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Why A/B Testing is Important

Missy Hildebrand | May 20, 2015 Comments
NEI love Data

We're big data nerds here at Americaneagle.com. Data gives us insights to answer the who, what, where, when, and why of website interactions. It tells a story of a site's successes and failures. Data guides our decisions that we hope ultimately lead to favorable outcomes, and it also helps us turn around and start again when we've faltered. Data is everywhere, but only truly reveals its value once it's evaluated, consumed, and ultimately applied.

Our secret ingredient for extracting value from data is testing. And if you're looking to enhance your online business, utilizing well executed A/B testing is the key to success.

You might be thinking "A/B testing is no secret… even presidential campaigns have used it". And you're absolutely right. But the thing is, while everyone seems to be talking about it, nobody is really doing it. A/B testing, or split testing, studies user behavior by testing hypotheses about how website visitors react to difference versions of site content. For instance, will your customers be more likely to click a call-to-action that says "Save 20% Now" or "Take 20% Off"? The information gleaned from this type of testing can then be used to optimize your site and zero in on what's really effective in getting users to do what you want.

What Are The Benefits?

A/B testing offers 3 concrete benefits:

  • Improved Content – A/B testing often leads to better site content because you need to identify which content is valuable and why. Then, once you generate variables to be tested, you begin to fine tune which version of that important content gets the message across most effectively.
  • Become More Profitable – Companies that use A/B testing have more time and resources to spend on actually implementing changes, rather than debating. This is because they value data over opinions. These businesses are nimble and are able to quickly adapt to changes in the marketplace by looking at the data.
  • Accurately Measure Performance and Behavior – Wouldn't it be nice to take the guess-work out of your decisions? By employing A/B testing, you ultimately can. It gives you the cold, hard data that clearly indicates which variation is the winner. It also reveals how your target market will react.

Why Does It Work?

Utilizing this type of testing lets you see which content or variation causes your visitors to spend more time on your site, click through to additional pages, submit forms, make a purchase, or any other desired action you want them to take. If your goal is to increase email signups, you can test different call-to-action designs to see which one leads to higher acquisition rates. Instead of trying to predict what your visitors might want or do, you can actually know.

What Are The Results?

Not all results are the same for our clients. Tests can be inconclusive and take a lot of evaluation to determine the correct outcome. But if executed properly, many of our testing clients have seen reduced bounce rates, increased conversion rates, higher conversion value, and more sales overall.

I'm Convinced! When Do I Start Testing?

  • There's Only One Goal – It is important to remember that A/B testing works best when there is only one clear outcome to measure per test, examples being which version of an email gets the most clicks or which page gets the most amount of clicks. If you try to measure more than one goal, the results could get messy.
  • The Outcome Needs To Be Measurable – If you can't measure it, then you can't determine what works best. You can't decipher customer satisfaction from an A/B test compared to what customers prefer.
  • The Design Needs to Be Complete – These tests work best when you have a completed design. The idea is to conduct A/B testing to make minor changes that yield better results.

1 review

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  1. Chris Walters | Jul 13, 2015
    5.0000000000
    It is important to build a testing backlog during a website redesign and new CMS implementation to validate any design assumptions that were made during implementation.

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