Why A/B Test?

“Every experience consumers have can be made a little bit better,” says Marc Andreessen, founder of Andreessen Horowitz. He’s right, today’s digital atmosphere offers nearly limitless opportunity for the optimization of content and design. Instant analytics from digital experiments allows for more actionable insights and data-driven strategy. Though it can be an arduous task, A/B testing can have a powerful impact on the success of a digital initiative.

Let’s say your business is looking to acquire leads through form submissions on a landing page. Your form fields capture all required information, your color scheme matches your logo and you’ve proofed your content a thousand times. While the page is getting plenty of traffic, you’re frustrated that people still aren’t clicking “Submit.” Rest assured, you’re not alone.

Landing page optimization can be overwhelming – how do you know what to change, what to leave alone, what to make bigger, smaller or brighter? While there are best practices and abundant case studies to give you direction, the answer is simple – you probably don’t.

That’s why A/B testing is so useful. Divide your traffic into two groups and serve them different variations of the same page, testing the impact of the changes made. This allows for isolation and optimization of one element at a time, making tests more manageable, predictable and valuable.

By monitoring page analytics, you can determine which version performs better on the metrics you’ve defined. The winner becomes the new control and you repeat the process, testing this page against a new variation. Regardless of the variables you test, the idea is to try new things, develop stronger insights and move forward with more effective marketing.

With A/B testing software like Optimizely and Unbounce, digital marketers now have access to robust on-page editing tools that allow multiple variations of your page to run simultaneously to carefully targeted audiences. By setting goals to track specific elements of user engagement, we have the power to view live analytics that enable real-time adjustment and action.

It’s important to realize A/B tests won’t always result in good news – changing some variables will occasionally harm user engagement. In order to find what works, you have to be okay with finding out what doesn’t.

“Big improvements can come from a whole bunch of incremental gains,” says Andreessen. When it comes to A/B testing, the best thing to do is keep placing one foot in front of the other.

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