Step 2: The Hypothesis Creation Equation

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The A/B Testing Quick Start Toolkit

Now that you have a prioritized list of variables to test, you need to make sure your tests have a clear purpose. This will help you decide if your variations were successful, negative or inconclusive.


A hypothesis will also help you capture important insights about your audience that you can incorporate into future tests and marketing efforts.

To do this, you must clearly state a hypothesis before designing your test variations.

Although that sounds complicated, it’s not.

Use the following Hypothesis Creation Equation to make your own A/B test hypotheses:


Changing (element/variable) from X to Y will (result) due to (rationale/research).

Now, State Your Own Hypothesis

Take your highest priority testing variable from Step 1 and plug it into the Hypothesis Creation Equation above so you can create your own hypothesis.

Let’s say you own a yoga studio and offer a free class for people signing up to your mailing list. If you decide to A/B test your call to action (CTA) button text for your lead generation page, your testing hypothesis could look something like this:


Changing my CTA button text from “Get Your 1st Yoga Class Free!” to “Start My Yoga Journey Now” will increase email subscribers due to the value proposition of “Getting Started” resonating much stronger than “Get a Free Yoga Class” for getting new leads to take action.


If the test confirms this hypothesis, than now you have a stronger marketing message to use with your audience in everything from Facebook ads to opt-in form offers.


Now, with your new A/B testing hypothesis in hand, click the next lesson arrow below to begin Step 3 and learn how to design your A/B testing variations.

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