How Big Data Analytics Is Changing the Media Industry

Oct 5, 2020   |   By Veronica Horner

From content personalization to omnichannel strategies, big data analytics is transforming the media and entertainment industry.

In the past decade or so, big data has radically altered the landscape of the media & entertainment industry. The sheer volume of data alone has exploded since the early 2000s, enabling media companies to tap into data from digital channels to gain valuable insights into audience behavior and gain a competitive edge. 

Then came the era of big tech, dominated by the likes of Google and Facebook. Alongside this boom came improvements in data collection, trading, and analysis, which helped accelerated the adoption of new technologies, shaped business strategies, and changed how organizations think about customer engagement. 

Today, big data analytics is changing in response to new data privacy laws like the Global Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). But data remains the key driver of how media & entertainment organizations create value through audience engagement. 

Here are a few important ways that big data has transformed how media & entertainment companies operate — and why data will continue to serve as a key component to ensuring sustainable organizational growth. 

Driving Consumer and Audience Insights

Advertisers, publishers, and media companies rely on data to increase engagement with their product or brand. Over the last ten years, companies have come to rely on user data to segment audiences. By regularly analyzing search engine data alongside internal sales data, media companies have been able to take a detailed look at audience behavior and preferences. Big data analytics provides insights into who their audiences are, how and when they engage with media and products, and how crucial factors such as geography and time of day influence user behavior.

By leveraging their data resources, companies can conduct robust online testing to drive strategy in areas such as content planning and paid advertising. A refined data strategy helps create opportunities to influence direct purchases, monetize content, and build ongoing relationships with consumers. By segmenting audiences and targeting who they would like to reach, media companies can tailor content across different platforms in order to influence consumer behavior. 

But beyond leveraging data assets to gain insights into their audience and their audience’s behaviors, big data also enables media & entertainment companies to coordinate more effectively across multiple channels. Media companies now rely on a complex combination of print, word-of-mouth, and digital platforms including search engines and social media to drive audience engagement. 

Real-Time and Predictive Analytics 

As content cycles became shorter, real-time analytics have also become vital to gaining, or retaining, a competitive edge for media & entertainment organizations. Real-time analytics often have a direct impact on audience engagement by enabling content providers and advertisers to adapt quickly. Companies can produce content — across multiple media channels — that is tailored to specific audience behaviors, which creates greater opportunities to capture user attention.

In addition to seeking quick insights, today’s media & entertainment companies are turning their gaze to predictive analytics and machine learning to anticipate future user behavior and adapt long-term business strategies. Predictive analytics can now determine what time of day users are more likely to engage, and whether a campaign through social media will be more effective, or whether targeted ads would yield better results.  

The French publisher Editalis, for instance, deployed a predictive model to anticipate individual engagement in email campaigns. As a result, the organization was able to adapt its content and improve click-through rates dramatically. By using predictive analytics to model future audience behavior, organizations can plan content more effectively, strategize about how to bring the right product to market at the right time, and reach audiences when and where it matters. 

Personalized Content and UX

As data use becomes more sophisticated, personalization will be the determining component for future success. Media companies can rely on data not only to help them deploy effective personalized and targeted ads, but also to optimize user experience and anticipate user needs. 

Media & entertainment companies that invest in robust data infrastructures and strategies can leverage sophisticated algorithms to tailor user experience (UX) down to minute details. UX designers can tailor separate content for existing customers and new customers — or further in accordance with individual user preferences.

Consider that streaming giants such as Netflix and YouTube now curate the user’s homepage based on their previous activities, using AI to make recommendations based on factors like the type and length of content with which the user in question is likely to engage. According to a study by TiVo, streaming providers who implemented technology solutions that helped them personalize their content saw a 140% increase in audience retention over six months. 

As machine learning capabilities expand, organizations gain access to more sophisticated and more effective means of personalization. Connected devices, like virtual assistants and wearable technologies, are becoming ever-more attuned to a range of different user emotions — and how these emotions impact decision-making. To take a popular example, Amazon’s Alexa is now three times more accurate at determining user emotions than its previous algorithms. To offer users a more intuitive voice experience, Alexa can now respond to questions and requests with a range of emotional tones, depending on the situation.  

Increasingly sophisticated algorithms can predict how audiences are likely to respond depending on how they feel. This holds enormous potential for companies looking to gauge audience response to content. It also enables media outlets and entertainment platforms to create content that responds to changes in perception or correlate with changes in mood. 

The future of Data Transformation 

Concerns about data privacy have risen in tandem with innovations in big data analytics. The regulatory landscape continues to evolve and compliance has become a high priority for media & entertainment companies. Achieving compliance while maintaining customer trust and protecting the bottom line will require organizations not only to invest in the right technologies and capabilities, but also in robust data governance programs that protect against fines and costly audits. In addition to personalization capabilities and real-time analytics, compliance will be an indispensable consideration for companies looking to build their brand and maintain their reputation.

The “era of big data” may still be evolving, but big data analytics will continue to drive strategy for many businesses. Media & entertainment organizations can position themselves for success by leveraging advancements in personalization capabilities and creating an impact through omnichannel engagements. By making the right infrastructural investments and aligning strategy with technical expertise, companies can stay ahead of the competition even as policies change and disruptive innovations emerge. 

Organizations of all kinds can maximize the impact of big data analytics with the help of an expert consultancy. At SEI, we have over three decades of experience in implementing effective data & analytics and information security solutions that drive measurable results. Our consultants engrain themselves into clients’ cultures, organizational structures, and objectives in order to provide comprehensive support that aligns with the organization’s unique goals and requirements. Using this collaborative approach, we pair custom-made strategies with best-fit technological solutions that empower organizations to achieve more. 

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