Artificial intelligence (AI)- and machine learning (ML)-driven analytics are busting long-loved myths and giving savvy media companies the radical insights they need to upend how they do business, and the technologies can be used to give a lift to their revenues, according to Shiv Sehgal, chief product officer at RSG Media.
“In the next 15 minutes, we hope to first ignite the spark for your organization to begin and complete the ML/AI journey, which requires a strategy and appreciation for an aligned cloud, data and machine learning and AI strategy,” he said July 2 at the start of the AI, ML, CX & Supply Chain breakout session “I Know What You’re Going To Watch Next Summer: 5 New Ways Media Companies Use Machine Learning to Massively Grow Revenues by Decoding & Influencing Viewer Behavior” at the Global Media & Entertainment Day event presented live, virtually, from London.
He and Shawn Brennan, information architectures sales leader at IBM, used the session to explain how the two companies are applying AI and ML to media, specifically via the RSG Audience platform on the IBM Cloud, which Sehgal touted as “the industry’s first AI platform to decode data for radical insights.”
Sehgal went on to cite five ways media companies can use ML and AI to massively grow revenues.
First up was performance tracking. “Everybody wants to know how they are doing across platforms” and on linear vs. non-linear platforms, Sehgal said, noting RSG is joining linear and non-linear data sets. “We’re taking program metadata and curating those metadata sets across… many parameters such as key words” and whether a show is scripted or not, he told viewers.
The second way he cited was using audience insights. “There’s so many questions to ask around the industry,” he pointed out, adding: “How am I performing is just the beginning and if we can enable natural language on top of these data sets — just to democratize the insights across an industry — that is enabling what is the interesting part of this programming research side of things…. All of a sudden, you can understand how you’re performing easily so you can understand who are my viewers. You can start to segment your viewers, understand the profile of your viewers… You can understand the migration and journey of viewers.”
The other three ways he said media companies can use ML and AI to significantly grow revenues are via audience profiles, audience migration and viewer retention and acquisition strategies.
Data can be used to figure out the best time to air a promo or a program to “prevent any leakage” to other networks and programs, and “gain viewers along the way,” he told viewers.
“By sweating the small stuff … you can really move and advance the industry forward by introducing tools that allow people to interact with the data, but also get the key insights they need so they can focus on the strategic side of the business, which ultimately is building the optimal program schedule,” he explained.
He went on to share a few predictions on what will be launching next summer based on his company’s “stitched solution” ML-AI decision-making platform.
First, he projected there will be an increase in viewership for live sports next year that will include pregame content also, which he noted “impact the lead-in and lead-out” for a network’s other TV shows.
He also predicted there will be increased viewing of broadcast movies next year – specifically, daytime, family-oriented movies featuring elements of adventure and romance.
And he also predicted we will be watching an original program on cable TV next summer that will be created by Netflix or one of the other major streaming services.
Enterprises have declared their data journey to AI top priorities, according to IBM’s Brennan, who said 90% plan greater investments in data and 85% view AI as a strategic priority.
On the data maturity curve, “most organizations are somewhere in the middle,” Brennan said, adding: “To start our journey, it’s critical to understand your current state. Sometimes you know right away and sometimes it maybe takes a third-party view to really understand where you’re at. Once you recognize where you are,” then you can “implement a strategy to reach the future state and start unlocking the true value of your data.”
He went on to tell viewers: “For a typical Fortune 1000 company, just a 10 percent increase in data accessibility will result in more than $65 million in additional net income. So that’s huge. Meanwhile, the average financial impact of poor data is about $9.7 million per year. Those points just show the importance around getting value from data and how that can impact your organization. So it’s critical for organizations to move up this [maturity] curve. We know 40 percent of companies are struggling to retain talent to help them uncover these insights. So getting to strong points around self-service analytics and being able to apply machine learning everywhere helps the business automatically and rapidly discover these new insights.”
There are, however, “a lot of challenges” that media companies face in reaching … the upper part of the data maturity curve, he said. “Legacy systems make it difficult to connect and utilize data sources,” he noted, adding: “We have all heard data data data is the new currency. But 80 percent of data in AI work is spent on simply finding, preparing and governing the data. So this is one of the biggest issues. Just getting data is hard within an organization and when you do get it, it usually has a bunch of stuff you don’t want and you usually need to combine it with other data sets to get what you really want it to be in the first place. And once you’re at that point, you can start getting the value your organization really needs in order to kind of make its way up that curve.”
On the other hand, he said: “Now imagine a world where you can just jump to the getting insights part. Imagine how much time could be saved if you didn’t have to spend 80% of your time looking for that data.”
Another challenge is that “only 13 percent of analytics and AI projects reach completions,” he said. The problem is that one key ingredient is often missing, he told viewers: “You need a strong platform to help you get to the future state vision.” RSG used IBM’s platform to build its own platform specific for the M&E industry and the challenges it was facing, he said.
The fourth annual M&E Day event, presented by the Media & Entertainment Services Alliance (MESA), featured mainstage panels and more than 15 breakout sessions, covering the latest it data, cloud, IT and security across the media and entertainment technology ecosystem.
The event was presented by Caringo, with sponsorship by Convergent Risks, Cyberhaven, Richey May Technology Solutions, RSG Media, Signiant, Whip Media Group, Zendesk, Tape Ark, Sony New Media Solutions, 5th Kind, ATMECS, Eluvio, Tamr, the Audio Business Continuity Alliance (ABCA), the Entertainment Identifier Registry (EIDR) and The Trusted Partner Network (TPN).