According to Statista, 80% industry professionals stated that they were currently using or planning to use AI for personalising content, offers and customer experiences.

Artificial intelligence uses data to customise companies’ website content to match their customers’ preferences, customise price offerings and connect interactions across all channels and devices in a personalised way. AI learns from customer interactions to improve the accuracy of customer predictions, thus increasing the value from the company to the customers over the customer relationship lifecycle. Following on to this, machine learning algorithms have arisen as a favoured method for creating applications that understand customer preferences. These can be based on customer reviews, previous product purchases and product usage. Recommendation engines are a prevalent application of ML, where customers can be matched with offerings that they previously liked or may be interested in.

An interesting example of how AI/ML is used in marketing personalisation is the way Netflix uses their personalised recommendation system. Much of their system is powered by machine learning algorithms. For example, the artwork displayed for each title is personalised to the user. The idea is to find the best artwork for each member and make it relevant to them. Someone interested in romantic movies may be interested in the movie “Good Will Hunting” if the artwork shows romance movies containing Matt Damon and Minnie Driver. In contrast, a customer who prefers comedies may be compelled to watch the movie if the artwork shown contains the comedian, Robin Williams. Dependent on what customers prefer, different artwork will be shown.

Techniques such as the Netflix example above are increasingly being used to acquire and retain customers. Furthermore, studies have shown that 63% of customers expect some sort of personalised marketing from their preferred brands.