5 Reasons Why Your Content Platform Needs A Good Recommendation System

Recommendation system is the tool that'll help you find the needle in the haystack. .

4 min. read

Content platforms, regardless of whether they offer books, movies, or podcasts, face a common challenge: intense competition necessitates innovative strategies to distinguish themselves. In today’s market, where numerous players emerge, merely possessing a high-quality catalog is insufficient for retaining subscribed users. As expectations regarding user experience continue to rise, the presence of a robust recommendation system undoubtedly becomes crucial for the long-term viability of a platform. 

Not convinced yet? Here are 5 reasons why your content platform needs a good recommendation system:

1 – Because you have a lot of content.

Are you acquainted with the notion of hyperchoice? If not, allow us to elucidate:

Offering a diverse range of content on your platform is undoubtedly advantageous. It grants your users numerous options. However, excessive choice can sometimes become overwhelming, and spending an excessive amount of time selecting a movie or TV show can be frustrating. A proficient recommendation system, coupled with effective editorialization, can assist users in navigating your content, aiding them in making informed choices.

2. Because you want to offer a personalized experience… 

Personalization is a fundamental aspect of recommendations. By considering users’ preferences, dislikes, viewing history, and purchases, an effective recommendation system can suggest content tailored to their tastes. We all recognize the sheer joy of discovering something that immediately resonates with us while browsing through an extensive content catalog. In fact, stumbling upon the perfect match can be just as exhilarating as stumbling upon a hundred-dollar bill… okay, let’s be honest, I’d gladly take the bill too.

3. … without locking your users in a bubble.

Certain recommendation systems, like that of YouTube, have gained notoriety for presenting users with extremely sensational or conspiracy-oriented content. This is primarily because the algorithm’s objective is to entice users to click on another video once they have finished watching the previous one. According to Guillaume Chaslot, former YouTube engineer, “Hatred is useful for clickbait […] the algorithm tends to lock users in a bubble and offer them more and more extreme videos”. 

Nonetheless, users should retain authority over the recommendations they receive. They possess the right to comprehend the rationale behind the suggested content and decide whether it aligns with their preferences. Consequently, they should be empowered to request the exclusion of certain recommendations or reset their recommendation settings altogether.

Rumo adopts a semantic approach by correlating keywords with users’ preferences to curate optimal recommendations. Our objective is to assist users in discovering those extraordinary gems that they never anticipated would be presented to them so effortlessly. It’s akin to unveiling an unexpected treasure on a silver platter.

4. Because you want to keep a high user retention rate.

When your users are content with the provided content and its delivery, they have no incentive to seek alternative recommendation methods. As long as you consistently update your catalog, our recommendation system can establish connections between each movie, enabling the creation of playlists or new categories. By providing the algorithm with additional keywords and movie information, it enhances its precision in fulfilling its task, resulting in even more refined recommendations.

5. And because you want to maximise the efficiency of your editorial team.

Rumo does not aim to replace your editorial team; rather, it serves as a tool designed to assist them—a human-centered recommendation system. Your editorial team supplies the content and keywords, and Rumo optimizes their potential. It provides a preview of the recommendations users will receive, along with the flexibility to modify or add parameters and incorporate user activity data. By utilizing Rumo, your editorial team elevates the quality of recommendations, harnessing the full potential of its capabilities

If you’re still not convinced after this article, we invite you to try our free demo of Rumo. May the recommendation be with you!

*Learn more here on the issue of ethical recommendation algorithms on our blog