A website contains a myriad of different images, facts, and hyperlinks. Each nugget of information on a website is valuable to someone or the other who would like to access it readily. Designing a rich website that can readily yield its information to different users can, therefore, be quite tricky.
One of the thorniest problems in user interface designing is the creation of a complex website. This is because different visitors have different needs. And not just that; even a single visitor may have different needs at different times. Also, a website may be designed for a particular purpose and used in unexpected ways.
This is why web servers record data about user interactions and collect this data over time. Machine learning can come into play here by examining the user access logs in order to automatically improve the site and helping create what is known as an adaptive website.
What are adaptive websites?
As opposed to the creation of a single version in other web designs, in an adaptive web design, multiple versions a web page are created to better fit the user’s device. Often while designing mobile sites, companies tend to focus on the lowest common denominators such as device, browser, screen-size, and OS.
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This implies ignoring all the exciting stuff that mobile apps provide, such as location. Therefore, if your business aims to benefit from delivering a more contextually relevant experience, then the adaptive design is your best shot at this.
In an adaptive website, several different versions are created beforehand. The server detects factors like OS and device, and the correct version of the site is sent to the user. Besides, adaptive websites are the only way to reach the broadest mobile audience.
How is an adaptive website different from a responsive one?
Simply put, in the case of a responsive site, we encounter fluidity in the sense that no matter what the target device is, a responsive website adapts to the size of the screen. The layout of a responsive site is determined on the client’s side i.e. on the user’s browser. Therefore, the same file is sent to all the users but significant parts of the file may be hidden from the user.
Adaptive websites, on the other hand, involve static layouts that are based on breakpoints, which don’t respond once they are initially loaded. The screen-size is detected and the appropriate layout for it is loaded. Machine learning helps the web server take layout decisions by detecting factors like OS and device and then send the correct version of the site, making it quicker for the viewer.
What makes machine learning and adaptive websites a powerful combination?
The following reasons make a strong case for the use of machine learning in adaptive websites.
Adaptive websites have a much better load time performance and overall user experience. It works by transferring only those assets, which are necessary for the specific device. For example, high-resolution images are transferred only when a high-density retina display is detected, and not defaulted to everyone.
Machine learning helps identify the user intent and context. Machine learning in adaptive websites, therefore, finely tunes the site to satisfy the purpose of user’s engagement with it. The big news is that you don’t need to scratch your existing website completely. Developers don’t need to re-code the existing website from scratch to transform it into an adaptive website.
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The approach followed by adaptive websites is also Google-friendly. The need to maintain two content management systems with the mobile-specific site development approach is reduced.
With machine learning in adaptive website building, any business can create a highly interactive, secure site that works for everyone who might ever visit your site with any type of mobile device, then you have to create an adaptive design.
(Disclaimer: This is a guest post submitted on Techstory by the mentioned authors. All the contents in the article have been provided to Techstory by the authors of the article. Techstory is not responsible or liable for any content in this article.)
Image Source: solutionexplorer.net
About The Author:
Naveen is currently the CEO at Allerin Tech Pvt Ltd. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. Naveen is a keynote speaker and thought leader in the area of IoT solutions, Machine learning and Block Chain Technology.
Specialties: Solution Design and consultancy , Data Science, Machine Learning, Deep Learning Enterprise Application Planning, Cost Optimization and Block Chain
