Understanding the basics of A/B testing

So, first things first: What is A/B testing?

In its simplest form, A/B testing (aka split testing) is when you compare the performance of a new version of an asset against your current version and see which one performs better. 

Marketers most often use A/B testing to fine-tune performance on things like landing pages, emails, and digital ads. These tests are a great way to dig into what’s working (and what isn’t) on these assets and really optimize their performance.

Here’s how it works:

  1. Set your goal: Choose a target and explain what you want to accomplish with your tests (e.g., higher conversion rates, better engagement).
  2. Pick the variable you want to test: Choose a single element to test (e.g., headline, CTA pricing).
  3. Create your variant: Develop a variant of your asset with a different version of the element you’re testing. Remember, you only have one variant with one change in an A/B test.
  4. Set up your test: Set up your test with an A/B testing tool to randomly split your audience and segment your traffic accordingly.
  5. Run your test: Launch the test and let it run for as long as you need to reach a statistically significant conclusion. This timeframe can vary widely, so it’s best to use an A/B test duration calculator.
  6. Analyze the results: Compare the performance of the two versions based on any metrics you’ve defined.
  7. Implement the winner: Roll out the version that performed better in the test to your entire audience.
  8. Iterate: Use the insights you’ve gathered to refine and iterate on future tests.

Why A/B testing is important

There’s one big reason why A/B testing is important: 

Data-driven decision making is critical for businesses everywhere.

Marketing departments face greater scrutiny as budgets and the economy get tighter. Removing guesswork and uncertainty from marketing activities is critical. 

And if you’re able to point to data that supports your recommendations and strategies, it’s that much easier to make the case for why your business should be doing X and Y instead of Z. Even if it’s something you know is gonna work, being able to refer to concrete details just makes it an airtight argument.

A/B testing is how you get the data necessary for making these strategies work.