Opinion: The impact of data-driven broadcasting

Vinayak Shrivastav, CEO, Magnifi by VideoVerse, explains how harnessing the power of data can boost creativity in broadcasting

By Contributor

Published: July 5, 2024 Updated: July 8, 2024

Vinayak Shrivastav, CEO, Magnifi by VideoVerse, explains how harnessing the power of data can boost creativity in broadcasting

target=_blank title=Share on LinkedIn class=share-linkedin> Vinayak Shrivastav, CEO, Magnifi by VideoVerse, explains how harnessing the power of data can boost creativity in broadcasting

https://www.tvbeurope.com/features/opinion-the-impact-of-data-driven-broadcasting title=Share via Email class=share-email>

Broadcasters are gaining access to vast amounts of audience data, ushering in a new era of insights.

As both traditional broadcasters and OTT entertainment providers assert their position in the market, the value of consumer insight and its role in achieving a competitive advantage has become clear. The recent integration of AI into broadcast workflows stands out as a pivotal development for the industry. AI is reshaping how content is curated, how schedules are optimised, and how audiences are engaged. Data-driven broadcasting enables media companies to deliver a more tailored, efficient, and engaging viewing experience, with customer loyalty and increased revenue as the reward.

Interconnected insights The relationship between user data, content acquisition, and programme recommendations, is becoming increasingly interconnected and reciprocal. Distributors, entertainment providers, and even production teams rely on data to identify and respond to viewer demands and preferences. As we move towards a connected TV ecosystem, data will play a more important role. But it is not just main platform data that can provide useful insights, tracking the performance of multiple versions of promo content across social media platforms can also influence content strategies.

Leveraging audience insight in broadcast workflows transforms the way media companies operate. Tracking relevance and how viewers interact with content creates an increasingly comprehensive picture, because each new insight is never isolated from historical data. This approach contributes significantly to a more satisfying experience for viewers. Of course, manually analysing this volume of data is a near impossible task. AI-driven data analysis enables media companies to stay ahead of the curve across content creation, delivery and social media engagement.

AI in action AI has revolutionised data analysis by swiftly processing large datasets and extracting actionable insights to optimise personalisation and efficiency. AI-driven data analysis has become indispensable for broadcasters, enabling them to understand audience preferences, predict emerging trends and tailor content planning accordingly. In this way, content owners can meet the ever-evolving demands of their viewers.

Armed with information on how content has performed previously, editors can also leverage AI workflows to efficiently select the most engaging segments from a film or series. This ensures teasers and trailers resonate with target audiences while conserving valuable time and streamlining the process. Several versions can be tested with different groups, enabling content owners to develop tailored strategies that resonate better with particular segments. Whether it's identifying intense moments in a match, main character highlights in a series or action-packed sequences in a movie, AI-powered editing tools supercharge the customisation of promo content to meet the unique preferences of different demographics.

Sports highlights are a great example of this, take the Vietnam Pro Basketball League, for example. Through the integration of AI-backed data segmenting solutions into their content creation process, the league achieved a 77 per cent increase in video production and a 76 per cent surge in viewership on Facebook in just one month. By leveraging data-driven insights, they segmented their audience, and developed tailored content strategies that powered growth and awareness.

Magic in the metadata Using metadata tagging aids in the process of organising and categorising content, making it easier to manage, search, and optimise for various platforms. Metadata tagging provides detailed information about the content, such as its genre, theme, key moments, actors/players etc. This used to be done manually and was a painstaking process, but AI algorithms can now analyse the content and automatically generate relevant meta-tags and detailed descriptions, ensuring accurate categorisation and streamlined content organisation.

Content owners can now easily monetise vast content libraries, handle content distribution across multiple platforms in different regions and optimise content search and discovery for viewers. AI-powered metadata tags facilitate targeted content recommendations, personalised content delivery, and improved user experiences. This approach not only boosts audience optimisation but also allows broadcasters to focus on creating high-quality promo content that resonates with their audience on social media.

Focused on the future The next generation of media is both personalised and interconnected. Access to vast audience data, amplified by AI integration, and extended across global entertainment and social media platforms will allow for unprecedented customisation. There may be concerns about becoming too dependent on AI, which could result in a loss of human touch in content curation and decision-making processes. But human influence in the creative process is never in question.

AI is an invaluable co-pilot that automates many labour-intensive tasks such as data analysis, metadata tagging, and content extraction, saving time, effort and resources. In fact, AI will liberate content editors to focus on creat

LINK:	https://www.tvbeurope.com/features/opinion-the-impact-of-data-driven-b...
	See more stories from tvb

Most recent headlines