Reevaluating A/B Testing as a Strategy
In 2020, marketers have A/B testing down to a perfect science. Any time a new marketing channel happens to present untapped opportunities without a road map to drive results, A/B testing comes along to help marketers discover a path forward, and optimize their marketing efforts. In this article, we are discussing reevaluating A/B testing as a strategy.
It is no doubt that A/B testing is a tried-and-true approach for digital marketers all around the world. However, the marketing landscape has been changing a lot lately. It has been opening up more paths than ever before. Moreover, today many brands are taking the multichannel approach by leveraging storytelling, incorporating user-generated content into their strategies, and using cutting-edge technology like VR and AR to enrich the larger customer experience. Now, the problem that emerges here is that you can’t find enough time to judge each of these items on an individual basis by A/B testing them.
Efficient Option
The problem isn’t that A/B testing no longer happens to get results. It is simply the fact that it is no longer the most efficient option for evaluating current marketing performance. According to a survey conducted by eMarketer, most marketers reported that close to 80% of A/B tests do not produce any significant results. As of right now, A/B testing stands out for its extreme lack of efficiency in an industry where everyone seems to be obsessed with optimizing, fine-tuning, and improving every aspect of their marketing funnel. In the progressive environment of the year 2020, the development of enhanced approaches to the same marketing problems. It has thrown into relief the shortcomings of A/B testing by offering numerous upgrades to this time-honored testing strategy.
Now, the question arrives: Should you, as a progressive marketer, give up on A/B testing today? No, definitely not. Despite its many limitations, for some organizations, it still happens to be the best way to optimize and refine a campaign strategy over time. What you as a marketer is better off doing is trying to understand what technology-driven improvements can help you make this process faster. Mostly, you must try to look into the use cases of automation and artificial intelligence on making your content marketing decisions more impactful and productive.
Automation: The Future of Efficient A/B Testing
A/B testing marketing campaigns has always been a reliable but slow process. To track results, marketers need to test one variable at a given time. Problems start to crop up when marketers wish to test a lot of different variables together. Manual A/B testing doesn’t allow a marketer to try multiple combinations of different variables at the same time. Now, this is exactly where automation can step in to solve the problem. Today, there are multiple tools available for A/B testing which rely on AI-driven and machine learning technology to make the process faster and more effective as well. Thus, it is safe to assume that automation is definitely the future of the A/B testing going forward.
Conclusion
This brings us to the end of our discussion on reevaluating A/B testing as a strategy. Now, let us know some of your thoughts and opinions on the same.
