The power of audience analytics in media and entertainment

This article was originally published in the Winter 2018 issue of The Record. Subscribe for FREE here to get the next issue delivered directly to your inbox.  

It doesn’t take a trained eye to recognise that the media and entertainment industry is rapidly undergoing digital disruption. “Compared to audiences ten years ago, today’s consumers have access to unlimited amounts of content and are consuming it on an increasingly diverse range of technologies and platforms,” says Jennifer Cooper, global head of Media and Communications Industry Strategy and Solutions at Microsoft. 

In this media-saturated environment, audiences demand content experiences that are enriching and convenient, and consumption patterns are changing in response. “Recent research from Deloitte has revealed that in the last 10 years alone, video streaming subscription rates in the US have increased by approximately 450%, and this isn’t the only dramatic shift,” says Cooper. “Millennials now spend almost 15% of the time they devote to movies and television watching on smartphones. As a result, media and entertainment leaders face increasing pressure to find new ways to monetise content and generate revenue.” 

With this in mind, companies that rely on traditional business models are now facing a new reality as their business declines. “To remain profitable in this shifting environment, companies must develop monetisation strategies that rapidly deliver content to global audiences, attract and engage paying customers, and provide differentiated services to retain advertisers,” Cooper says. “Monetisation is a complex challenge that doesn’t have a single solution, but digital transformation is the clear imperative. Achieving these goals requires the agility, flexibility and scalability that only cloud technology can deliver.”  

Tania Yuki, CEO and founder of social intelligence firm Shareablee agrees that traditional business models must now be abandoned, advising that “media companies must let go of historical notions of owning the consumer in the time or in space via appointment viewing, and fully embrace an open model of joining audiences where they are already giving their time and attention.”

Success, says Cooper, requires media and entertainment companies to go further in developing personalised experiences. “According to recent Piksel research, 62% of viewers in the US and the UK will switch providers or channels if they aren’t able to find content that interests them,” she explains. “While many content platforms try to address this issue by providing recommendations, consumers aren’t satisfied. Only 16% of consumers say the content recommendations they receive are consistently very good.”

Tim Burke, CEO at marketing strategy platform Affino adds that winning this battle requires media companies to have a deep, rich understanding of their audiences, not as a whole, but nuanced based on the different personas it is attracting with the content it shares. “What are the interests and passions of these audience segments?” he asks. “What makes them engage? What other content do they consume? How do they consume it?”

In order to answer these questions, it is essential for media firms to better understand metadata.  “Artificial intelligence (AI) tools like Azure Video Indexer empower production teams to rapidly tag content automatically based on spoken words, faces, characters, and emotions,” says Cooper. “By using machine learning to analyse this metadata along with content performance and customer behaviour, leaders like Complex Networks are transforming the viewing experience to personalise it in near real time.”

Dan McQuillin, managing director at software development and hardware distribution company Broadcast Bionics explains that by harnessing audio and video metadata, the company was more able to offer a modern, integrated and intelligent solution to deliver the workflow in a much simpler way, which “enabled broadcasters to create better content, to reach new audiences on new platforms and monetise it in new ways.”  

“Where teams previously relied on supervised learning tools that required time-consuming manual workflows, today’s leaders use advanced machine learning engines like the Azure Custom Decision Service to continuously test new content experiences and select those that resonate most with viewers,” says Cooper. “This data-driven approach to building personalised content experiences goes beyond audience retention and churn rates – it also enables companies to deliver new value for advertisers.” 

Broadcast Bionics’ AI technology helps traditional broadcasters not only understand what’s going on, but also measure and monetise content across different platforms, which, according to McQuillin, is very important for the commercial models necessary for sponsors and advertising. “With that in mind, our technology is designed to offer the personalised experiences that advertisers will demand more and more in the future.”

According to Burke, “analytics can’t just be about time of day and minutes watched. The amount of rich first and third-party data available needs to be leveraged for the creation of data-driven personas. Understanding an audience’s passions, interests, and preferences provides media companies with an understanding of the context behind why an audience consumes specific content,” he said. “In the age of the attention economy, where consumers have a massive amount of selection in terms of content to consume, a lack of understanding of your audience means you will be out of business.”

This is an opinion shared by many, including McQuillin, who states that “broadcasters can increase their social engagement and the sharing of their content by capturing the attention of those who have an emotional engagement with the content.” 

However, this isn’t just a pressure felt by media and entertainment firms – advertisers are experiencing similar challenges. Cooper explains that capturing the attention of the consumer is becoming more difficult and so they are turning to the media firms to resolve the issue. Delivering these desired results means matching the right advertisements with the right content, which is no mean feat.  “More than 55% of consumers indicate that even relevant advertisements take away from the viewing experience, according to IBM. To deliver for both groups, business leaders must use data to improve advertising efficiency.”

In order to please both sides, companies should use AI and audience analytics. “By using tools like Azure AI to identify viewer attributes and analyse browsing history, leaders can develop more accurate audience segments and hone individual preferences,” Cooper said. “When paired with metadata generated by production tools like Azure Video Indexer, these insights empower companies to pair viewers, content, and products with increased accuracy to keep the advertising revenue flowing.” 

Partners like Affinio have developed AI segmentation and visualisation technologies on Microsoft Azure that enable media companies to gain deeper understanding of their audiences, at a granular level. “We are putting the power of AI at the fingertips of marketers, content creators and ad sales teams,” says Burke. “This enables them to unlock the valuable audience intelligence that is buried in their data lakes, so they can make better decisions around content, distribution and maximise the value of their inventory by automatically identifying the audiences of highest value to the advertisers.”