realize is that the variation was better all...
Why does an Indian D2C founder still reach for an expensive global tool by default? Usually, because no one told them four of the best A/B testing tools were built by Indian founders, in rupees, for mobile-first traffic. This guide starts there, then covers the global platforms used widely in...
Look up experimentation in tourism, and you'll find tons of case studies from companies like Booking, Expedia, and Airbnb. These companies run thousands of tests a year on their own platforms, and Booking alone keeps over 1,000 experiments running at any given moment. That paints experimentation as a normal part...
When you run A/B tests, you most likely have your tool firing its script in one place and Google Analytics firing in another. Very rarely do both tools agree on how many people saw your test. This disagreement usually reads as a small, annoying thing you learn to ignore. Until...
