Neural A/B Testing is a feature designed to optimize conversions and direct traffic to options (pages or checkouts) that show better statistical results, using a mathematical algorithm to analyze traffic and conversions, directing visitors to the best-performing options.
This feature is useful when you want to increase conversion rates, whether for leads, checkouts, or sales through optimized traffic distribution.
In Guru, the main types of Neural A/B Testing are:
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Checkout: optimizes conversions by directing traffic to the best-performing checkout links;
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Leads: optimizes lead capture, directing traffic to pages that capture more leads;
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Sales: optimizes sales conversions, directing traffic to the best-performing sales pages.
How it works
The Neural A/B Testing divides traffic between different options (checkouts, landing pages, sales pages) and, based on the performance of each option, directs more traffic to the options that show better results, and this is done through an algorithm that calculates a score conversion for each option.
When using Neural A/B Testing, the corresponding P.P.C.T. (for checkout, leads, or sales) should not be used, as A/B Testing replaces it.
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