Media and Entertainment is one of the early industries to be hit by digital disruption. There has been a massive transformation in content consumption and viewing patterns with the arrival of smartphones, Smart TVs, and live streaming services. Amidst such disruption, media and entertainment companies need to step up their game or risk losing the audience.
As per a report by PwC, digital revenues account for larger share in E&M market with each passing year.
Today good content is just not enough. The audience is demanding better experience along with it. Your audience now want to watch the content anytime, anywhere and any device – and they want it personalized to their needs. The demand for personalization is surging across many industries. Customers want more control over what they buy or consume. And, media companies need to cater to the audience demands.
Personalized content is one of the success secrets of Netflix. The platform allows each member to search and watch content as per their interests. As per the company, “Each experience is personalized across many dimensions: the suggested videos and their ranking, the way videos are organized into rows and pages, and even the artwork displayed.” Today Facebook, Spotify and most of the media channels use personalization to enhance audience experience.
Personalization in Media & Entertainment: Creating A Deeply Personalized Experience
Personalized Content Recommendation
Massive volumes of new content are being created every week. There’s clearly a content overload. Users would need more than a lifetime to consume this content. In this overwhelming digital space, your audience need a trusted filter that can guide them to content of their interests.
Machine Learning and behavioral analytics can help you create advanced search and recommendation engines that can help your audience in discovering the content of his choice. Personalized content recommendation engines not only help your audience but also drive content consumption in your platform as users get hooked to a continuous supply of interesting content.
Streaming services like Netflix and Amazon Prime have achieved good success with the subscription-based ads-free revenue model. But that’s hard to replicate across the industry. Other players like digital magazines, newspapers etc., didn’t really had much of a success with subscription-based monetization model. For them, advertising remains an effective monetization strategy.
However, traditional advertising is becoming less effective at engaging consumers and creating bad user experiences. For companies relying on ads for revenue, personalized advertising is an effective way. They need to leverage data technologies like AI, Machine Learning etc., to identify their user’s interest based on past buying/search history and demographic data to deliver ads that would interest and engage the audience.
Experience is the key to success in media. X-ray in Amazon’s Prime Video is one good example of accentuating the viewer’s experience with information on what they’re watching. The feature provides users with bios, filmographies, facts, trivia, and more on the screen without the need to press pause.
Similarly, voice search, day/night mode, live voting, live sharing on social media etc., can help you create personalized experiences that the users so desires. Also, it is important to keep the experience consistent across all devices-whether big or small. Remember, people are viewing a lot of content on their laptops and mobiles as they commute to work or travel.
Media and entertainment space are getting increasingly competitive as the democratization of technology has made each one of us a publisher and content creator. Established media companies need to respond to this challenge by putting their audience or users at the center of their business strategy. This calls for getting a 360-degree view of their audience and building 1:1 relationship with them. And then catering to them with personalized experiences.
At, Gemini Consulting & Services, we can help you leverage new data technologies like AI, Machine Learning and Sentimental Analytics etc., to create personalized experiences for your audience.