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The four key elements of delivering User-Driven TV

Make sure you always deliver a 5-star service by implementing a User-Driven TV policy and leveraging data technologies that always put viewers first.

user driven tvIn today's ultra-competitive streaming landscape, personal profiles and content recommendations alone are no longer enough to satisfy viewers. With mounting expectations and evolving preferences, broadcasters and service providers face the challenge of delivering exceptional viewing experiences. 

But within a challenge lies an opportunity. For with the extensive data, experience, methodology, and technologies at our disposal today, there lies an opportunity to embrace a user-driven approach, which utilizes a combination of four elements and a single, mutual goal: Putting viewers first.   

The four elements

Our approach to User-Driven TV is based on four main elements: mapping the users DNA; addressing the viewer with personalized content offerings, promotions, and advertising; using viewership analytics and behavioral patterns to detect low viewer satisfaction and ensure an outstanding quality of experience (QoE); and lastly, monitoring the availability of the service and applying predictive algorithms to prevent issues in advance, ensuring premium quality of service (QoS) anytime, anywhere, and on any device. 

Let’s look though these in turn.

1. Mapping User DNA


 

In order to gain enhanced visibility into the performance of content offerings and subscriptions, we use data collected from multiple sources within the video chain, which provide us with invaluable insights into viewers' behaviors and helps with the identification of sometimes hidden content usage patterns.

Utilizing our extensive partners ecosystem, we have also incorporated a semantic video content algorithm from Spideo, which incorporates humanized and supervised semantics to improve content discovery algorithms. This enables content owners and service providers to extract maximum value from first-party semantic data and affinity segments across various business models, including subscription-based, ad-based, and hybrid models.

2. Simplifying Monetization with Targeted TV Advertising

Being user-driven doesn’t end with personalized content, and offering personalized advertising is a win-win practice which serves the interests of both the service providers – and its end users, as viewers have been shown to respond more favorably to targeted ads. An important pillar for content monetization, Targeted TV Advertising relies on attaining valuable, in-depth insights into viewer behaviors and preferences. 

To maximize the potential of this solution, you need a full-stack programmatic infrastructure with advanced data segmentation capabilities, which will allow you to translate viewers usage data into accurate, highly valuable audience segments for advertisers.  

I am proud to share that VO is an industry pioneer in this aspect, providing a dynamic segmentation model that ensures effective advertising and hyper personalized viewing experiences, allowing service providers to increase the number of ad slots without increasing ad load or charging premium rates. 

The fusion of User DNA with ad-based monetization mechanisms forms a self-sustaining cycle that enhances user exposure, leading to superior content discoverability. 

This process can also be harnessed for internal promotions, using the existing targeted advertising tools. As user exposure expands, more ads are shown, generating an increased amount of user data and, in turn, resulting in enhanced targeting and discovery.

 

3. Optimizing User Experiences

Another key element in being user-centric is maximizing user satisfaction. By closely monitoring QoE and integrating it with viewership data, valuable insights can be gained to identify potential anomalies in viewersexperience that might leave them in danger of churn. 

Various indicators can be analyzed, such as a decrease in content consumption, a higher frequency of video issues, or excessive time spent within the application compared to content viewing. These comprehensive metrics offer an all-encompassing perspective on viewer engagement and satisfaction. 

By recognizing these patterns and behaviors, content owners and service providers can actively resolve any issues that might hinder viewer retention, thereby promoting continuous viewer loyalty and engagement. 

This proactive approach allows for targeted interventions, such as tailored promotions to effectively re-engage viewers and enhance viewer retention.

 

4. Securing a Consistently Robust Service

Last but not least, let’s talk about quality of service. After all, what good is a viewing experience if it’s interrupted or inconsistent? 

A prerequisite criterion, sure, yet by monitoring the various components of the video delivery chain and optimizing their quality there is still much to be done in this field. 

If we monitor the device, the video quality, the overall service stability, and also inspect all other system components across the delivery chain, we can proactively prevent backend failures.

Leveraging AIOps and, in particular, predictive analytics, an AI-based bandwidth prediction algorithm can calculate changes in available bandwidth based on environmental factors and predict the occurrence of a drastic change in available bandwidth on an end users video player. By anticipating changes in network quality, the video player can then adjust video rendering to improve QoE for viewers and prevent ultimately backend failures.

Moreover, using advanced data analysis alongside behavioral pattern analytics, we can identify weak signals through event correlation, anomaly detection and to ultimately ensure the provision of premium level of service anytime, anywhere, and on any device.

From a viewer's point of view: Adopting a viewer-centric approach

 

To secure viewer loyalty in today’s landscape, broadcasters and operators must cater to individual preferences with tailored content discovery, promotions, and advertising; They also need to be agile, embrace innovative business models and seize new monetization opportunities so they can diversify their revenue streams, and adeptly provide for evolving viewer preferences and the mounting expectations of audiences.

Adopting a user-driven approach, powered by advanced data tools, marks a transformative advancement in the video and TV industry; one that equips content owners and service providers with the tools to ensure viewer satisfaction and outpace competitors. And as competition for viewers increases, it is the companies that provide fully user-centric, unparalleled experiences that will benefit the most from enhanced revenue generation opportunities in the future.

Hadar Tel Mizrahi

Hadar Tel Mizrahi is leading Product Manager in the personalization and recommendation domain at VO. She first started at the company as a software developer working in DRM products and TV Platform integrations, before becoming QA Team Leader and then turning her attention to content recommendation and personalisation. She holds Bachelor's degrees from Tel Aviv University in both Law and Economics