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Harnessing technology to leverage the power of data in AVOD

Journal Article from Symphony MediaAI

Thu 30, 09 2021

By Mark Moeder
CEO of Symphony MediaAI

Mark Moeder is the CEO of Symphony MediaAI, a US-based company specialising in revenue optimisation technology for media and entertainment. Symphony MediaAI has been at the forefront of revenue optimisation for over thirty years and has earned a reputation as the most trusted name in the industry. They process data and deliver revenue insights to more than ninety percent of the US media and entertainment market. Through the implementation of emerging technologies such as artificial intelligence (AI) and machine learning (ML), they are revolutionising revenue workflows and empowering clients with integrated data intelligence on a scale never seen before.

Moeder shared his perspective with IABM on the role of data and technology in maximising revenue for content licensors in the growing AVOD market.

“What’s driving interest in AVOD?”

We’re seeing continued movement of viewing from a traditional linear setting into the digital space. The majority of US studios now have their own direct-to-consumer (D2C) products, mirroring streamers like Netflix and launching in an increasing number of global markets. And it doesn’t end there. Broadcasters too are placing more focus on what they do with their adjacent digital platforms, accelerating (or adopting) a digital-first mindset.

Here in the US there are well over 300 OTT services, but many are finding they cannot survive on the SVOD business model alone. I think it’s really telling when you look at the activity of some of the biggest names in the business and how they’re all getting involved with AVOD. ViacomCBS’s acquisition of Pluto TV has proven to be an astute move and helped them to really establish a firm footing in the AVOD market. Then you have the likes of Fox Corp. buying out Tubi and they’re predicting it will return greater ad revenue than their existing broadcast entertainment network in the near future.

These global media organisations all understand the importance of AVOD and adding this additional pillar to their business model. It is critical to capture the share of viewing that is happening below the subscription tier. However, AVOD is still a comparatively immature section of the market and a new revenue model for many. Content owners seeking to track the financial performance of their AVOD strategies often rely on software that can accommodate existing revenue streams and data structures such as SVOD or broadcast, but AVOD is very different.

“What should content providers consider when planning a move into AVOD?”

AVOD is a strong opportunity for content owners to compensate for declining linear revenues, subscription fatigue, and SVOD churn. But in order to retain a competitive edge and maximise income, they must embrace the full applications of big data. Real-time insight is absolutely critical for accurate revenue recognition, tracking and forecasting. It enables adaptation and efficiency as market conditions shift.

However, the sheer volume of data available - not least in its varying degrees of quality and complexity - can prove overwhelming barriers for those who are unprepared.

Take for instance licensing agreements: A typical content owner is managing a master agreement, licensing deals for each title or series, and any number of contractual amendments for every AVOD platform that distributes their content. Add to that complex revenue sharing terms, many of which involve variable rates and data fields that have never been tracked before like minutes of ads viewed – and then multiply that by the number of titles and distributors you’re dealing with. Content owners don’t just have to track more data, they have to track an entirely different type of data. Some of it is quantitative, like ad plays; some of it is qualitative, like agreement clause language. It gets extremely complex extremely quickly, and the teams that manage AVOD revenue (e.g. finance, legal, distribution) must quickly mature data operations to keep up.

We still encounter businesses today that are tracking their content distribution activity in spreadsheet applications like Excel. They’re having to input information from their contracts, the content that they’re providing, the financial returns and performance measure by hand. All of that data is being ingested through an incredibly manual process. They’re then relying on a person or a team of individuals to analyse and essentially dictate AVOD strategy when they could instead utilise technology to perform these acts on a much larger scale, providing them with high quality and actionable insights in an instant.

To be clear, licensing teams aren’t stuck with outdated systems because they’re somehow lagging or resistant to change. Most simply don’t know there’s any other way. Technological developments in media and entertainment have largely focused on production and ad distribution, overlooking “back office” functions like legal and accounting. Fortunately, that’s changing.

What are the main strengths of AI and machine learning?

As the adage goes, “You don’t need a weatherman to know which way the wind blows.” I think that is a good summation of what people in the Media industry may be thinking when it comes to content distribution and trusting their instincts. Yes, you can step outside and see what the weather is today, but can you accurately predict if you’ll need to take an umbrella with you in two weeks’ time? This is where AI and machine learning steps in. You can take all the data that you already have and more accurately predict what’s coming.

AI can aggregate all your different sources of data, where there’s often little in the way of normalisation across formats and outputs, and really help you to analyse and interpret huge volumes. There are so many different AVOD services out there for distributors to supply with content, but how are you to really tell which are the best opportunities for you? How do you know what content will work best in which environment? Which licensing models offer the best returns? Instead of modelling all of this manually - which can be incredibly time intensive - AI software can automate the entire process and accurately forecast demand. Consider the resources required for a team of even the most senior data scientists to predict ROI for a licensed content library by region, by title, genre, audience segment, replayability, and a myriad of other important data points across multiple platforms with wildly different audiences.

Simply put, AI generates quality of insight for a business that is unrivalled and can really empower their AVOD revenue streams.

AI and machine learning can no doubt help the AVOD platform owners too?

Absolutely. There are so many applications of AI and ML in helping not just content providers, but also the AVOD platform owner.

ML is especially powerful here. You can think of ML as an AI system’s ability to teach itself, thereby increasing its value to the organisation over time. That happens two ways: with supervised machine learning, you know what insights you’re looking for and train your ML system to answer business questions in an instant. That’s incredibly useful for AVOD platform owners that want to understand audience behaviour, for example. Unsupervised ML is where AI really comes into its own, working autonomously in the background and analysing your data to find patterns, anomalies, and answers to questions that you wouldn’t have thought to ask. Instead of just telling you who’s about to churn, it can detect underlying churn drivers you weren’t aware of. It can predict which audience segments will have the highest lifetime value and the highest near term time-spent-viewing. It’s exactly the sort of strategic insight AVOD platform owners want to get ahead of their market competitors.

As I said before, the SVOD model doesn’t work for everyone. A lot of businesses - particularly in the US and the UK - are adapting to the freemium AVOD model. This offers an additional revenue base for distributors struggling with slow subscriber growth and/or high turnover. (Instead of cancelling a subscription, subscribers now have the option to downgrade to the ad-supported tier.) Just as importantly, it offers a wealth of subscriber insight. AVOD platform owners can leverage AI insights not only to identify those users who might be ready to step up and upgrade to SVOD again, but also to optimise pricing strategies and help personalise content recommendations to hook people in.

Ultimately, AVOD data doesn’t just grow AVOD revenue. With adequate data intelligence, it fuels organizational growth.

AI and Machine Learning sounds complex, how difficult is it to understand as a user?

Symphony MediaAI has been active in the media distribution and optimisation field for over 30 years, and we’ve seen a lot of positive technological change in that time.

Yes, these are complex technologies on the back end. But companies like ours exist because we recognize the value in making data intelligence accessible to everyday users. We quite literally take AI and ML out of the lab, where our R&D teams are making really interesting breakthroughs, and put it into the hands of business users. That’s the rewarding part for us: to see our clients effortlessly implement the world’s most advanced data science technology in their daily workflow.

It’s very clear to me that data isn’t going to become a valuable commodity if end users need an advanced computer science degree or decades of experience as a financial analyst to understand it. That’s why we’re also committed to optimising the front end. Our product teams have actually spent time in media and entertainment finance roles. They’ve executed the same workflows our clients execute, reported to the same stakeholders, faced the same challenges. That real-world experience is integral to our product design. Users aren’t looking for AI, they’re looking for time savings and revenue growth. We’re committed to building products that enable users to do their jobs better, without having to master the technologies that sit under the hood. It’s an exciting moment to bring that sort of accessibility to market.

Distributors looking to extract real value from AI must likewise consider the needs of those business users. How do we arm both technical and non-technical individuals with the right amount of information that they can understand, learn from and apply in a business setting? Unless this insight is readily available to those who need it and can be acted upon immediately, technology is worthless.

What is next for Symphony MediaAI in the world of revenue recognition?

Data is the oxygen of revenue performance. Content providers must strive to attain the maximum data rights in their content partner agreements, but you need to have a data platform to make sense of it all; a platform that can ingest, learn from, analyse and make predictions based on this data.

Our vertical AI solutions cater to the unique data landscape of the media and entertainment industry. That allows businesses to navigate this complex and fast changing ecosystem, optimise their strategy and sustain their competitive edge.

Looking forward, we’re focused on continuously releasing features and products that multiply the value we bring to the teams we support today. We’re also evaluating where we can add further value throughout the enterprise. How can customer marketing, data science, and product development teams best leverage the solutions we’ve developed? What other sectors of the industry can benefit from our technology? Those are the strategic conversations taking place right now, and we look forward to expanding our capabilities as the industry evolves.

About Symphony MediaAI

Symphony MediaAI is the leading provider of revenue optimization solutions in media and entertainment. Its Revedia SaaS platform automates end-to-end licensing revenue management and analysis to maximize workflow efficiency, data analysis, and revenue growth for content owners and rights holders. Having analysed billions of transactions on behalf of industry leaders and emerging innovators for over thirty years, Symphony MediaAI brings a deep operational understanding of content providers’ unique revenue and data challenges. Learn more at www.symphonymedia.com

Mark Moeder, Chief Executive Officer at Symphony MediaAI, is a growth and transformational oriented executive with an extensive knowledge of general technology and the media space. Carrying 20 years of industry experience in the media industry; centering around technology, revenue management, and optimization. Mark joins SymphonyMediaAI from 10 years at WideOrbit Inc, the preeminent ad decisioning and ERP provider for TV/Radio/Cable industries, where he served as chief operating officer. In this capacity, Mark oversaw business operations for WideOrbit’s various product verticals, all externally facing initiatives, special projects, and strategies. Prior to WideOrbit, Mark spent seven years at Google. Serving as technical operations manager, Mark managed operations for Google’s Broadcast division, specializing in the real-time insertion of advertising on live Radio Broadcast streams. Before pivoting to a technology specialization, Mark spent several years in the media industry proper. Holding positions of Operations Manager, Director of Programming and on-air talent to Radio and Television organizations throughout the Midwest.

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