Optimize your web experiences with multivariate experiments and approach your conversion strategies scientifically.

At face value, A/B or split testing may seem similar to multivariate testing. In practice, however, they are measurably different. A/B testing is a great tool to perform a series of tests on a series of items. Multivariate tests, on the other hand, are designed to test tens if not hundreds of variations, giving you a wide pool of data for your conversion metrics. If your web traffic is high enough to support them, multivariate experiments on your layout and funnel process are critical to reaching your business goals.

A great way to start is by having a “control,” which in this example is the existing design. From there you develop a few variations, and then experiment by testing a variety of common elements.

Deconstructing your web page.

To perform multivariate experiments on your page, we first start by deconstructing your layout into test units and deciding on what area to focus on.

From there, we create multiple variations and combinations of design and messaging of these test units. This provides the subjects of our experiments. Once all of the units are defined, we use software to catalog and monitor each test unit and to split your traffic equally to each specific scenario. With enough traffic and time, we can start to see results that show which items are performing better depending on particular outcomes we assign to the tests.

Other considerations.

We think it’s a good idea to slowly work up to multivariate experiments only after we’ve implemented some form of A/B testing to create a pool of data. We also do not recommend performing too many sectional test units at once, because it requires a lot of segmentation and variations to work effectively. It’s best to work your way through your layout and focus on the most important areas first, the ones that have a high impact on conversion. Another important question to ask is whether or not you have enough traffic to support running a multivariate test. The lower your daily traffic is, the more time you’ll need to wait in order to collect enough use-cases to get really accurate data.

Gain insightful analytics about your conversion rate along with finding great strategies that outperform your current benchmarks. Let us be the ones to guide you.

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A/B Testing Social Media