Have you ever wondered….

Would an orange “buy now” button work better than a green button?

Does a single page or a multi-page checkout encourage more sales?

Is it better to drive web traffic to the homepage or a different landing page?

You probably spend a lot of time asking questions like these. Maybe you’ve even built a list of ideas you believe will make your website convert better.

But how do you know for sure these ideas will work?

Companies with high converting websites use A/B testing to ensure every site change makes a positive impact.

What Is A/B Testing?

A/B testing is the process of using a randomized experimentation process, driven by statistics principles, to understand if a new site experience will result in a negative, positive, or flat improvement over time.

Put simply, A/B testing allows us to estimate, with a high amount of confidence, how much online revenue a web optimization will generate.

Here’s an example.

Let’s say we have a website that uses static imagery on all of our product pages. However, we want to know if replacing all static images with videos will increase our site conversion rate.

To answer this question, we need to have two versions of our product page:

The original product pages with static images (The Control)
The new product pages with video (The Test)

To understand which version generates a higher site conversion rate, we need to randomly split our website traffic so that 50% only sees the static image product pages and 50% only sees the video product pages.

We can then use statistics principles to determine how long the test needs to run and what impact we’ll need to see to call the test a win (if the video does better), a loss (if the static image does better), or flat (if the results are inconclusive).

Of course, we love test wins because we can translate those wins into an estimated revenue impact for the year ahead. But even if the test loses, we’ll have stopped ourselves from making a website change that could have hurt our website conversion rate.

Data-Driven Decision Making

At Reusser Design, we believe there’s a process behind making data-driven decisions for your business.

That’s why we believe clients who use A/B testing to optimize their online businesses will see the biggest revenue impact, even in the short term.

But what does A/B testing mean for your long-term goals?

Building an A/B program with a consistent testing roadmap will help you:

See online revenue increases year-over-year
Estimate and plan for future online revenue growth
Make data-driven business decisions
Learn more about your customers
Use your online investment budget strategically
Maintain a high ROI on your site investments

How To Launch Your A/B Testing Program

Launching a program isn’t as easy as investing in a tool and starting your first test. There are five things every successful program needs:

Tools - You’ll need a testing tool (like Google Optimize or Optimizely) and an analytics tool (like Google Analytics).
Team - Every testing team needs a testing strategist, analyst, designer, and developer.
Data - You’ll need to use quantitative and qualitative data to build your test hypothesis. Then, when your test is live, your analytics data will help you understand whether or not your test was successful.
Strategy - Your A/B testing strategy will help develop your program goals and testing roadmap. A good testing strategy will also help you make sure you’re testing data-driven hypotheses.
Process - Testing requires a reliable, repeatable process that takes you from test ideation to test insights quickly.

The best thing you can do for your digital business is invest in a method for data-driven decision making.

At Reusser Design, we’re committed to helping you optimize your web performance and improving your business using the web traffic you already have.

Are you interested in launching an A/B testing program? Reach out to get started!

Make Revenue-Driving Business Decisions With A/B Testing