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10 Big Data Applications and Use Cases in Media and Entertainment Industry

The tremendous amount of data generated in the media and entertainment industry is ideal for real-time analytics of the audience’s interest areas and empowering media companies to leverage that interest.

For instance, insights into content visibility explicate how the audience is often confronted with the paradox of choice and frustrated or bored with repetitive storylines being pushed across channels.

That makes it imperative to understand how the media and entertainment industry can bolster audience engagement using big data.

Top Uses of Big Data in the Media and Entertainment Industry

Big Data can help the Media and entertainment industry understand what type of content the audience wants to consume and how. For instance, they can get real-time insights into customer churn rate, the ideal time for scheduling a particular program, and how effective Ad targeting can fetch good results.

To that end, here are the four prominent areas where big data makes a difference in the media and entertainment industry.

  1. Predicting what the audience wants
  2. Optimizing and monetizing the content
  3. Running targeted advertisements for desired results
  4. Understanding customer disengagement

Before we get into the nitty-gritty of big data applications, here’s how popular media companies like Netflix, Spotify, and Amazon Prime use big data to their advantage.

  • Netflix: Netflix currently boasts more than 220.67 million paid subscribers globally and is the number one OTT (over-the-top) content streaming platform. Reason for this success? Big data analytics. With big data analytics, Netflix offers its audience personalized media recommendations and predicts whether a particular form of content will cater to the targeted audience.
  • Spotify: People’s favorite music app uses big data to determine what type of music or songs a particular age group will like. Spotify boasts about 20 million songs in its data repository, with 20,000 new songs added daily. As such, Spotify uses big data to offer personalized music recommendations based on the audience’s music preferences.

Let’s now take a look at the top 10 big data applications for the media and entertainment industry and how they have changed the industry.

The 10 Big Data Applications and Use Cases in Media and Entertainment Industry

Here are the top big data applications and use cases for the media and entertainment industry.

1. Consumer Expectations

The media and entertainment industry can deliver highly localized and area-specific content with the help of big data analytics. In an era where consumers expect customized content and recommendations, big data analytics can drive hyper-personalization and hyper-awareness of industry trends and consumer preferences.

2. Targeted Offers to Attract Customers

As the customers’ behavior insights come to the fore, media companies, through targeted programming, can increase their customer base and retain the existing one. For instance, big data can help attract new customers by presenting schemes on paid memberships for a specific period.

3. Optimized Content Scheduling

Big data analytics can help media companies schedule content at the right time when their audience is active and engaged. This can lead to a huge increase in viewership, subscribers, and greater revenue. The concept of time alignment is ideal for targeting a specific market segment.

4. Analyzing Social Media Sentiments

Today, audiences have loads of opportunities to demonstrate their amusement, displeasure, or discontentment with the content showcased. Media companies can collect this data, analyze the audience’s sentiments toward certain shows, and take the necessary action.

5. Audience Churn Reduction

Audience churn is often a result of poor content and engagement. Sometimes the content is boring and irrelevant to the targeted audience, and sometimes, there are no offers to keep the audience hooked for long. Media and entertainment companies can analyze their audience’s data and find out why they are disengaged with the company’s platform. If a large chunk of the audience is uninterested in specific types of programs or is unimpressed with content, media companies can enhance the same to attract viewers back.

6. Recommendation Engines

As elucidated in Spotify’s case above, big data analytics can help media companies personalize content for audiences. Working on the principle of finding patterns in consumers’ behavior realized either implicitly or explicitly, recommendation engines use machine learning algorithms and recommend the most relevant content to the consumer.

7. Targeted Advertisements

With the help of big data analytics, media companies can showcase targeted commercials to their audience. For instance, if a media company finds that a particular product is more relevant to its female audience and people in the 25-35 age group, it will run targeted advertisements for the same. This can improve the company’s ad revenue per customer.

8. Product Development & New Revenue Sources

Often, media and entertainment companies are inclined toward offering additional products and services to their customers to incentivize consumer behavior and enhance their experience. However, if the products are not developed keeping in mind the existing audience, this can backfire. Big data analytics can help media companies prepare product roadmaps based on the audience’s preferences.

9. Financial Data Analysis

For strategic allocation and distribution of resources, the media and entertainment companies need to evaluate data from financial transactions. Big data analytics can help them analyze financial transactions, including revenue, cost of goods, and expenses for a particular period. This allows them to make strategic decisions and undertake future business operations.

10. Brand Management

Big data analytics can help the media and entertainment businesses in better brand management through multiple forms of digital communication channels like mobile, website, apps, etc. This can allow them to build a solid digital identity and rapport with the target audience.

In a Nutshell

Optimizing and monetizing content is the biggest determinant of success for media and entertainment companies. The use of big data analytics can help them ensure that the content is relevant, engaging, and entertaining. It offers a ton of insights – from financial performance to consumer behavior, customer preferences, and anticipated needs.

At Ascentt, we help media and entertainment companies make strategic decisions for optimizing content, refining advertising, and increasing customer satisfaction using the power of analytics.

Connect with our experts to know how big data analytics can help you take your business to the next level.

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