Mumbai: Navigating the vast sea of entertainment options can be overwhelming, with countless choices often making it hard to find content that truly resonates. MovieMe addresses this challenge with a groundbreaking approach to content discovery.
Founded by Bhavesh Joshi, a film enthusiast with a background from the UK’s National Film and Television School, MovieMe harnesses machine learning to deliver hyper-personalised recommendations, making it easier for users to find content that truly resonates with their unique tastes. MovieMe is reshaping how we interact with cinema and television by offering features like ‘Scenes’ and ‘real-money game’.
Indiantelevision.com’s Arth Chakraborty caught up with MovieMe founder and CEO Bhavesh Joshi to delve deeper into their offerings, future trends and more.
Edited Excerpts:
On the inspiration behind MovieMe, and the ways in which it is disrupting the traditional entertainment landscape
The inspiration for MovieMe stemmed from my deep love for cinema and the realisation that, despite the abundance of content available today, many viewers still struggle to find films and shows that truly resonate with them. I wanted to bridge this gap by creating a platform that does not just recommend what’s popular, but what aligns with each user’s unique tastes and preferences. MovieMe is disrupting the traditional entertainment landscape by leveraging machine learning to offer hyper-personalised recommendations. We are moving away from a one-size-fits-all approach, giving users a curated experience that feels tailor-made just for them, which I believe is the future of content consumption. We are also extremely focused on enhancing the cinematic experience for audiences, giving them new tools and ways in which to interact with their favourite content, and celebrate their love for cinema.
On MovieMe’s AI-driven recommendation system working to personalise user experiences
MovieMe’s AI and ML-driven recommendation system is built on sophisticated algorithms that analyse a wide array of data—from a user’s viewing history and interactions on the platform to broader trends in content consumption, and over a thousand data points of movies (story arc, character development, plot tropes, etc.). By continuously learning from user behaviour, our system evolves to provide more accurate and relevant suggestions over time. It’s not just about recommending what’s trending; it’s about understanding the nuances of each user’s preferences and providing them with options they might not have discovered on their own.
On ways in which MovieMe has transformed content discovery for its users
One of the most gratifying aspects of MovieMe is hearing from users who have discovered hidden gems they would have otherwise missed. For instance, we’ve had users who primarily watched mainstream Hollywood films but, through our recommendations, found themselves exploring indie and international cinema that they ended up loving. Another example is our ‘Scenes’ feature, where users can discover movies based on short scenes or clips they enjoy, which has opened up a new dimension of content discovery, making the experience both personal and emotionally engaging.
On the role that machine learning plays in understanding user preferences and predicting trends on MovieMe
Machine learning is at the core of MovieMe’s ability to understand user preferences and predict trends. By processing vast amounts of data—from individual user habits to broader viewing patterns—we can anticipate what content will resonate with different audience segments. This allows us to not only recommend existing content but also provide insights into emerging trends that could shape future viewing habits. Our machine-learning models constantly evolve, ensuring that MovieMe remains ahead of the curve in predicting what our users want to watch next.
On MovieMe ensuring data security while providing personalised recommendations
Data security is a top priority for MovieMe. We employ robust encryption protocols and data anonymisation techniques to ensure that user information is protected at all times. Additionally, we are transparent with our users about how their data is used to enhance their experience. We believe that maintaining user trust is crucial, which is why we have implemented strict policies to safeguard privacy while still delivering the personalised recommendations that our users value.
On MovieMe adapting to the cultural trends that are currently shaping the entertainment industry
MovieMe is deeply attuned to the cultural trends shaping the entertainment industry, from the rise of diverse storytelling to the growing demand for localised content. We have incorporated these trends into our recommendation algorithms, ensuring that users are introduced to a wide range of voices and perspectives. Additionally, our platform is constantly updated to reflect the latest in entertainment, whether that’s emerging genres, the resurgence of certain formats, or shifts in how content is consumed.
On MovieMe’s unique features like ‘Scenes’ and ‘real-money game’ and its impact on user engagement
Our ‘Scenes’ feature allows users to explore movies based on short scenes or clips of content that resonate with them—whether it’s a thrilling chase sequence or a heartfelt conversation. The idea is to offer a new form of content discovery and allow users to discover content that truly strikes a chord with them. Of course, it also functions as an endless repository of bite-sized content, great for watching stuff in those little in-between moments when you don’t have time to watch full episodes or movies. This feature has significantly enhanced user engagement by offering a new way to connect with content on a deeper level.
The ‘real-money game’ – or forecast game, as we call it – is another innovative addition where users can predict box office earnings and win cash prizes. This gamified experience adds a layer of excitement and drives engagement by integrating users into the entertainment ecosystem in a more interactive way. It also helps us generate valuable data points about audience expectations around different movie titles and their genres, cast members, production teams, etc. These data can then help industry professionals make informed decisions about various components of their future releases, including production, marketing, and distribution.
On envisioning the future of AI in content discovery and entertainment, and MovieMe’s future plans for innovation in this space
The future of AI in content discovery is incredibly promising, with the potential to make entertainment experiences even more intuitive and immersive. At MovieMe, we’re exploring new ways to leverage AI to enhance personalisation, including more advanced predictive analytics and real-time recommendations based on mood or social context. We are also looking at how AI can be used to create more interactive and dynamic content experiences. Our goal is to continue pushing the boundaries of what’s possible in content discovery, making MovieMe not just a recommendation engine, but a comprehensive entertainment companion that evolves with its users.
