A/B testing — also called “split testing” — is one of the most powerful ways to improve conversions, increase average order values, and provide a better customer experience on your website.
Unfortunately, there’s a lot of misinformation online about how to set up an effective test. It’s simple to miss easy wins and test things that don’t improve your bottom line.
The good news is running an effective A/B test may be as simple as going back to the basics. That’s why in this article, we’ll cover A/B testing best practices so you can get the best results out of every experiment.
Let’s dive in.
What Is A/B testing?
A/B testing is the method by which brands show two versions of the same website experience to two unique website visitors. The purpose of showing two variants of your website is to see how users interact with your brand or website differently based on those variables.
Every A/B test also includes a goal: what the brand hopes to achieve as a result of the experimentation. It can be quantitative (like increasing the size of an average order, improving checkout rates, and increasing overall conversions) or qualitative (such as improving a user’s understanding of something about your product or their preferences).
At my own business, Anatta, we’ve leveraged A/B testing to help clients validate big ideas, increase conversion rates on landing pages, raise the revenue per visitor, and improve customer satisfaction from mildly happy to extremely satisfied.
A small tweak can sometimes go a long way.
The Power of A/B Testing
When you do A/B testing in a scientific and strategic manner, you will:
- Learn the needs and wants of your customers to create a clearer picture of your buyer persona.
- Get actionable insights faster so that your company can earn more revenue.
- Develop a research-driven culture within the company that focuses on the customer and not the stakeholders.
But how do you know when to use A/B testing? Despite how common it is to hear that you should test everything, the most successful A/B tests are more targeted and carefully planned out.
The best time to leverage A/B testing is when you or a member of your team has a great idea about how to improve things on your site, but they have a hard time knowing whether their idea will move the needle.
In scientific terms, that means they have a hypothesis. A/B testing turns hypotheses into real numbers with statistical significance to help you make better decisions.
So here are four key ways to successfully improve conversions through A/B testing.
4 Ways to Improve Conversions Through A/B Testing
- Scrutinize the hypothesis.
- Perform user testing.
- Do a cost-benefit analysis.
- Learn fast. Implement faster.
1. Scrutinize the Hypothesis
Start by having the idea reviewed against competitors, colleagues, and even other businesses in your network. Is the idea being used by other people in your industry? An idea should require more than novelty to be implemented. It should stand on substantive evidence that the idea will work. If it’s not, throw it out.
Next question: Is your idea solving a real problem that a customer has brought up through conversations or support tickets? If it’s not, again, throw it out.
Lastly, if you take a poll of this hypothesis across other stakeholders (like the people in charge of revenue and acquisition), does it score highly as a problem to solve? If not, you guessed it, throw it out.
2. Perform User Testing
Once you have narrowed down your hypothesis to the most efficient ideas to test, create a few solutions to the problem. But keep in mind that you shouldn’t test all the ideas because the time to find an actionable insight takes double or triple the time with each additional variation.
The best path to take is to weed out diverging ideas through quick user testing. By getting the prototypes in front of real customers, you can easily find the one to two solutions that customers like best or find most useful.
Let’s consider an example. If you’re trying new navigation for a shoe company, you might sit down with a user and ask them to perform a certain task on your website. You can say, “If you’re looking for leather shoes, how would you do that using this navigation?”
Once they’ve accomplished this on their own using one navigation, pull up the second navigation option and make the same request. Then ask the user which navigation they preferred or found easier. This testing saves you a lot of time. It’s fast feedback that allows you to quickly eliminate ideas. The user will tell you which navigation they liked and which one they hated.
3. Do a Cost-Benefit Analysis
Before starting or developing an A/B test, do a true cost-benefit analysis to determine if running the test is worth it. This step follows user testing because through the user test you can determine obvious variables not to test. You get early, affordable feedback from a few users to inform whether you run the more expensive and long-term A/B test.
You can do that by adding up all the costs to create the test (digital product team time plus platform costs plus opportunity cost of something else not getting done while the test is running) versus the potential upside (increase in conversion rate, increase in cart value, and so on). If the benefits are greater, then prioritize the test accordingly.
4. Learn Fast. Implement Faster.
The objective of an A/B test is to acquire new information to help you create a final solution to present to your customers. Taking a lot of time to make the test perfect adds to the overall cost.
And remember: this is still just a test, not a full-scale solution. So treat it as such and get the test shipped quickly instead of waiting.
Just like SEO and paid ads, you don’t want to achieve growth by just throwing hacks and random tactics at a problem. You want to foster a strategy that empowers your company to see significant results toward a predetermined goal.
A well-defined A/B testing strategy can not only be quantitatively better for your brand and bottom line. It also helps you truly understand the customers you want to serve — and how to serve them best.
