What Makes The Move To Multi-variate Testing Worth It!

Imagine testing every business idea in a single session, instead of multiple sitting. Multivariate Testing outperforms the A/B (bucket) technique, which allows CRO (Conversion Rate Optimization) professionals to analyze and evaluate limited ideas. What makes multivariate testing a better optimization model to traditional methods is that it evolves with changing dynamics. In comparison, traditional A/B testing would require multiple sequential A/B split tests as elements change to determine the right combination. With Multi-variate Testing, faster evaluation is achieved because one can input variable combinations for a more defined hypothesis.

Although AI (Artificial Intelligence) technology combined with Multivariate Testing promises greater CRO results, proper execution is key. The popularity of multivariate testing as the perfect CRO solution for today’s ever-growing e-commerce network is its speed. It turns out way cheaper than split testing, which only measures the influence of a single marketing idea per evaluation. In just one sitting, online marketers can evaluate potential designs and how it impacts different elements.

It even gets easier with AI technology which intelligently exploits genetic algorithms as a means to identify profitable ideas. Ultimately, this shapes how e-commerce is adapted to improve CRO and increase profitability. This personalized approach aims to convert casual browsers by creating a relatable e-commerce platform that will optimize sales conversion. A lot goes into designing consumer experience that can positively sway a purchase decision. In fact, it requires having the right data to input, and analyze to determine how well the combination really works.

Multi-variate Testing requires a considerable portion of traffic as does the traditional A/B solution. What sets the two apart is how traffic is distributed to perform an analysis. For example, A/B split tests divide traffic into two even portions. Whereas Multivariate Testing prefers smaller segments. A given is that e-commerce receiving low traffic volume opt to do A/B split tests. Medium to large scale companies found Multivariate Testing more beneficial given the multifactorial nature of the business.

How well AI-powered Multivariate Testing will work for e-commerce relies heavily on measurable elements. Nonetheless, it’s a powerful e-commerce optimization tool to exploit and learn the complex behavior of an evolving audience. With online marketers gaining relevant insights into consumer behavior, e-commerce personalization will eventually become less of a challenge. Furthermore, it’s the right approach to eliminate any doubt of CRO success because AI-powered multivariate testing allows room for greater accuracy. The conversion gains will be significantly higher because faster testing makes it easier; to conduct trials concurrently while improving insights and implementing winning designs.

Read: http://digitalmode.net/2017/07/21/tech-evolution-using-smarter-ai-tools-maximize-conversion-rate-optimization/

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