A/B testing allows you to make side-by-side comparisons of marketing assets with slight variations. By testing new variants against old ones, you can zero in on the winning formula to increase your success. Effective A/B testing requires a special approach using these four keys.
- Use a Testing Tool
A/B testing is dependent on running two variations of an ad simultaneously using identical conditions. Because of these parameters, using a testing tool will ensure you have the right statistics and proper comparisons to find statistical significance.
- When you’re not getting enough traffic
- How significant your results are
- When you can safely stop running the test
Knowing when to stop running the test is important as you need to be certain you have collected enough data for statistical confidence.
- Test One Variable at a Time
Your digital marketing assets have many variables that you can test. Images, text, headings, CTAs, buttons, color, font, and more can all have an impact on results. By choosing one variable at a time, you will know which one is responsible for changes, good or bad.
By keeping everything organized based on one change, you can get relevant, easy-to-understand results that you can act upon. Track behavior to look for data that shows proof something works or doesn’t work. You can then optimize this variable for the next test.
- Use Effort and Impact to Prioritize
Prioritize your A/B testing variables using a quick “effort and impact” model. This model allows you to rate the effort involved and potential impact expected when you change a variable.
Effort considers how hard it will be to perform the test. For example, writing new headings is harder than changing the color of a button. Impact considers how a test can bring you closer to your goals and improve your bottom line.
Rate each variable from 1 to 10 for both effort and impact. You want to start with the variable that takes the least effort and will have the highest impact and make your way down to the hardest tests.
- Set Goals
Although testing tools often allow you to set more than one goal, you should always have a main goal in mind. In most cases, you will be generating clicks, but deciding what you want from those clicks is critical to your testing.
If you change a heading or the color or wording of your CTA for example, it might generate more clicks but not do much for lead gen. If you look at the number of clicks and decide, “Yes, this was successful,” then you might miss the critical fact that you are getting more clicks but fewer leads.
It makes more sense to set goals that get people further down the conversion funnel as opposed to something less specific, like getting more clicks.
Following these four keys will allow you to complete methodical A/B testing and help improve your digital marketing success.
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