With consumer and behaviour market changing rapidly, it has become more crucial than ever for businesses to invest in more data-driven technologies. Presently, artificial intelligence, web design and data science are three spheres that are collectively influencing the internet realm. Every day, technologies like artificial intelligence, big data, etc. are setting a new benchmark, driving businesses to offer better AI-based solutions. However, before further elaborating on how these technologies help businesses, let’s understand these three important domains in brief :-
Web designing can be understood in two segments; designing and development. A web designer is a professional who designs the website by specifying the layout, typesetting, colour, theme, etc. A web developer, on the other hand, is responsible for the functionality of the entire web page in order to make it responsive and interactive for the users.
First coined in the year 1959 by Arthur Samuel, machine learning is a field that allows the computers to learn without explicit programming instructions. Machine learning along with other spheres of Artificial Intelligence has presently become the biggest trend in computer research fields and big corporations like IBM, Google, Facebook, etc.
Data Science, also known as pseudoscience is a research field that makes sense out of the large data mainly concerned with optimization that is available for different purposes. It employs numerous tools to accomplish the objective and requires extensive knowledge of various fields primarily Python, Computer Science, Statistics, etc.
[Pull Stat]- “In the year 2017, 51% companies implemented or expanded their use of Artificial Intelligence.”
How Data Science and Machine Learning Augment Web Designing?
1. Personalized and Valuable Content
Just like us humans, machine learning technology also looks into a behavioural pattern of user data to predict their reactions on a particular event or change. Further, with the help of data mining, statistical analysis, data science tool, etc. machine learning is integrated into a system to customize the content that is based on pattern recognition.
It works similar to how relevant ads pop on the side of the screen while browsing the internet or how Youtube recommends us videos based on our previous searches. This allows the content of the page to customize automatically or let the developers understand user preferences based on the data location from where the page has been accessed.
[Pull Stat]- “79% of the companies have documented personalization strategies to offer customized content to their target audience.”
2. Expanding the Role of Developers
Incorporating data science and machine learning into the web designing process allows the developers to focus more on bringing innovative designs and development. Additionally, they are also provided with more opportunities to take up strategic roles while tweaking certain aspects of the page to optimize the overall performance.
3. Identifying and Understanding Browsing Behaviour of the Users
Recognizing users browsing behaviour including content nature, the page they are redirected to, average time spent on a page, etc. are some of the vital factors that can help in optimizing a website. For instance, if users are redirected from an exceptionally working web page to an average website, it is natural that they wouldn’t spend much time on the latter website. This behavioural observation would allow the developers to list down the relevant reasons and provide useful insights to improve the website’s performance.
4. Effective Filtering of Relevant Data
Machine learning is capable of collecting unlimited data along with regular analysis and assessment. Once the data is collected from multiple sources, it filters out the relevant variables in order to prevent complicated integrations, offering short and precise data feeds. This allows the company to customize the experience based on the recent behaviour and interaction of the consumer.
5. Safeguard from Emerging Security Threats
In recent times, multiple companies employed machine learning technologies including logistic regression to identify malicious websites. Similarly some companies use classification algorithm to identify and predict these websites based on primary criterions such as security features, domain identity, and data encryption techniques, etc. This has allowed the businesses to effectively protect web application from the growing security threats.
Many leading companies across the world are continuously embracing machine learning and data science tools. Their imperative role in the web designing allows optimization and offer window of opportunities for more innovation at the ground level. With the kind speed technology is advancing and overtaking business world, it would be prolific for the companies to adapt to the new changes in order to thrive in the competitive market.