A/B Test Emails More Often & Aggressively
A/B testing in email campaigns is inconsistently adopted across multiple segments of the market, despite most email marketing platforms offering this functionality. It’s time to start using this more often and aggressively, especially when you have more to gain from the insights it produces.
Common objections from marketers around A/B testing are typically a combination of complexity, audience size, and being overloaded. The benefit is the complexity is way lower than it has ever been with platforms taking care of the maths and execution.
Audience size is an important point if we’re caring about the semantics of “significance” in a statistical sense, although this alone should not dissuade you from A/B testing.
As for being overloaded, this is typically a mix of being asked to try many different things by stakeholders or feeling like its a difficult task because it does not have a repeatable process.
Regardless of your reasoning, approach A/B testing with a framework that grounds your tests to one dimension of the AIDA funnel (attention, interest, desire, action).
For each email campaign you’re executing, follow these steps:
Define & align your goal to one dimension of AIDA
Create your A/B variants & confirm what you’re testing matches your selected dimension
Execute your campaign over two weeks & review the results
Here’s a quick reference on what to test and the metric to measure aligned to AIDA.
Attention: tweak subject lines, measure open rates
Interest: tweak body copy, measure overall click through rates
Desire: tweak specific blocks of content, measure click through rates on that content
Action: tweak calls to action, measure conversion rates
TLDR: A/B testing is equals part an art and a science. Use a framework like the one above to make it easier to execute tests regularly.
