A price cut fills one calendar by emptying a neighbor's — is your A/B biased?

Experiment designHard

Problem. You test a price-guidance change that lowers suggested prices. You randomize listings 50/50 and measure bookings. Results look great. Why might they be overstated, and how would you design the test properly?

Before you reveal: say your answer out loud, as if you were in the real interview — get your reasoning across clearly first. There is no single correct answer: reading what the interviewer is really after and defending your own thinking is what makes an answer strong.

You can't cleanly randomize a pricing launch — how do you measure it? →