Role of recommendation engine in personalizing the streaming experience

Today, viewers have complete freedom to watch the latest movies and listen to their favorite music on preferred devices – Smartphones, Computers, Tablets, or Connected TVs, every time and everywhere.

But back in 2005, when the premium movies & TV content were made available online for the first time, no one ever imagined that streaming services would offer this flexibility and grow this faster.

Well, all the credit goes to the leading OTT players – Netflix, Hulu, Amazon Prime, Spotify, etc.

With personalized and seamless streaming experience, these brands have completely revolutionized the way audiences access to video/audio content.

“They believe success in OTT realm is all about how you engage your users. There is no shortcut, but you have to personalize your programming, advertising, and even delivery, as per the habits and preferences of each individual user.” 

You too agree with the fact, right?

Even the thought leaders in the industry believe in the power of truly personalized experience in building a successful streaming service.

Hence, here we are going to shed focus on the need for personalization in the OTT industry and will let you understand the role of recommendation engine in personalizing the streaming experience.

Why personalization is important in streaming?

Personalization triggers streamer’s satisfaction.

Apart from excellent content, strong discovery tools, and a straightforward interface, the success of a streaming channel also depends on subscriber’s satisfaction percentage.

If you are offering a streaming experience that is uniquely tailored for each user and ensures the highest quality delivery of both content and advertising that is relevant to the user’s viewing preferences and interest, then no doubt, your subscribers are satisfied and you are doing a great job.

But in case, the satisfaction of your consumers is not upto the mark and the churn rate is rising month-over-month, you must work on tailoring your streaming experience immediately.

In OTT space, personalization mainly refers to a 1 to 1 experience, where all the offerings are tailored as per the user’s behavior and interactions. By delivering a personalized experience, you can make each user feel that the streaming service is exclusively designed for them and thus improve organic engagements.

Thanks to advanced technologies like AI-based recommendation engine, delivering personalized streaming experience is now simple and automated. No matter, whether the personalization process involves video streaming or audio streaming, a smart recommendation engine can do wonders, you have ever thought of.

How a recommendation engine helps in personalizing OTT delivery?

A recommendation engine is a software or program that works on data inputs and delivers accurate or relevant recommendations in the real-time environment. It simply analyzes the viewer’s content preferences, the time & device they stream on, various details from billing and account management, and accordingly configure a personalized streaming experience on an individual level.

From the beginning when a user opens the streaming interface, browses the content library, streams video/audio content, to closing the OTT application, the entire session life-cycle is being tracked down and taken into consideration. Such insights give a complete understanding of why, what, where, when, and how the viewers are streaming their desired content and leverage necessary actionable information for a seamless OTT experience.

Combined with all these real-time data, the AI-driven recommendation engine initiates a 1-1 session management approach with each & every user, and ensures a high degree of personalization, which is the true key to audience engagement.

Practical advantages of using a recommendation engine

• Faster & efficient content discovery –

Digital audiences don’t have much patience to browse the entire content library. They always want the streaming services to recommend interesting titles on the home screen, as quickly as possible.

According to a survey report, a viewer takes around 90 seconds to decide which content to stream on. If in between, the user doesn’t find anything good & interesting, then there are higher chances, a churn will occur.

With insights from user’s streaming history and viewing preferences, the recommendation engine offers a bunch of relevant content instantly and improves the appeal of content discovery and makes the selection process faster & efficient.

• Binge-streaming functionality –

Just reducing the time spent in browsing content, won’t help. 

To earn a satisfactory revenue, you have to let your users stay for longer and spend more time on streaming content.

On average, a user retains 8-10 hours of streaming in a single week, out of which most of the sessions happen around the weekends. This means streamers are more active on weekends than on weekdays.

Now, with the help of a time-based recommendation engine, you can suggest your best binge-worthy streaming content during the weekends, and allow your users to engage deeply. No doubt, the subscribers will be more loyal and will return more frequently through meaningful recommendations for additional viewing sessions.

• Valuable advertising

It’s true, advertisement-based monetization model ensures a profitable ROI in streaming business. But this doesn’t mean you can just stitch any advertisement from any genre into the streams and affect the user experience.

Just like content, advertisements are also important in terms of user engagement. 

If the advertisements are completely irrelevant, users will simply feel irritated and may decide to switch the platform.

To avoid such consequences and to showcase valuable advertising as per user’s viewing preferences and interests, you need to set up a smart Ad decisioning system using recommendation engine.

Yes, you read it right!

A recommendation engine can incorporate ads into the streaming manifest, addressing the known interest of each individual user. This will make the ad spots valuable and draw more attention of the users towards the screen.

Giving every user a personalized streaming experience

Considering everything that we have discussed till now, hope you are clearer about the role of recommendation engine in delivering a tailored streaming experience to users.

Now if you don’t feel like integrating a recommendation engine into your streaming framework, then you are not serious about growing your business.

Take a free trial of our recommendation engine and see how a 1-1 relationship with users helps in delivering a personalized streaming experience to every individual with great accuracy.

Come on, it’s time to upgrade and take your streaming service to a whole new level.