From Content Discovery to Retention: How Argoid’s Personalization Solves Choice Paralysis For Streaming Platforms

From Content Discovery to Retention: How Argoid's Personalization Solves Choice Paralysis For Streaming Platforms

The plethora of streaming content makes it difficult for viewers to choose material that interests them. Personalized recommendations neatly solve this problem.

The emergence of streaming services has completely changed the entertainment landscape by giving consumers access to a huge variety of content. With so much content available, viewers may find it challenging to find and interact with material that interests them.

In fact, in a survey by PWC, 31% of respondents said that easy, personalized content recommendations would be a reason for staying with a streaming service. Even amid the generally favorable view of video entertainment, 29% of respondents said they were often “frustrated” or “overwhelmed” by the array of choices on offer.

This is where the role of personalized recommendations takes on special significance, making choices simpler, saving viewers’ time and giving them a reason to stay back. A personalization engine has now become essential for streaming platforms with a vast catalog, and who care about the customer experience.

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Argoid aims to increase viewer satisfaction & retention, smartly driving revenue for its clients. Helping viewers make a decision without overwhelming them with choice, is an deft way to achieve this ”

— Gokul Muralidharan, CEO, Argoid

Argoid’s Streaming Personalization: A Three-Pronged Approach to Driving Viewer Engagement and Retention

Argoid’s media recommendation system for streaming platforms is designed to drive viewer engagement and reduce choice paralysis by tailoring the viewing experience for each individual user. By delivering personalized content to relevant users at the right time, as well as offering AI-enabled and personalized search features, it helps to drive higher engagement and viewership.

One of Argoid’s customers, a streaming music leader, witnessed 75% users clicking on Argoid’s suggestions, within the first week of deployment, and over the month, 87.9% used Argoid’s recommendations at least once. This suggests that a significant percentage of users prefer to interact with the platform’s suggestion feature, powered by Argoid.

With this customer, Argoid recommendations account for 38% of user engagement overall, which means a sizeable portion more than one-third of all user involvement, can be attributed to it.

So how does Argoid’s personalization technology help drive viewer engagement? Here is how.

Content Discovery:

Argoid’s personalization algorithm doesn’t just suggest content based on what the user has previously watched; it also takes into account what other users with similar viewing histories or tastes have enjoyed. This helps the viewer discover popular content that they may have missed otherwise. Recommending video content from other users, in addition to considering preferences and behavior, helps the viewer build trust in the platform and continue using it.

Recommendations for Conversion:

Argoid’s personalization algorithm uses a variety of data points, such as viewing history, watchlist, plot/summary/storyline, search queries and more, to recommend content that is likely to interest the user. By providing relevant recommendations at the right time, the viewer is more likely to engage with the material and feel satisfied with the platform.

Recommendations for Retention:

Finally, Argoid’s personalization algorithm helps retain viewers by suggesting content that will keep them engaged. This includes recommending related content, suggesting new episodes or seasons of shows the user has already watched, and even suggesting content based on the time of day or day of the week. Thus, the platform is more likely to retain the user.

This three-pronged personalization approach ensures that no two viewers see the same page or the same set of recommendations, and all have the satisfaction of individual preferences being taken into account.

Ultimately, Argoid’s recommendation system helps streaming platforms achieve their goals of decreasing churn rate, increasing user engagement rate, and increasing customer satisfaction by providing users with a viewing experience that meets their specific needs and preferences. By keeping users both engaged and satisfied, Argoid helps streaming platforms stand out in a competitive market and grow their business rapidly.

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MTS Staff Writer

MarTech Series (MTS) is a business publication dedicated to helping marketers get more from marketing technology through in-depth journalism, expert author blogs and research reports.

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