In our last post, “Evolutionary Design Beats Revolutionary Design (Part-1)”, we discussed about why redesigning should be evolutionary and not revolutionary. We discussed the prime reasons that are responsible for failure of revolutionary design. In the second part of this guide, we will be focusing upon the benefits and challenges that you are going to come across when implementing Evolutionary Design.
Benefits of Evolutionary Redesign
When you rely upon evolutionary design, you are basically taking a step to develop an edge over others. You can create something simplistic yet innovative while blending both design and analytical analysis. The primary benefits of Evolutionary Redesign are as follows.
Lowers the risk by altering only elements that would improve results: Sometimes the changes over the platform are so drastic that it gets difficult for the loyal customers to find the products they want to. The fact that they feel estranged by the unfamiliarity offered by the sites makes them leave the website. This is when ER approach comes in to picture and implements changes only over those elements that need improvement.
Rather than aesthetics, ER data focuses upon analytics: When initiating the redesigning process, the first thing that most of the designers do is to ask for suggestions. Luckily, you are going to come across several suggestions. Since, every individual has varied opinions, there is possibility for you to get skeptical about which changes you should probably implement. This is when you can take in to consideration some factors that help in sorting the best options. With analytical data, you can make sure that you focus only upon those elements that require change and others that do not. It is not about how stunning your design looks. What matters is that your websites should redesigned while taking in to consideration in-depth analysis of data, which sis going to lead to lead to a lift in performance.
Freedom to roll out new features: With ER design, you get the freedom to make global product updates at the earliest without making you invest much time in planning, designing and developing. When you have a sequence of updates to be rolled out, ER design lets you make the small updates and also test them at the earliest. This suggests that your product will experience stable improvement, which is something that could not be expected in case of revolutionary model.
ER design is based upon A/B Testing results: ER allows you to consider A/B testing component while considering the redesigning element. You get the additional benefit of testing the website as per user behavior and choices. This helps in making the redesigning decisions easy. The best part about A/B testing is that it lets you come across a conclusion that manages to offer improved results. So, you can expect to deduce some dramatic changes in the conversions and revenue through A/B testing.
ER Designing Considers user feedback: There are several consultants who make designs based upon their personal choices and convenience. Rather than considering personal convenience, you should be focusing upon what the end user expects from your design. Designing for the people who are using your website would help in improving the conversions. All that you need to do is to make sure that you are letting the user benefit from your product line while serving them in a better way.
Challenges of Evolutionary Redesign
Patience is the key in case of ER: With the constant changes evolving in digital industry, it gets important for you to constantly upgrade the product line. When planning to opt for a major visual overhaul, most of the designers rely upon delivering something that manages to stun the customers and leaves an impression that you are in touch with the recent updates. It is more about art but in case of evolutionary design it is more about functionality.
Dedication towards analytics and testing
As a digital site owner, you will have to focus upon evaluating what the analytics suggest. ER designing involves changes that are slow and methodical, which make take a quite a few years to get implemented. You can perform A/B testing while upgrading feature-by-feature but this is not an easy task. There are chances for these changes to get executed in a considerably long time.