Finding the sustainability balance with personalised video streaming

As the expansion of personalised video streaming continues apace, JUMPs CEO and co-founder, Jer nimo Macan s and Fran ois Polarczyk, sustainability director at Accedo, consider how it can be balanced against the need for sustainability

By Contributor

Published: May 30, 2024

As the expansion of personalised video streaming continues apace, JUMP's CEO and co-founder, Jer nimo Macan s and Fran ois Polarczyk, sustainability director at Accedo, consider how it can be balanced against the need for sustainability

target=_blank title=Share on LinkedIn class=share-linkedin> As the expansion of personalised video streaming continues apace, JUMP's CEO and co-founder, Jer nimo Macan s and Fran ois Polarczyk, sustainability director at Accedo, consider how it can be balanced against the need for sustainability

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The video streaming industry is facing mounting competition and a decline in consumer spending on subscription services. To counteract these challenges, broadcasters and media companies are increasingly turning to personalisation to enhance user engagement, retention, and reduce churn.

Personalised video services naturally help consumers navigate extensive content libraries more efficiently, leading to improved satisfaction and loyalty. However, this approach also increases the processing demands, negatively affecting a service's environmental impact.

In a world where sustainability is an increasingly critical concern, how can we balance the need for personalisation with the imperative to operate sustainably?

The environmental impact of personalisation in OTT Personalising video streaming services involves the use of sophisticated algorithms and extensive data processing to analyse user preferences and viewing habits. This level of personalisation requires significant computational power, which in turn leads to increased energy consumption and a larger carbon footprint. The infrastructure supporting these operations, often hosted by cloud vendors, demands substantial electricity. For instance, the data centres running these services consume vast amounts of energy, contributing to the overall environmental impact.

While leading cloud vendors like Google Cloud are developing tools to help reduce energy consumption, the challenge remains significant. Personalisation solutions are necessary to help users navigate growing video catalogues efficiently, potentially reducing the time spent searching for content and surfacing content they might not find on their own. However, all this data processing happens online, meaning energy consumption is inevitable.

Strategies for reducing environmental impact Video service providers can adopt several strategies to minimise their environmental footprint while still offering personalised experiences:

Optimising Existing Technologies: Revisiting and optimising older personalisation technologies can significantly reduce energy usage. By refining these technologies, companies can maintain the effectiveness of their personalisation efforts without excessive energy consumption.

Leveraging Cloud-Based Solutions: Transitioning to cloud-based personalisation technologies can optimise computing needs. Cloud providers like Google Cloud continuously develop technologies to enhance efficiency and reduce energy consumption. Cloud-native personalisation technology often consumes fewer resources than traditional hosting-based or hybrid solutions.

Hybrid Recommendation Systems: Employing smart hybrid recommendation systems that combine collaborative filtering, content-based filtering, and generative AI can reduce the computational load. These systems can provide effective personalisation with less energy consumption.

Content Caching: Prioritising the caching of popular content closer to users can decrease the frequency and intensity of personalised processing. By storing frequently accessed content locally, companies can reduce the need for continuous data processing.

Balancing personalisation and sustainability Achieving a balance between personalisation and sustainability is both possible and necessary. One effective strategy is to set thresholds for when and how deeply to personalise content, maintaining high user satisfaction without excessive energy use. Additionally, focusing on the development of efficient AI algorithms can help. While training AI models is energy-intensive, optimising these models to deliver high personalisation with less computational overhead can significantly reduce environmental impact.

AI can also dynamically adjust content delivery methods based on real-time data, enhancing sustainability. For instance, AI tools can identify speech and screen time among certain age or gender groups, providing media organisations with insights to assess and share the variety of their content based on these key performance indicators (KPIs).

Social considerations and future directions Beyond environmental concerns, there are social implications to consider in streaming personalisation. Over-personalisation can create echo chambers, limiting users' exposure to diverse content and viewpoints. This has broader implications for cultural consumption and social cohesion. The industry must ensure that personalisation algorithms encourage a healthy variety of content, fostering a well-rounded viewing experience.

Leveraging the vast amounts of data related to content can also push for more sustainable content or display sustainability criteria (such as gender representation or sustainable production data) when searching for content. This approach can help promote local productions or content that supports positive impact behaviours, which could be important for certain viewers.

Ultimately, i

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