Wall Street guru and statesman Bernard Baruch had a simple mantra to get ahead. “Most of the successful people I’ve known,” he said “are the ones who do more listening than talking.”
The same holds good with running a successful OTT brand. A huge trove of great content and effective advertising are just the beginning. But, what really makes some OTT platforms click way better than others is their ability to capture viewer feedback and act upon it. In an industry where churn rates were at 45% in Q3 2021, it’s the key to retaining customers.
But predicting what viewers prefer is challenging since pandemic-induced changes have triggered massive shifts in users’ emotions, psychology, and behavior. Many of these are difficult to fathom. Or are they?
With so much OTT content available, it may take a viewer a lifetime just to consume all that a single platform offers. This is why successful OTT players need to be acutely mindful of users’ choice of content. The whys and whens of their choices, if accepted, studied, and acted upon, form the bedrock of successful customer engagement strategies.
Conversely, without a personalized approach and sharply focused recommendations, even great content platforms can fall by the wayside. Netflix, for example, garners as much as 80% of its watch time from personalized recommendations. If acting on user preferences is so crucial for an established industry giant, you can only gauge its importance for challenger OTT brands to succeed. Viewers who experience AI-based recommendations have been shown to consume three times more content per viewing session.
Beyond addressing the growth and customer retention needs of OTT platforms and the viewing needs of users, user preferences help creators too. With user preference insights, content creators can gauge which genres, storylines, star casts, and other parameters are working for them. This helps them up their content game while shaping result-driven content partnership strategies for OTT platforms.
Content personalization strikes a chord with viewers, as it seems like the platform truly cares for their likes and dislikes. Offering a personalized piece of content increases the positive perception towards the platform, making viewers strikingly more loyal towards it. In addition, it helps the OTT marketers in evaluating each content, simultaneously and accurately gauging the change in consumption patterns over time.
The challenge here is not gathering user preferences but having a strategy to utilize them. In most cases, viewership data exists in the OTT platform’s vast data lakes. But using this data to provide a meaningful and enjoyable OTT user experience is as much an art as a science. It involves complex type of analysis and predictive analytics to drive the best value for the end user. By crunching viewership data available to them, OTT service providers can mine insights, notice trends, and build viewer affinity.
OTT platforms are constantly innovating to use recommendations better – Netflix’s Surprise Me function is one such example. But, at a fundamental level, pooling and analyzing data remains at the core of content personalization.
Your data and AI algorithms should be able to access and crunch data about your users’ behavior, such as – preferred genres, actors, teams, or sportspeople. It should be able to accept both explicit – likes, shares, watch duration, and ratings – and implicit data points. These could be demographics, weather, local and global events, connectivity, and time of viewing. Finally, your AI algorithms should then be able to automate to serve appropriate content based on these data points.
In analyzing these data points, AI and machine learning play a vital role. These technologies intuitively recognize patterns in viewer behavior, which can be scaled to predict how other viewers with similar attributes or demographics consume content.
ViewLift has spent a decade scripting success stories for a diverse range of OTT platforms of all flavors and sizes. Our prime focus area is to provide the engineering and architecture that helps our customers to deliver delightful experiences that engage and retain their viewers.
Content personalization, therefore, is one of the core features of what we do. In addition to solutions, architects and engineers, we assist OTT platforms with workstreams like analyzing user preferences. Our state-of-the-art analytics infrastructure offers them a 360-degree view of both real-time and historical data on user preferences and much more.
In addition to it, our consultancy experience allows us to customize solutions based on the platform’s unique needs and challenges. So, our customers always stay ahead in this OTT era, whether it’s about Home Page recommendations, personal playlists, e-mails, notifications, genre-based recommendations, or a plethora of emerging technologies and innovations.
Chorki, a Bangladeshi regional OTT content pioneer, approached us to help up its recommendations game. Using a combination of analytics and processes, we accurately captured user preferences, likes, and dislikes on each content piece. We then used this collective data to help Chorki figure out its top-performing movies and shows. Based on these insights, Chorki was able to offer highly personalized content to viewers right on their site’s home page.
The approach of accepting user preferences has reduced Chorki’s churn rate by a significant margin. It has also enabled them to modify their content creation and distribution strategy to mirror user demands, leading to it enjoying a significant CAGR.
Analytics and data are at the core of everything we do at ViewLift. In a cluttered OTT market, helping platform owners ride on data to shape their growth strategies and content partnerships, retain customers, and challenge industry giants is what we do best.
If you want to kickstart your content personalization journey by leveraging your viewers’ preferences, likes, and dislikes, we’re here to partner with you in this process.