The B2B Marketer’s AI Search Action Plan
As the AI search landscape shifts before it settles, we provide four pragmatic steps you can take now to optimise AI search tools for demand capture.
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In this article we explore A/B testing for B2B marketers and why you might be wasting your time, or worse, believing the wrong outcomes.
A/B testing, also sometimes referred to as split testing or bucket testing, is a research methodology used to determine which of two variants is more likely to produce the optimal outcome.
In most cases the A version is the control (or often the live) variant and the B version is the test or “new” variant.
Traditionally A/B testing is a very effective way for marketers to test and optimise all sorts of outcomes, including copy, conversion and usability features or changes.
Quite simply, you put both variants live, split the traffic between them, and the version that performs best wins.
If you want to find out more how to optimise and test your B2B digital marketing campaigns or have any questions about B2B digital best practice, we’d love to chat. Get in touch!
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As the AI search landscape shifts before it settles, we provide four pragmatic steps you can take now to optimise AI search tools for demand capture.
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