If you’re in the video content delivery business, you already know that, today, the OTT (Over-The-Top) video delivery landscape reaches far and wide and makes up for a fragmented and extremely competitive market. To give you an idea:
Ovum’s latest OTT Video Forecast estimates that the number of global SVOD subscribers will rise from 271 million in 2016 to 558 million by the end of 2022.
Considering the highly competitive nature of the market, OTT video delivery businesses are exploring new ways to in which they can actually differentiate themselves from competitors and stand out from the crowd.
Data mining is all around us. No wonder that data collecting systems – sensors, social media interactions, and smartphones – have become ubiquitous. As so, analytics has become the driving force for most of the decision-making processes in modern businesses. Using big-data, businesses can better understand their customers and offer services that are tailored to the audience’s taste and expectation. In sum, analytics are helping video delivery businesses to create more meaningful services.
Empowering AVOD and the emergence of new revenue streams.
VOD (video-on-demand) comes in three main flavors:
SVOD, which stands for Subscription Video-On-Demand – Users pay a fee (usually monthly) to stream an unlimited amount of content.
TVOD, which stands for Transactional Video-On-Demand – Buy or rent specific content whether it’s a movie or a show.
AVOD, which stands for Advertisement based Video-On-Demand – Users don’t usually need to pay any fees as ads support the content.
Putting it simply, data is critical across the board when it comes to VOD business models. Sensible analytics history allows businesses to “trim down the fat” from their catalog. For instance, when assessing the performance of VOD titles, decision-makers may decide to spend less money upon negotiating rights for a specific genre that’s not performing well. That money can then be channeled into purchasing VOD titles from a genre that’s expected to perform better.
AVOD, however, has a tighter relationship with data reports as its traits can be leveraged by meaningful holistic big-data. In fact, AVOD requires a Smart Business Intelligence module to achieve all of its revenue generation potential. In this particular case, knowing which titles and genres perform better is just not enough. You need to know who’s watching, when they’re watching, where they’re watching, and how they’re watching.
Ads displayed as banners and videos are AVoD’s main drivers of monetization. As all of the display advertisement goes: it becomes more efficient the more we know about the viewers.
According to Ovum’s latest research, AVOD will account for 17% of global TV and video ad revenue in 2022 and is set to be worth $37bn in global revenue.
At WeCast, we understand the potential of AVOD when used as a stand-alone business model (according to IHS Markit, AVOD accounts for around 95% of online video revenues), or as the perfect gateway for introducing new OTT services for future paying customers.
When setting up a new video delivery endeavor, or trying to open new revenue streams in already-existing business using the AVOD business model, it is essential to choose an Online Video Platform with a sturdy Smart Business Intelligence module capable of pairing the data and insights collected with the most popular services such as Google DoubleClick, Tremor Video, or YuMe. Moreover, you need to make sure the OVP you selected supports VPAID and VAST protocols to ensure complete interoperability between all advanced video ads, ad networks, and the OVPs own technology.
Keeping churn rate in check.
As OTT enters a truly worldwide mass-market stage, consumers are becoming more aware of their choices. In such a competitive arena, pricing, value for money and, especially, high-quality service, become critical KPIs for retaining customers, as most of them they won’t hesitate to switch to providers offering better deals.
In this context, understanding your customers and assuming a proactive approach to churn is critical. A few OVPs carrying proprietary Business Intelligence modules, like WeCast, are already using predictive churn modeling to identify customers who can potentially leave your service. By analyzing multiple data sources such as usage patterns, Churn Prediction tools allows you to flag individuals or groups of customers that might be leaving your service soon and give you the opportunity to act before they actually leave.
Offering better OTT service and amazing experiences
The benefits of big-data are exclusive generating additional revenue or retaining customers. It also impacts the QoS (Quality of Service) and QoE (Quality of Experience), which contribute to any business’ overall success and viability, thus ultimately impacting the revenue and customer retention.
On the QoS side, big-data can generate useful insights and metrics that can help you to reduce operational and after-sales costs by taking pre-emptive action from monitoring your network. For instance, you’re able to optimize your traffic by routing it through the best CDN nodes or identify and fix anomalies within the network that may be affecting your service.
When it comes to QoE, it is quite obvious that big-data can help you tailor the content you’re offering to better match your audience’s different profiles. But it doesn’t end in what you’re offering; it reaches into your service’s very own features an how users interact with it. As so, analytics assume a big role in understanding how your audience navigates through the user interface which allows UX-UI designers to fine-tune front-ends to deliver more exciting experiences.
We can help your video delivery business
At WeCast, we work hard to provide the best tools for video distributors to take their operations to the next level. That’s why our proprietary Business Intelligence module, allows our customers to understand and use big-data towards opening new revenue streams, increasing subscribers acquisition, reducing expenses, offering amazing experiences and maintaining a low churn rate.
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