Liam wants to test the effectiveness of two different emails to improve his emails geared towards a younger audience. He only has a smaller sized audience for this, so will need to consider how he tests. Liam recommends testing with the first 15% of his audience, and then using the results to decide the email that is sent to the remaining 85%.

Liam's approach is flawed because A/B testing in Mailchimp typically requires a minimum audience size for each test segment to ensure statistically significant results. While 15% might seem like a reasonable starting point, if the overall audience is small, 15% could still be too few recipients to draw reliable conclusions. Mailchimp's A/B testing feature usually recommends a larger percentage for each segment (e.g., 20-50% for each variation) or a minimum number of recipients per segment to ensure the test has enough data to declare a winner with confidence. Testing with too small a sample risks making a decision based on random chance rather than actual performance differences.