5 Ways Big Data Plays a Major Role in the Media and Entertainment Industry

Deliver a personal experience is the ultimate motive of any entertainment and media company.


With smartphones and associated digital media becoming the major source of entertainment, media creators and distributors must embrace Big Data Analytics to create a connection with their customers.


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It will help unlock hidden insights about customer behaviour and facilitate achieving the ultimate goal – delivering personalized content.

According to CloudTweaks, Facebook collects and processes 500 TB of data daily. Google processes 3.5 Billion requests daily. Amazon receives 152 Million customer purchase data daily.

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Hence proved, that data volumes are skyrocketing on a daily basis. Big Data is too big to ignore.

If harnessed, it can be used as a massive force for boosting your business. For forward-thinking media and entertainment companies, Big Data holds the key to future business profitability.

Who can Gain Big from Big Data?

Almost every media associated business with large volumes of data can leverage Big Data to its benefit. The largest benefactors of Big Data in the media and entertainment industry will be:

Video Publishers

Independent or private video creators who publish content including video, audio, text and images.

Media Owners

Businesses that own copyright to sell content that can be sold through retail or mass content distribution mediums.

Gaming Companies

Online or offline video game makers that can log gamer reactions for fine tuning gaming experience.

TV Channels

Television channels that broadcast owned or purchased video content to a mass population.


In this article, we explore the several ways how Big Data is helping entertainment and media industry make sense of the massive flood of data that gushes in from multiple sources.

1. Predicts Audience Interests

Traditionally media content was served only in limited forms. Today, they are replaced by myriad media services like pay per view, on demand, live streaming and much more.

In the process of content delivery across these forms, broadcasters also collect a vast amount of user data which can give in depth understanding of behaviour and preferences.

According to the statistics compiled by YouTube, it has been found that YouTube’s lion share of viewers is audience falling in the age group of 18 to 34 years.

YouTube has also unearthed several other interesting statistics about its users like what kind of videos viewers watch the most, what devices are used for video streaming, how long each video was watched and much more.

How did YouTube know so much about its users in such a minute manner? It is Big Data and Analytics that is at play. Big Data throws deep insights into YouTube’s audience behaviour and helps it to syndicate content that is closely aligned to their viewer preferences.

2. Insights into Customer Churn

Customer churn is a serious menace that media companies find almost impossible to tackle. It has been found at least 30% of customers share their reviews through social media. Until Big Data arrived, combining and making sense of all the user data from multiple sources, including social media was next to impossibility.

With the advent of Big Data, it is now possible to know why customers subscribe and unsubscribe. It is possible to know what kind of programs they like and dislike with crystal clear clarity.

Deeper insights into responses towards pricing and subscription models can also be drawn with Big Data. Through Big Data Analytics; content pricing, media content and even delivery modes can be tailor made to reduced customer churn.

3. Optimized Scheduling of Media Streams

The rapid growth of digital media distribution platforms has literally torn down the barrier that existed between end users and distributors. Reaching the end-users directly without any intermediary is feasible than ever before.

Moreover, social networks have also set the stage for creating individual connections with viewers unlike in the past where mass distribution of media was the norm. Connecting with audience directly through scheduled media streaming can maximize revenues for media companies.

Business models like on-demand and scheduled viewing can also be mastered through Big Data enabled customer behaviour analytics. Big Data Analytics help identify the exact content which customers would want to engage with on a schedule basis.

4. Content Monetization

Big Data is helping media companies create new revenue sources. It arms media owners’ new avenues to capitalize on the media interests of customers. Let’s examine the success story of The Weather Channel:

The Weather Channel (TWC) is a privately owned weather business co-owned by IBM. TWC uses Big Data to observe and understand customer behaviour in specific weather conditions.

With the help of Big Data, TWC has fabricated a WeatherFX marketplace where sellers can advertise their products that have higher chances of selling in a given weather scenario. Presently, TWC is estimated to earn at least half of its advertising revenue with the help of Big Data analytics.

Thanks to mobile profusion and bandwidth expansion, now it is possible to reach out to a larger chunk of digitally connected audience for content monetization. Big Data facilitates zeroing in on the right content that such audience will prefer.

5. Effective Ad Targeting

The revenue models of media and advertising is largely dependent on programmatic advertising. All these years, programmatic advertising has been done on a random manner, with the hope that customers will like what is shown to them.

Big Data takes the guesswork out of programmatic advertising. It helps advertisers and businesses pinpoint the exact preferences of customers. It also gives a better understanding about what type of content viewers watch at what time and duration.

This granular visibility of customer preferences helps improve the efficiency of ad targeting resulting in higher conversion rates or TRP as the case may be.

Furthermore, in a live streaming scenario, Big Data also helps advertisers to tweak their broadcasts real-time to deliver a far enriched and personalized media experience.

The ‘Big’ Road Ahead

Big Data can open up the lane to fast success to businesses in the entertainment and media industry. It can help negate the biggest risk factor in the industry – changing customer behaviour.

Big Data can help have a steady pulse on the shifting customer preferences. It helps reduce customer churn, creates alternate revenue channels and also boosts customer acquisition and retention through data intelligence.

In the end, it creates a new ecosystem where customer experience is put as the centrepiece. After all, the entire entertainment and media industry thrives on the end-user experience that it creates.

More Great AIM Stories

Sunu Philips
Sunu Philip is the Inbound Marketing Head of Cabot Technology Solutions – an IT consulting firm specialized in web and mobile technology solutions. Cabot offers progressive end-to-end business solutions, blending a solid business domain experience, technical expertise and a quality-driven delivery model.

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