Website Personalization with Drupal CMS and Machine Learning
Your website is the main digital platform over which you interact with your visitors and potential customers. While at one point of web evolution you could only create a one-size-fits-all website to address all your target audience, today that is not the case. You can now customize the page your visitor sees based on the visitor’s interests and browsing behavior commonly referred to under the broad umbrella of web personalization.
What is Website Personalization?
Website personalization is the process of creating unique visitor experiences on the web, based on the visitor's previous behavior on the website, their demographics, and their interests.
Benefits of website personalization include increased time on site, better CTAs and optimized landing pages, a better understanding of customers and customer loyalty, relevant product recommendations based on user behavior, and increased conversion rates and revenues. Visitors enjoy getting that personalized subtle touches (like recommendations and targeted content) especially if it done in such a way without asking intruding questions and encroaching into their private space.
According to a study by Statista1, 90% find marketing personalization appealing and according to Epsilon research2 80% of customers are more likely to make a purchase when brands offer personalized experiences.
Analytics Insight states3,
“Machine learning-based personalization has gained traction over the years due to volume in the amount of data across sources and the velocity at which consumers and organizations generate new data. Traditional ways of personalization focused on deriving business rules using techniques like segmentation, which often did not address a customer uniquely. Recent progress in specialized hardware (read GPUs and cloud computing) and a burgeoning ML and DL toolkits enable one-to-one customer personalization which scales.”
What is Machine Learning?
Machine Learning is a type of artificial intelligence that predicts outcomes based on data gathered. The most important aspect of machine learning is that it teaches itself progressively, learning from the data it is given. Historical data is used to build a model set and using that model, new outcomes can be predicted. Algorithms are trained to make predictions based on this, uncovering key insights from within this data mining process. These insights in turn help in the key decision making processes within applications and businesses, which should favourably improve business growth.
Advantages of Integrating Machine Learning with Drupal
Companies collate data about their customers, products, and services through social media, emails, and other communications. By integrating machine learning, Drupal sites can tailor content based on predictions from the previous browsing history. The person does not have to necessarily be logged in. Instead, they are assigned unique User IDs and their browsing behavior or patterns such as clicks, searches, and commonly accessed pages can be mapped to provide personalized web experiences. This leads to personalization opportunities, some of which are
- Understand overall user sentiment around a given topic and context
- Provide recommendations based on a user’s recent interactions with the site
- Perform Lead Scoring (ranking based on the prospect of engagement in the current session)
- Suggest other related products a user might be interested in purchasing based on past trends
Drupal allows for easy integration of these future promising features through modules. The benefits of using machine learning for personalization will definitely give Drupal websites an added boost for traffic and conversion!