User Experience (UX) Research
Data drives successful marketing decisions. Leaders don't want to make their next move without the evidence to back it up. Thankfully, there are multiple ways to get information to back up strategy. One of the most common methods is A/B Testing.
However, effective A/B tests require sound research. Marketers who run tests without researching their customers and understanding what affects conversion rates waste valuable resources. To set you on the right path for A/B Testing, let’s dive right into how research can help you develop a testing strategy that gets you the key data to rev up your marketing.
A/B testing (also called split testing) is a tried-and-true method of marketing strategy. With A/B testing, marketers apply the scientific method by making a change to their website or product and then measuring the effect on their desired metric. A/B testing is broken down into a few essential elements.
A/B testing involves testing an original design or idea ("A") against an alternate design ("B") to see which produces better results. "A" is the control, and the alternate "B" is the variation.
For example, in A/B testing, “A” could be the current product landing page and “B” is the updated landing page, with new graphics. When you run your A/B test, you can test them to see which one leads to more sales.
A/B testing is effective because it allows marketers to compare two versions of something to see which performs better. By running tests, they can gather data about what works and what doesn't.
You can't jump right in and test hypotheses without a strategy. So, keep in mind that there are two different types of A/B testing.
The beauty of A/B testing is that you can use A/B testing to test anything measurable: headlines, calls-to-action, images, forms, etc. Ultimately the goal of A/B testing is to improve the performance of your website or product. This is why brands are keen to use A/B testing in all sorts of ways.
Headline Tests. Test different headlines to see which one performs better. The headline determines whether someone clicks on your page.
Call-to-Action Tests. Test different calls-to-action. The call-to-action tells the customer what to do next and convinces them to take that next step.
Image Tests. Test different images. The image is what catches the customer's eye and draws them in.
Form Tests. Brands can test different forms. The form is how you collect information from your customers. You want to make sure it's easy to use and effective in getting the information you need.
Brands can also use A/B testing to increase conversion rates on websites or landing pages. Or to improve the engagement of their email or social media campaigns. When used correctly, A/B testing can be a powerful tool that helps you understand your customers and what converts them. But, A/B testing is not a silver bullet, and you should use it as part of a larger optimization strategy.
Over the past 20 years, A/B testing went from an open secret in digital marketing to an industry standard in Silicon Valley. There are many reasons brands turn to A/B testing, but the main draw is that news ideas can be tested by focus groups in real-time. Rather than wait weeks or months to analyze data, brands can get results instantly. This means they can make changes to their strategy quickly, to make the most of marketing efforts and budgets.
A significant benefit of A/B testing is the data. A/B tests provide valuable insights into consumer behavior and you can use this data to improve the performance of your website or service.
Let's say you're investing in Google Ads. You can set up A/B tests that track the click-through rate (CTR) for three different blog articles. After running the test for a week, you can measure which title had the most click-throughs. You can use this data to structure your campaign and improve your return on investment (ROI). This is more effective than randomly choosing a title and hoping it performs well.
You can use A/B testing to test different hypotheses. This helps you avoid making changes that could potentially hurt your business.
For example, let's say you want to add a new call-to-action (CTA) on your homepage, but you’re not sure how it’ll perform with your customers. You can create an A/B test that measures the conversion rate of visitors who see the new CTA vs. the original. If the results show that the new CTA decreases conversion rates, then you know that it's not an effective change.
You can run A/B tests with minimal cost to help you quickly make informed decisions. Running several tests with new iterations can help you tweak your strategy and make improvements along the way.
Rather than making a hefty investment into a social media ad campaign targeting one demographic group, you can invest in short-term A/B testing across two different demographic groups. In a few days, you can see which ad is performing better, review your data and make the changes you need to perform better.
It might be tempting to skip the research, but it's not efficient to test random guesses. You'll rarely see optimal results, leading to frustration and a waste of resources. Instead, start your A/B testing with solid marketing research.
Research begins with data collection. Here are a few of the most common A/B testing research strategies.
Website heat and scroll maps. Heat maps are visual representations of where people click on your webpage. A scroll map shows how far down visitors scroll on a page. You can use these to identify areas of your webpage that are performing well or that need to be improved.
Surveys. You can use surveys to collect data about customer satisfaction, needs, and wants. This research helps you understand what's important to your customers and how to improve your product or service.
Customer interviews. Talk to customers about their experience with your product or service to identify areas of improvement and customer pain points.
Google Analytics. Spend time in Google Analytics to learn how people's behavior. What are they doing? What's the path they take to purchase? How can you replicate these behaviors on your website? Go into the Google Analytics admin panel and work through how to configure your goals, segment, and events.
Heuristic evaluations. During a heuristic evaluation, you go through a checklist (with the help of two other people) to evaluate your website's conversion performance. This pinpoints usability flaws and bolsters conversions.
A/B testing is a great tool, but it won’t solve every problem. So, when is A/B testing right for you and your idea?
Well, there are two main criteria to consider.
Campaign Performance. If your digital marketing campaign is underperforming, you may use A/B testing to isolate and improve it.
New Strategy. You're launching something new (a web page or an email campaign) but unsure which approach will work best. You can use A/B testing proactively to compare the effectiveness of two distinct strategies to find the superior one.
Keep in mind, that A/B testing is an effective measure of marketing efforts, but it's not suited for providing metrics on holistic concepts like customer satisfaction or loyalty.
When it comes to A/B testing, there’s no one-size-fits-all solution. You should tailor your testing strategy to your specific goals and objectives.
Create a detailed buyer persona. Before you can build a testing strategy, you need a detailed understanding of your target customer. Create a buyer persona that considers age, gender, location, interests, and pain points.
Determine your goals. Determine what you want to achieve with your A/B tests. Do you want to increase conversion rates, click-through rates, or something else?
Identify what to test. For example, the copy on a landing page.
Create your hypothesis. Create a hypothesis about the impact on your goal. If you're testing a button's color, your hypothesis might be that "changing the button color from green to blue will increase conversion rates by X%."
Choose your metric. Choose the metric you want to track. Some examples include conversion rate, click-through rate, and bounce rate.
Set up your A/B test. Once you've created your hypothesis and chosen your metric, it's time to set up your A/B test. You'll need two versions of your web page, email, or other elements––the original (control) and the variation.
Test and analyze your results. When you're ready, analyze the results. This will involve looking at the metric you're tracking and determining which version performed better.
Document and make changes. After you've analyzed your results and decided, it's time to document your findings and implement them on your site.
Don’t make guesses hoping they’ll work. Instead, invest in research and A/B testing. Equipped with a solid A/B testing strategy, you’ll be rewarded with valuable insights into your customers that you can use to improve your brand. A/B testing is a complex process, but with the right research and preparation, it can be an invaluable tool for any business.