Hyper-Personalization Using Content Discovery
With the increased amount of video content in the market, it has become challenging for users to search for the content that they want to watch. Out of the many factors that contribute to overall user experience, content discovery is the most crucial.
Limitations of today’s content discovery methods
Individuals who are engaged less frequently with newer content discovery methods are more likely to provide low ratings for the overall user experience. 
A recent survey  indicates that
83% of viewers look for something new to watch a few times per month
73% of viewers believe that their friends and family know their viewing preferences better than their streaming service
42% of viewers spend their time searching for the right content to view
Operators are continually enhancing traditional content discovery method by integrating powerful recommendation engines, interactive UI for near-term and adopting AI for the long term success.
Enhance traditional content discovery for near-term success
The next-gen viewers have limited viewing hours and shorter attention span. Operators can avoid churn through personalized & tailored options by helping viewers to quickly discover the content of their choice.
IHS Market analysis has identified content discovery methods widely used by viewers which can be enhanced by operators using the following solutions:
Viewers generally rely on a TV guide to help them discover the content of their choice, which can be enhanced with integration of powerful recommendation engines, voice-based navigation and personalized picture based TV guide. By integrating a powerful recommendation engine, the time viewers spend in viewing the content would increase by 25% - 50%.
Operators can bring in user profiles, which would store information about the viewing patters, to provide better recommendation.
Recommendations by TV/ video provider
One way to offer personalized content is to provide a better recommendation, which can be achieved by bringing in user profiles and powerful recommendation engines. With a powerful recommendation engine, the time viewers spend in viewing the content increases by 25% - 50%.
Flipping through channels
Most of the time viewers are not sure about what to watch and spend their time flipping through channels to discover the right content. Implementing UX to showcase a preview of next 3-5 channels can make viewers’ choice easy.
Predefined section on service
With the availability of a massive amount of content, it becomes important to offer easily accessible personalized content to the viewers which can be achieved by providing predefined sections such as most watched, favorites, etc.
Search functionality on video service
AI technologies like ML, NLP can be used to analyze user pattern and previous viewer’s behavior can be seamlessly integrated into the existing systems to offer individualized result.
Recommendations by family, social media and friends
Social media platforms and recommendation by family and friends are growing as a result of video content awareness. Integration of social media in your platform would help to enhance the content discovery.
|CONTENT DISCOVERY CATEGORIES||SOLUTIONS|
|TV guide||Integrate voice or IMDb ratings|
|Searching online||Integrate browsers & search engines|
|Recommendations by TV/video provider||Bring in user profiles & better recommendation engines|
|Flicking through channels||UX for showcasing next 3 channels|
|Predefined section on service||Personalized content readily available|
|Search functionality on video service||AI based searches|
|Recommendations by family, social media and friends||Social media integration|
Content discovery of the ‘future’
To offer the best user experience, service providers need to improve their content discovery mechanism and extend hyper-personalization. The idealized platform will deploy AI, machine learning and predictive analysis to understand every piece of content to learn more about the viewing pattern, offering contextually relevant experiences with more personalized suggestions. This would also help in segmenting the audience for targeted content discovery and advertisement.
With the integration of voice, the most exciting element is the ability to detect the intent of viewers. Suggesting movies or shows that viewers would be highly interested in, based on voice tone and emotional state would be a game changer for any content discovery platform, which would include:
- Personal assistant
- Interactive & UX enhanced mobile applications
- Contextual content discovery
- Powerful universal search
Tata Elxsi’s Centre of Excellence (CoE) has built a platform to accelerate deployments targeting higher levels of personalization and quicker content discovery.
Tata Elxsi’s Content Discovery Platform
Content discovery platform is a versatile, intelligent video analytics solution with image tagging as its core feature. It aims to offer insights to improve customer experience and generate newer avenues of monetization. Highlights generation, immersive and targeted advertising, closed caption creation for the hearing impaired audience, interactive gaming analytics, content performance (interest, emotion, attentiveness, demography) are some the prominent features to improve the overall user experience. The platform enables contextual commerce on TVs.
Today the critical point for operators to be relevant is to offer hyper-personalized content with near-zero time for content discovery.
Having a platform that uses AI to give viewers the ability to search, discover and quickly view hyper-personalized content will determine success for OTT operators.