Marketers will always seek ways to improve their online presence, and there’s no better way to solidify concepts than to employ the services of good ‘ole scientific method. Tests provide measurable proof on whether or not certain changes are to be made, instead of making drastic decisions out of pure guesswork.
A/B testing is basically the testing two ideas; one is a proposed new concept while the other is the normal or controlled condition. For example, a marketer tests two kinds of Facebook posts – one with a photo and one without – and see whether the addition of photos make a significant difference in terms of audience response.
However, despite of their admirable intentions to improve lead generation, marketers are either reluctant of or oblivious to what exactly it’s all about. Here are some of the questions you may have come across with during your data gathering about A/B testing:
When should A/B testing be done?
It’s only logical to do a test when there is a clear question in mind. If you add X to your current system, will it improve? Are people more likely to respond favorably to the color X or color Y? If a blog post has X number of words, will it increase likability?
What are things usually tested?
The common subjects are calls-to-action, blog headlines, images and content length. You can also perform tests on emails, social media elements and paid search ads.
Is it okay to use multiple variables?
Your goal is to determine which variable made a significant effect, and if you test several variables at once, it would be hard to pinpoint which one is making the impact. If you want a more conclusive result, test one variable at a time.
How can I trust the results?
Sometimes the outcome may be too surprising or too uninteresting, and the only way for you to establish reliability and credibility is to run the same tests again. The more the results are replicated, the stronger the evidence becomes.
Does it affect SEO?
In running A/B tests, marketers would sometimes need to post duplicate content with slight variations to compare the effectiveness of whatever it is being tested. Thus, there is a fear that Google may not see this as helpful to one’s SEO efforts. The truth is that Google itself recommends A/B testing to improve site functionality.