Personalizing Media and Entertainment content: Personalized notifications, real-time personalization, collaborative and content-based filtering
By: Jala Sanar
Tags: Media And Entertainment, Personalization, Content, Machine Learning, Digital Transformation

Personalizing Media and Entertainment content: Personalized notifications, real-time personalization, collaborative and content-based filtering

Picture source: Pexels.com

Audiences love content personalized to their preferences, likes, and dislikes. To this end of delivering a relevant and memorable customer experience, the huge amount of media and audience data (which many media companies struggle with) is a boon. More the data, better the personalization, and better the audience retention and expansion.

To explore the various approaches and techniques for personalization, we invited Manish Mudgal, Head of Media & Entertainment, for UK and EMEA, MediaAgility to our Media and Entertainment special edition mini-webinar series. He works with media publishers to help them create future-proof digital strategies and apply cutting-edge technology solutions to acquire loyal customers, increase traffic and revenue, and handle their big data. In the webinar, he covers techniques like personalized notifications, personalized content, contextualisation, collaborative filtering, and content-based filtering.

Personalized notifications to garner real-time audience attention

Manish Mudgal (MM): Notifications are the medium through which we try to reach the customer in real-time. For example, if a content piece is showing a sudden spike in traffic and we know that the audience would be interested in that content, we would like to let them know in real-time. Here we will rely on different types of notifications, like — in-app notification on mobile devices, a pop up on webpage, an email, a dynamic list, a browser notification.

Based on the technology platform and the users’ presence, today, we can very well determine where our audience is online and which type of real-time communication do we want them to experience.

Personalized content with Real-Time Personalization technique

MM: When we talk about personalized content, we are talking about dynamic web pages, dynamic advertisement, dynamic promotion of the products, dynamic email subscriptions, and so on. To present the content in a more personalized manner on a webpage we actually recommend three types of approaches — real-time personalization, collaborative filtering, and context-based filtering.

In real-time personalization, we don’t have a history of the user or the visitor. We know a little about them but want to make sense out of whatever information is available. So we see what type of information is available to us when the user lands on a website afresh. We get the data points like users’ IP address which leads us to their location. We know the device, browser, screen size, operating system. If there is an umbrella of the websites which a publisher possesses, we can know much more about the users from the data available about the other websites they previously visited.

This type of recommendation is based on a calculated assumption backed by the data from the recent past (of other first-timers). We know what a mobile user is most likely to show interest in or which content piece will be more appreciated more by a laptop user. Similarly we can define interest groups for new users in terms of iPhone and Android, or by location. This case adds more value where we want to welcome users in a more personalized manner than being a website that is the same for everyone.