To be perfectly honest, this is a subject that I have been ignoring for the longest time. I thought A/B testing was just a buzz word that fancy marketers throw around at unsuspecting clients. Recently, I have been proving my past self wrong and starting to see the light.
It first started out with asking myself: “How can I help my clients succeed after their product has launched?” In my programmer’s mind, my first thought was how do we know what works and what doesn’t? In this article, I’m sharing with you what I’ve discovered about A/B testing.
First, let me explain what A/B testing is all about. Simple put, we’re testing two (or more) versions of something and seeing what our visitors respond to more. The “something” can be a website, a mobile app, or even non-digital things such as product packaging or business cards.
In this article, I’m strictly speaking of testing websites - how one design (A) compares to the second design (B). By doing this, we’re splitting our visitor traffic into separate designs and measuring which design performs best.
So you might be wondering how you can start A/B testing on your own projects. I was wondering the same thing too and had a little trouble at first thinking of things I should be testing. It really comes down to what you want your visitors to do when they visit your website. For example, if we run an online store, you may want your visitors to add an item to a shopping cart or if you run an online service, you want your visitors to sign up for an account.
So how can we encourage our users to take the desired steps? Or maybe another question to ask is what is discouraging our visitors? Is it the our marketing copy, colors in the design, is our navigation menu confusing?
All these questions can be answered with a couple A/B tests. If we’re not sure what is driving our visitors away we can start setting up a test that changes a few elements on the page. For example, here are some other things that we may want to test:
As a simple experiment, I created an A/B test for the Littlelines homepage. At the bottom of the page is our call to action button that takes our visitors to the contact page. My goal is to increase the frequency of clicks for our call to action button. In other words, I want to encourage our visitors to contact us. Thus, our conversion goal is to get visitors to click the button. So I setup an experiment using three distinct messages on the button as displayed below.
There you have it. We setup a simple experiment to see which of the three call to action buttons has the best effect. Okay, so how do we actually run this experiment in production? Well, there are a lot of choices when in comes to A/B testing including several open source options such as Facebook’s PlanOut, Etsy’s Feature, eCloudera’s Gertrude. And for Ruby on Rails projects, there’s Vanity and Split to name a few.
All of the above A/B tools require some programming knowledge. If your not a developer, no worries. There are several online services available that make A/B testing a snap without any technical knowledge required. See Visual Website Optimizer and Unbounce.
In our case, I’m using Optimizely to conduct our experiments. I find Optimizely to be a simple and easy tool that allows you to dive into A/B testing quickly. And perhaps the best part, it will collect the data for us and display the results into an easy-to-understand format. Checkout the results from our Littlelines homepage experiment:
I’ve been running this experiment for 13 days. Which begs the question, how long do we need to run our experiment? We don’t want to cut the experiment too early because we don’t want any false positives. It turns out this is not a simple answer. There are a few onlines resources that can help us including a calculator. Luckily for us, Optimizely will try to figure this out for us. Notice in top-left section of the graph above, it states our experiment is “currently inconclusive”. This basically means we have not let our experiment run long enough. Great, we’ll just keep this experiment running until Optimizely tells us otherwise. So far it looks like our original “friendly” button is leading - it was able to convert the most of our visitors, but we will have to wait and see if final tally before we declare a winner.
Along my A/B journey, I found a few good articles and videos that explain what A/B testing is and how some companies are using it to their advantage.
Mailchimp explains how A/B testing can improve your email marketing campaigns How does A/B Split testing works?.
Airbnb shows us how they run experiments Expirments at Airbnb and the common pitfalls they ran into and how we avoid them.
Although not specifically about A/B testing, Cap Watkins’ Etsys Product Design Principles talk at HybridConf 2013 gives us a little insight on how Etsy uses A/B testing to see which designs convert better.
Hopefully, I’ve illustrated how A/B testing can be a great tool to help inform us on decisions and how easy it is to get started today. If your using A/B testing on your projects, please share in the comments. I would love to know more about how well or not well it’s working for you.