Evolving viewer consumption preferences, driven by new devices and services, have led to a shift in content delivery methods employed by video service providers (Pay TV operators; OTT players). More advanced set-top boxes and applications have been developed to facilitate this trend, resulting in a significant increase in viewing data generated. In this insight, we explore how video service providers can leverage this data to establish an edge in the increasingly competitive video services industry.

Video Analytics: Extracting Value from Video Data

By Samuel Kornstein and Rishi Modha 

Viewer preferences and video consumption habits are shifting, enabled by the rise of new technologies and widespread adoption of advanced STBs and consumer media devices. New video services have emerged to meet shifting consumer viewing preferences. For example, pay TV operators are delivering TV over the internet (TV Everywhere) and pay TV alternatives, like Netflix and Hulu provide over-the-top streaming subscription video on demand services (OTT SVoD). Accordingly, content distribution technologies and viewing habits have changed. IP-based delivery has superseded traditional content delivery methods, and a complex ecosystem has developed around creating, managing, and delivering video content.

The central challenge faced by video service providers of profitably delivering top quality content to their audience through a seamless user experience has become more challenging as a result of fragmented content delivery methods and an increasing number of consumer devices. Successfully delivering a consistent and refined customer experience in this challenging environment can therefore be a key differentiator.

Video Analytics - Rise of OTT Subscriber Projection

New content delivery methods have been adopted throughout the industry. Beyond OTT video service providers, traditional providers now offer IP-based/digitized set-top boxes in addition to TV Everywhere (TVE) services. Moreover, the number of internet-connected set-top boxes have grown substantially in recent years, and is expected to more than double by 2017 (see figure 2). As a result of increasingly common and technologically advanced digital set-top boxes, the rise of TVE services, and new, internet-based OTT platforms, video service providers now have the capability to collect and analyze tremendous amounts of data about video consumption and usage.

Video Analytics - Number of Internet-Connected Set-Top Boxes

In the Internet age where granular viewing data is abundant, understanding consumer preferences and tailoring content, advertisements, offers, and services to individual preferences is not only crucial to attract new consumers, but also to retain and further monetize existing consumers. The sheer size and granularity of set-top box data enables executives to dive much deeper into audience behavior than possible with audience samples – it enables the industry to look at smaller and smaller geographies, demographics, and time periods. Content acquisition, programming, and sales & marketing executives have traditionally relied on high-level geographic and demographic data about consumers to inform important business decisions. While that approach is informative, integrating consumer viewing habits and usage significantly enhances the ability to understand consumers and tailor offers and content based on real and actual behavioral data.

As video viewing technologies become more advanced and interactive, it is likely that viewing preferences will evolve further. The abundance of data available to video service providers, either through streaming players or connected set-top boxes, can prove to be an invaluable asset. Video service providers will need to take advantage of this asset in order to flourish in an increasingly competitive climate.

Video Analytics - Evolution of the Set Top Box

Extracting Value from Video Usage Data

There are a number of areas that video service providers can stand to benefit from analyzing their data, including the following:

Video Analytics - Benefits of Data Analytics

The sheer size and granularity of set-top box data enables executives to dive much deeper into audience behavior than possible with audience samples.

1. Content Analytics

Traditionally, video service providers have relied on TV ratings and consumer demographics to understand popularity of programming and consumer viewing preferences in order to make decisions that affect business performance. As the quantity and granularity of data increase significantly, video service providers are responding by shifting their analytics approach beyond analyzing basic TV ratings and simple consumer demographics. Providers now have the ability to leverage their wealth of data to obtain a more holistic and detailed understanding of their consumers by integrating subscriber, set-top-box/OTT platform, and third-party data in near real time. This new analytics approach enables providers to better and more accurately reach consumers across various viewing devices and devise more telling and practical consumer segments.

Currently, video service providers are facing several challenges in a rapidly evolving industry. Firstly, as more content becomes readily available on the internet, video service providers are struggling to maintain content differentiation and identify new growth drivers. Secondly, as consumers now have multiple video viewing device options, it is becoming increasingly important, if not a necessity, to understand consumer behavior and preferences across multiple video viewing devices.

Video Analytics - Viewing Session Duration and Number of Viewers

2. Upsell/Cross-Sell Potential

Tapping into the wealth of data video service providers have access to can help these providers obtain a better understanding of their existing consumers, and in turn, identify upsell or cross-sell opportunities. For most video service providers, the opportunity lies in how to upsell existing consumers into premium content and other services offered – the key is to accurately identify upsell and cross-sell opportunities across viewing devices (e.g., activation on multiple devices; premium content) through analyzing behavior and demonstrated consumer needs.

Video service providers can develop granular segmentation to more accurately pinpoint upsell and cross-sell opportunities. The growth in available data allows video service providers to identify precisely who within a household is watching TV based on data analysis on viewing habits, preferences, and usage patterns across different devices. Video service providers can leverage this data-enabled knowledge and practical segmentation approach to refine their sales and marketing approaches, as well as their customer relationship best practices.

Video service providers are now able to use advanced data analytics to identify and segment customers with highest upsell or cross-sell potential. For example, upselling existing subscribers the ability to watch on multiple devices may be most attractive to younger subscribers demonstrating low video consumption on traditional viewing devices. Or for traditional pay TV operators, upselling live TV (such as premium sports packages) to households with viewers that regularly watch catch-up sports TV.

3. Product Improvement

Delivering content well is key to succeeding as a video service provider. Beyond having differentiated and valuable content, leveraging data to ensure that viewer experience is as smooth as possible and that the product is always relevant is key. Quality of experience is now considered one of the most important differentiators for a video service provider. In addition, given the proliferation of video viewing devices, it is no longer sufficient to deliver content well on one platform, but across multiple platforms. As a result, it is necessary for video service providers to have a holistic view of user experience and product functionality.

Armed with large quantities of data, video service providers now have the capability to understand errors and issues (slow bit rate; buffering, pauses, etc.) encountered by users with more depth, and potentially understand user experience by analyzing how errors & issues affect or inhibit consumption behavior. This can help video service providers quickly identify key elements in improving user experience (e.g. finding correlation between errors encountered on specific devices vs. content being watched). Moreover, providers can make functionality improvements by gauging user experience through identifying most used functions, missing functions, consumer learning curve, and product’s ability to reach all devices. For example, video service providers can analyze how users interact with their services when new functions or features are introduced, how that affects viewing behavior, and what adjustments need to be implemented.

Video Analytics - Number of Errors Encountered by Minute

4. Password Sharing Mitigation

New services and delivery methods have freed content viewing from a number of constraints, allowing viewers to watch content out of the home, across a range of devices and at times that suit them. This creates some commercial risk for video service providers, as it is now possible for a non-subscriber to use a service by obtaining the password of a paying subscriber. As a result, video service providers need to be able to identify possible misuse and develop reasonable mitigation policies that limit the practice and protect revenue as best possible.

By combining detailed viewing logs with further information, such as GeoIP databases and demographic information, video service providers can use advanced analytic techniques to effectively identify suspicious usage patterns. For example, identifying that a subscriber consistently uses multiple devices, many of which have never been used in the subscriber address, to watch the same piece of content provides some evidence that password sharing may have occurred. By forming multiple high-risk patterns and building subscriber segmentations based on this, video service providers can accurately identify high-risk subscribers in addition to understanding their behaviors and content preference. This information prepares them for effective mitigation actions, which could include a revision of device limitation policies or the launch of targeted new service offerings aimed at signing up non-paying viewers.

5. Churn Reduction

Video service providers are under increased competitive pressure with more services available for viewers to choose from than ever. To succeed in the current environment, it is crucial that they are able to retain subscribers on their platforms. Of course, offering quality content and delivering a strong user experience is at the heart of effective retention, but focusing on solely on making these aspects great is not sufficient, churn needs to be properly measured and understood to be reduced in the most effective way.

Key drivers and paths to churn can be identified by analyzing key factors (such as engagement levels, user experience metrics and content preferences) against historic churn patterns. Armed with this, video service providers can prioritize service improvements that mitigate churn. Adopting a data-driven approach can also help them to be proactive in addressing churn. By developing predictive models that calculate the chance and likely causes of near-term churn for individual subscribers, video service providers can remedy any issues before a subscriber takes any action themselves.

Video Analytics - Identifying Churn Risk Factors

6. Advertising Revenue Optimization

Advertising spend is shifting as collective attention moves from traditional formats to digital. Taking into account the increased competition for viewers, it is imperative that video service providers make the most of their data in their bid to maintain and grow their advertising revenues in the current climate. To maximize revenues, it is crucial that video service providers understand their audience (across all platforms) and the consequent value of their inventory and are able to clearly communicate this to advertisers.

User segmentation based on a number of factors, including content preferences, demographic information and multi-screen engagement, can help to build clear profiles that can help advertisers understand what they are buying. As multiple valuable viewing segments shift to multi-screen viewing, being able to measure actual viewing and engagement across these platforms will only help to further justify spend.

Crucially, the volume and granularity of data available to video service providers can be leveraged to innovate new and potentially lucrative opportunities. For example, high-value micro-segments can be created based on profiling and detailed real-time location information. Advertisers can target these viewers on a cost-per-impression basis at a far higher yield than otherwise, with real-time measurement in place, creating a win-win situation for both advertiser and video service provider.

Video Analytics - Identifying High Value Micro-Segments

Conclusion

Given the increasingly competitive landscape video service providers face, the challenge of device proliferation and rapid technology advancements, and ever-changing consumer behavior, it is no longer sufficient for executives to rely on traditional decision-making approaches. With more data available than ever before, video service providers stand to benefit from more advanced, sophisticated, and granular data analytics in order to better understand consumer behavior and improve business results.

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