As the TV and video market continues to evolve, recommendation and discovery solutions must dynamically respond to changing consumer patterns. Content recommendation systems must take into account the full range of consumer experiences, as well as stay informed about content business rules and financial goals in order to succeed.
These are some of the findings from nScreenMedia’s latest paper, commissioned by ContentWise , the personalization, discovery and recommendations solution for digital TV content. Entitled ‘Preference is just the Beginning: Video Recommendations in the Age of Mobility’ , the paper highlights the key factors that will be instrumental to the success of discovery and recommendations for operators, aggregators and content providers.
ContentWise is a business unit of Moviri, a leading provider of data mining and optimization solutions for enterprise IT systems and digital media, working with CMS platforms and front-end applications -- on VOD, linear and pay TV -- to deliver a personalized experience to end users and to provide management tools, reporting and analytics to content acquisition, marketing and editorial teams.
“With a huge number of TV and video choices available today, it is becoming increasingly difficult for viewers to discover content in the TV and video world. And from our discussions with operators and content providers during NAB and TV Connect, this volume of content is also proving to be a challenge as they are finding it difficult to surface programs with the right potential to their audiences,” said Paolo Bozzola, CEO, ContentWise. “The future of personalization will rely on contextual information. This information is instrumental in keeping recommendations and discovery relevant for viewers and effective for operators and content providers.”
Therefore, ContentWise asked nScreenMedia to independently research and author a white paper on the critical functions of a 21st century video recommendations system. The paper examines five key topics that are pivotal for the future of recommendation and discovery, namely preference, location, time, target device and business rules that will all play a crucial role in personalization, presenting tremendous opportunities for both viewers and content providers alike.
Some of the key findings from the paper include:
· Preference: Preference remains a key factor in what recommendations viewers will find valuable. However, the explosion in content choices, devices, and external influences like social media, all influence content preferences for viewers. By building complete preference profiles, operators can drive on-demand viewing and revenue goals, especially for their subscription services.
· Location: Location is dramatically affecting what content viewers prefer to watch, and services need to consider whether viewers are watching content in the home or on the go. Recommending content that is applicable to the environment will be a truly valuable asset, especially to advertisers.
· Time: While the time a viewer watches linear TV is a known quantity, the time of day that a viewer watches on-demand content is different each time. Being able to contextualize the adverts within content with high relevancy will add value for both the viewer and the content provider.
· Target Device: Every viewer prefers different content on different devices and what they find relevant in terms of programs and advertising can change significantly. Recommendations that can take that into consideration and are responsive to target device will dramatically change the viewing experience for consumers.
· Business Rules: Today there are many business practices that must be taken into consideration within the dynamic TV ecosystem - whether that is rights for different platforms, such as online or VOD, or how long content can be made available. Recommendations and discovery must be aware of these business rules. A service cannot recommend content that is not available due to restrictions on device, location or time, while ad targeting must be aware of what programming ads can be shown in.
“If you don’t use context variables like time, location, device and content preferences to build profiles, then you don’t see the real dynamic picture of the viewer’s consumption,” said Pancrazio Auteri, CTO, ContentWise. “Having a full picture of your audience will enable content providers to let context-aware personalization drive whole user experiences, delivering content users value and ultimately drive revenues.”