Entertainment industry makes a killing using Data Science!!

Few industries are seeing as big a surge in demand for data scientists as the entertainment industry. Although largely known for its art, the entertainment industry has placed great emphasis on its science in recent years. With streaming services, production studios, and legacy media companies collecting troves of data on production trends, users’ viewing habits, and post-production planning, data scientists hold the key to helping organizations make sense of the wealth of information they’ve gathered. It’s a role that requires equal parts technical skill, analytical acumen, and creativity—a love for movies and television also doesn’t hurt!

How is data science used in the entertainment industry?

At a surface level, data science insights can help entertainment companies with forecasting, operations research, topic modeling, user segmentation, and content recommendations. Streaming services such as Amazon and Netflix, for example, rely on data to determine what shows are greenlit and promoted. “You do not make a $100 million investment these days without an awful lot of analytics,” Dave Hastings, Netflix’s director of product analytics, said at the Wharton Customer Analytics Initiative Conference in 2015. Meanwhile, over at 20th Century Fox, data scientists have used AI to analyze movie trailers in order to determine what audiences might like. In the years since, the role of data science in entertainment has only grown.

Going deeper, data scientists can help entertainment companies optimize their decision-making by offering solutions rooted in data in place of the traditional approach of relying on human experience and intuition. For example, Netflix'x data analytics division has helped the organization with business and technical decisions such as planning budgets, finding locations, building sets, and scheduling actors. Netflix’s data scientists have also created models that allow production executives to make critical decisions using data-centric ‘what-if’ scenarios, rather than relying on their best guesses.  

Entertainment industry data scientist job roles/responsibilities

Most data scientists bring to the table technical skills such as knowledge of probability and statistics, data visualization, machine learning and AI, and proficiency with Python and SQL. And while these skills might help a person parse through troves of information, the entertainment industry expects its data scientists to also approach data sets with creativity, and be able to effectively communicate findings to those who don’t have technical backgrounds.

“Learning what is a valuable problem to solve, how to ask good questions with data, and solve problems creatively are similar and adjacent skills,” said Alyssa Zeisler, Research and Development Chief and Senior Product Manager, Editorial Tools, at the Wall Street Journal.

In other words, a large part of a data scientist’s job is to connect relevant dots to tell a story and persuade those in charge that the insights are meaningful and worth acting on.

Other common responsibilities of entertainment industry data scientists include:

• Using data and machine learning to build recommendation engines
• Defining performance and success metrics
• Developing and communicating recommendations rooted in data to non-technical members of the organization
• Designing and developing algorithms and statistical models and machine learning pipelines
• Analyzing behavioral data and identifying opportunities for growth

Some Use Cases in Media and Entertainment industry are:

1. Personalized marketing

The attraction of customers’ attention is a crucial prerogative of any company, primarily when it is involved in media and entertainment business. When quick and impressive online experience became very familiar for many people, it is even more challenging to retain the attention of the customer gained.

2. Customer sentiment analysis

All the media and entertainment companies seek to distinguish how the visitors feel about their content, web page, or web apps. This knowledge gives a prospect to adjust to the viewer's taste. For this purpose, customer sentiment analysis is widely applied.

3. Real-time analytics

Real-time analytics, by its very name, provides the data processing presenting the output in the extremely short periods of time. As far as, media and entertainment enterprises possess a vast amount of data provided by the customer with their every click, the speed of its analysis is a valuable factor.

4. Recommendation engines

Recommendation engines give the entertainment and media providers a chance to focus on the users’ desires and feelings. Besides the history of a user within one company, a provider pays exceptional attention to the sensations related to this user.

5. Content distribution on social media

The modern world of social networking offered the media and entertainment providers a fabulous chance to enforce their marketing strategies with a powerful tool of social media content distribution. General tendencies, users’ behavior, preferences, experience, interests, and histories are now available in one click for huge media enterprises.

6. Analysis of media content usage

Since the appearance of the worldwide network, its popularity is continuously growing. It has become a universal platform for business, social life, entertainment, and leisure. Every day millions of people all over the world leave their fingertips in the network. These are their clicks, likes, posts, reposts, comments, shares or views. Ignoring such valuable information would be a significant loss, especially when it concerns the media content and its direct impact on the audience.

Conclusions

Data science is employed in many spheres of human life. The value of the algorithms and their efficiency can hardly be underestimated. The use of data science in the field of media and entertainment has become an art.

It is no longer enough just to spread news, rumors or offer entertaining activities. A company should reach the interaction with a customer, evoke feelings and emotions and make a desirable impact. The ability of data science to collect, process, analyze, store, provide recommendations is a huge benefit for the media and the entertainers.