Top 4 Use Cases for Media Companies in 2020

Posted on February 12, 2020

5 Minutes Read

With some of the biggest breakthroughs in Machine Learning and AI in recent times, inventions and concepts which were once only fictional dreams,  now exist at the comfort of bedrooms! Remember JARVIS (Just A Rather Very Intelligent System), the hyper-intelligent AI from the Iron Man movies? Jarvis is a personal assistant who can optimize tasks and follow instructions extremely well from  Iron Man. Today, voice assistants like Alexa and Google Assistant are no less and can control household devices, music, run alarms, read news briefings, among plenty more.

The Media and Entertainment industry has always been a cornerstone of contemporary human culture, delivering movies, TV shows, sports and so much more across the globe and over a multitude of devices. According to a report by PwC, the total M&E revenue is predicted to jump to approximately $2.2 trillion by 2021. However, globally the industry growth has been falling behind, so a large number of media companies are increasingly turning to innovative solutions to help fuel growth.

One of the biggest challenges for broadcasters is delivering delightful experiences to consumers in the midst of rapidly changing preferences and technological disruption. AI now offers a platform that can automate various media production processes and workflows including but not limited to editing, storyboarding, generating video clips, etc.

“The biggest reason why AI adoption will succeed is that Broadcasters and technology providers are coming together with the understanding that technology and humans have to work in conjunction to create transformative solutions” 

Vivek Khemani, Director, AthenasOwl

This article outlines the top 4 challenges we solved for media companies using custom Artificial Intelligence:

  1. Automate video QC and content transformation for faster content distribution

While the battle for viewer screen-time between broadcasters and TV channels remains fierce,  media companies are continuously seeking new strategies to retain their positions in the market. One of the most compelling opportunities involves monetizing of existing TV content from  OTT platforms like Netflix, Hulu, etc. However, to do this quickly and effectively, production teams need to spend hours conforming assets manually to meet the custom specifications for each digital platform.

With the help of AthenasOwl’s custom AI solution, a top 10 broadcaster in the US was able to improve efficiency and productivity by up to 5X and save up to 80% of creative editors’ time. Employees were able to significantly reduce the manual effort involved in scene level video logging and QC, leaving them the bandwidth to focus on more subjective and creative tasks.

  1. Easy Repurposing & Repackaging of Content 

While many companies still rely on existing media workflows, the current content logging and organizing process are time-consuming and error-prone. Creative editors often waste hours of manual effort looking for the most relevant and compelling clips for repurposing and repackaging of existing content.

One of the largest American broadcasting companies headquartered in New York City, leveraged AthenasOwl Smart Catalog solution to detect various elements like character faces, emotions, age-gender, custom locales, colour palette, highpoints and more for approximately 5 seasons of a popular TV show.

By incorporating an AI system, the content teams were able to generate rich metadata at scale and conduct quick and powerful searches at a scene level to facilitate easy repurposing and repacking of this content.

  1. Enriching the Sports Fan Experience

The modern football fan wants to be informed as well as entertained. Supporters still yearn for the pleasure that arises from the goal being scored or a defender making a good tackle, but they also seek a deeper understanding of the game. So as modern technology changes the way fans watch and interact with their favourite games, global sports broadcasters need to adapt to the changing digital landscape.

One of the biggest European Football Leagues was looking for a solution to help them quickly create short-form content pieces to share on their multiple digital channels – that can help them increase fan engagement.  Traditionally, sports broadcasters required large teams of the editor to manually pore over hours of match footage to find highlight-worthy moments. However, with AI, the solution is simple to speed up the process of logging and detecting football-specific moments within many years worth of match footage.

AthenasOwl Smart Catalog is custom-built for Football content, through which the client was able to generate rich metadata for over 50 years of old untagged content. Content managers could now search and retrieve moments as specific as goals, red cards, yellow cards, highpoints within any game and showcase across various digital platforms.

With the objective of leveraging better monetization opportunities in this age, the above use case is best to provide a solution to various broadcasters.

  1. Measuring Brand Visibility and ROI from Sports Sponsorships

While live sporting events are a fantastic opportunity for brands to showcase themselves and can have an incredible return on investment,  industry research reveals that about 40% to 45% of companies don’t have an effective system in place to measure sponsorship ROI comprehensively.

For example, the sponsorship team at Adidas might not be able to effectively gauge how many people noticed their logo on the Manchester United jersey when a game was telecast live on TV and OTT platforms. In the fragmented digital media and entertainment world, questions like how impactful brand visibility is as compared to the viewership and what is the level of audience engagement often remain unclear.

With such challenges in mind, a global premium sports company generating large ad revenue wanted to track and measure brand visibility, ad spends and relative ROI for their customers. An automated AI-enabled solution AthenasOwl Smart Analytics was able to help them detect the various sponsor brand logos and measure the screen visibility at near-perfect accuracy across channels while providing more sharper and strategic insights to their clients.