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AI A/B Testing: How AI-Driven Optimization is Different

Conversion rate optimization (CRO) is an important and widely used strategy in enterprise marketing and product management. CRO teams at large companies run hundreds or sometimes thousands of experiments per year in an attempt to continuously optimize customer experience. A/B testing is one tactic of many in optimizing the digital experience for customers.

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The Problem

A/B testing just isn’t that efficient.

Experimentation has traditionally been limited to A/B testing as the principal tool for validating/rejecting conversion and personalization hypotheses for machine learning tools. However, most A/B tests do not produce positive results, and most companies do not have the necessary resources or traffic levels to run the number of A/B tests required to see a consistent ROI for money spent on website optimization. While A/B testing is still as an important tool for risk mitigation and data-driven decision making, gains from optimization remain out of reach for the majority of businesses.

The Solution

Test more ideas, faster.

Evolv AI uses artificial intelligence (AI) to improve the ROI of experimentation by increasing both test velocity and win-rate without increasing manual resources dedicated to optimization. Think of it as AI A/B testing. Evolv AI accomplishes this by efficiently evaluating a broad set of hypotheses within a single experiment. During an experiment, the system identifies which hypotheses are positively impacting performance and those which are not. Evolv AI’s A/B testing software uses this data to automatically generate new experiments consisting of a combination of the high-performing hypotheses—continually searching for higher-and-higher performance within an experiment. This enables businesses to quickly evaluate many designs without the manual effort and low win-rate of running a series of sequential A/B tests.