What You Put In and What You Get Out of Multivariate Testing

Multivariate testing is basically the process of making an assessment on certain web designs’ potential to deliver ideal results. This simple experiment is recommended for websites that seem to have faltered in terms of traffic and conversion.

Fledgling web developers can equally benefit from the process especially during the phase of deciding on the site’s structure and looks.

Yet not everyone can emerge victorious from multivariate testing. It entails keen planning on the elements to test along with the metric that will be utilized for the data analysis. Suffice to say, this particular experiment is one of the best embodiment of the “garbage in, garbage out” principle.

It is therefore a must to know all the factors and input needed to get a fill of the preferred outcome.

Inputs

There’s no special formula in virtually all processes. Even when multivariate testing comes with algorithm, there are certain factors that may hamper success. They create the pitfalls that you should be able to get around with.

In order for you to effectively skirt issues in the test, you should be wary of the following factors: 

Specific Goals or Site’s pressing Problem

Surely, there’s a reason behind your need to conduct multivariate testing. Your site may be losing significant traffic and you’d want to revive that. It could also be that you are observing alarming bounce rates and you have not made a single sale for quite a long time.

All these are legit reasons for testing. It’s important to have all these issues laid out, as these would dictate the right direction that you can traverse for the experiment. 

Elements Tested

Logically, it is not right to have the image and web content tested when you are aiming to raise the conversion rate of your site through multivariate testing. The number of purchases or subscription is mostly driven by banners, calls to actions, download buttons or sign up forms. It is then appropriate to use these elements for the test.

Note that the selection of components should be dependent on what you want to achieve through the experiment. 

Metrics

You wouldn’t measure distance with a weighing scale as you wouldn’t measure conversion rates with the number of hits. Multivariate testing requires you to determine the areas that you want to evaluate, along with the basis for assessment. Embracing the right metrics can lead you to a solid conclusion and correct analysis.

The Outcome

Doing all the right steps and considering primary factors of success in multivariate testing allows you to avoid being blindfolded and feeling your way around marketing. Once you get the hand of the process, you can have a closer reach on the following advantages:

• constant flow of traffic or influx of revenue 
•  greater returns of investment as produced by higher conversion rates
• more effective branding and efficient marketing
• increased number of hits and repeat customers 
•  avoidance of risks usually spawned by changes in website layout

Author's Bio:
Aadith sasi is a freelancer who promotes multivariate sites where they provide Multivariate testing resources include the Maxymiser website