Predictive A/B Testing: What It Actually Means, and What It Cannot Do

That knowledge helps you decide which ideas to build and test in your own shop, before committing design, development, and traffic.

This whitepaper explains how that works, what a prediction can tell you, and where its limits are.

Here’s what’s inside:

1/ What “predictive” actually means

The difference between evaluating an idea before you build it and changing how a test runs after launch.

2/ How past tests inform your next move

How results from comparable shops help you assess a test idea, and why context matters.

3/ What a prediction cannot tell you

Why a promising idea still needs to be tested in your shop, and why new ideas without a track record deserve room too.

4/ Which ideas to leave out

How rejecting weak hypotheses before development helps you focus your resources on more promising tests.

5/ How Apex puts it into practice

Test memory, a testing tool, and managed execution with the DRIP team. Predictions checked against real results.

We built one of the largest A/B test databases in e-commerce: 4.3 million tests from 151,000 shops, since 2011.

On top of it we built our own testing tool, Apex by DRIP.

Apex tells you which test wins before you build it, and runs your whole testing program in one place.

That prediction helps you prioritise. The experiment still has to prove the result in your shop.

Use the whitepaper to understand the approach and make better decisions about your next tests.

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