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A/B Testing

A/B split testing is a method of comparing a variety of single-variable test samples to determine which changes will improve response rates. A/B testing is used heavily in web marketing to optimize page design by seeing which design combinations work, and which ones don’t. Using this testing technique, a webmaster can experiment with variations of calls to action, color schemes, wording, forms, layouts, and pricing on their pages to find the optimal configurations that maximize conversions.

These tests are executed by running two variations concurrently, wherein one portion of your audience sees a control page and the rest of your visitors see the altered page. By measuring and comparing conversion rates of the two versions over time, you can analyze the results to find out which variation produced the most conversions. Conceptually, it is a relatively simple process and is illustrated in the diagram below from Smashing Magazine:

A/B Testing Chart

Technically, there are a number of moving parts needed to make the testing possible, which can complicate the process. Your web application must have the logic in place to either deliver multiple flavors of a given page or redirect specific visitors to entirely different pages and be able to track conversion rates for each test. Many organizations rely on A/B tools available in the marketplace to handle this task, which can involve redirects, additional scripts, and altered page delivery.

Here is where issues often arise… The introduction of this logic, whether 3rd party or homegrown, brings about additional fail points and performance bottlenecks in money-making conversion paths.

Slower, less reliable applications will have lasting negative effects on a company’s conversion rates, sales volumes, and brand name. Because of this potential pitfall, you should monitor the performance and availability of your click paths. Rigor can help by using transaction checks to track the quality of the A/B testing system from end to end. By using Rigor, you can verify that both versions–and the system as a whole–are performing as designed and not frustrating your users.

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