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What Is A/B Testing in Marketing?
In the world of marketing and sales, an A/B test compares different versions of a sales campaign by randomly showing them to different customers, allowing marketers to see which version performs better. For instance, if Version A of an online marketing strategy outperforms Version B's click-through rate and conversion rate, marketers can use the split test results to design a unified campaign that incorporates the strengths of Version A and hits the best possible sales metrics.
How Does A/B Testing Work?
The A/B testing process involves comparing different versions of a marketing campaign, pricing scheme, website design, or promotion. The different versions must be served to prospective customers at random in order to achieve accurate results. For instance, when a company buys an online advertisement, it can arrange to have a select number of random customers land on Version A of a landing page, while an equal number of randomly selected viewers land on Version B of the same landing page. If, during this test run, one version of the landing page shows a better conversion rate, the company can then direct all incoming traffic to that version of the landing page.
4 Ways to Use A/B Testing in Marketing
A marketing professional might run a split A/B test to glean a wide array of information. Consider these five ways A/B testing applies to marketing campaigns.
- Pricing: What price point attracts the most new customers or subscribers?
- Ad campaigns: What type of advertising has the highest click-through rate and brings the most traffic to an e-commerce homepage?
- User experience design: Which version of a website influences user behavior by keeping customers on a page?
- Calls to action: What call-to-action methodology can inspire customers to engage with a brand by leaving reviews or writing testimonials?
4 Tips for Running a Successful A/B Test
To properly construct an A/B testing tool, you must consider several key factors.
- Know your goal. Running an A/B test is not as simple as posting two random iterations of a website or advertisement. The most effective A/B testing campaigns have a clear optimization goal, whether that's sales, engagement, or word of mouth.
- Set a fixed length of time for the test. Barring an unforeseen catastrophe, let your A/B testing run its full course before drawing conclusions. Resist the urge to draw conclusions in real time, lest you end up overemphasizing anecdotal events with little statistical significance.
- Collect a relevant sample size. The more data you collect, the more likely you are to have statistically significant results. Surveying friends and family may be better than nothing, but a truly random trial with many subjects is ideal.
- Test one variable at a time. Scientific testing, whether in chemistry or marketing, requires isolating one experimental element and changing it while all other elements remain constant. For instance, if you are trying out different versions of your website's call-to-action button, only change one aspect at the time. If you test different button colors, do not change the actual text of the button. If you change the font on the button, keep the words and color the same. If you experiment on more than one element at once, the test results will be harder to decipher.
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