There's been a sharp rise in OTT and streaming consumption among consumers, owing to the global pandemic - be it for entertainment purposes or otherwise. In fact, according to a report by the Boston Consulting Group (BCG), the Covid-19 pandemic boosted the growth of over-the-top (OTT) subscriptions by a staggering 60%.
Needless to say, with OTT services gaining traction, online streaming giants need to improve their quality of content and look for ways to personalize as well as optimize video recommendations for consumers across the board.
In this blog, we will look at the top 3 ways in which you can provide personalized recommendations to users and make the most out of your OTT platform.
Top 3 Strategies to Deliver Personalized Video Recommendations
Here are the top tried and tested strategies to personalize your video recommendations with a media recommendation engine:
1. Home Page Recommendations for the Win
Thanks to streaming giants such as Netflix, the benchmark for judging an OTT platform's capabilities is high. For instance, if you are not offering personalized content and a customized browsing experience from start to finish, you're already behind the competition. Today, an overwhelming 92% of marketers admit to using personalization techniques in their marketing.
One way to create a positive impression in the subscriber's mind is by personalizing the home page based on the user's likes, preferences, needs, and past viewing history as Netflix does via its "Because you watched [X]" section:
Remember that you can create your own categories such as "Recommended For You," "Trending," "Continue Watching," etc. based on how users are interacting with your platform.
The learning: Netflix makes use of ranking algorithms to personalize video content for the user. Plus, the brand pays special attention to how customers navigate the page and understand which sections the customer is most likely to pay attention to, among others. For instance, the brand places the most relevant videos in the upper-left corner as this is the most viewed section on the home page. Home page recommendations can create a powerful image in the user's mind and build a positive first impression that's bound to last.
2. Similar Movies/Shows Category
If you give your customers too many options to choose from, they're going to suffer from choice paralysis. This is where online streaming brands and OTT players can reduce customer effort and boost user satisfaction by showcasing a "Similar movies/shows" section.
Take the example of Amazon Prime Video, which highlights a "Movies we think you'll like" section:
The learning: This kind of personalized recommendation - based on the user's viewing patterns--can effectively engage your audience and increase user retention. In the end, customers want a seamless, accurate, and effortless browsing experience so optimizing your video recommendations can pay off huge dividends.
3. "Customers who watched this, also watched" Section
Another time-tested video content strategy that works wonders is the "Customers who watched this, also watched" recommendation. By studying how customers are using your platform and analyzing their choices, you can literally predict your customer's next exact move and showcase highly relevant content to skyrocket your user engagement rates. This strategy allows you to segment customers based on real-time data and drive customized video recommendations. this type of recommendations can easily grow retention.
In fact, as per data, Netflix has over 1000 recommendation clusters based on user preferences. Furthermore, the brand produces approximately US$ 1 billion a year from customer retention through its personalized recommendations.
While creating segments, make sure to ask yourself the following questions:
- Is your target audience active on streaming platforms and which segment has the most revenue potential?
- How can you drive footfall to your platform using personalization?
- What kind of content are your customers liking/disliking and why?
You can also leverage special customization features that are available within the Argoid platform - from personalized banners and ribbons to ordering of pages/tabs--to elevate the customer's browsing experience.
The learning: Personalization is not just about reaching out to a single customer; it is also about creating a sense of community within your target group. By using categories such as the one mentioned above, customers can feel a greater sense of belonging to the overall community as they connect with each other over shared viewing interests and end-goals.
Hyper-personalization is the name of the (OTT) game today. Customers want super relevant and context-aware video recommendations from brands. If you need a platform that can empower you to deliver a hyper-personalized OTT consumer browsing experience, look no further than Argoid.
Argoid’s AI-driven media recommendation engine allows you to provide hyper-personalized recommendations to each user across touchpoints and in real-time. More importantly, the adaptive engine intelligently showcases the most relevant videos to users, based on their current interaction with the platform.
This, in turn, can boost user happiness, improve conversion rates, and build trust as well as confidence as customers start finding real value with every browsing session.
What are video recommendations?
Video recommendations are about using an OTT recommendation engine that tracks your audiences and their behavior to predict the movies and shows they will like. Popular OTT platforms like Netflix have been using this strategy for a long time to maintain a low customer churn rate.
Why should OTT players offer video recommendations?
OTT players are not always aware of the preferences of viewers. As a result, viewers experience choice paralysis, and they may even stop using your OTT platform simply because they are not getting suitable video recommendations. Thus, enabling a media recommendation engine becomes a significant part of the user experience on OTT platforms.
How can personalization improve OTT video recommendations?
Generic or rule-based recommendations have limited value; the full potential is only realized with AI-based personalization. With a video recommendation engine, OTT players can provide customers with quick results based on their preferences and reduce their search efforts. As a result, churn rate declines and you build a viewer base of repeat customers.