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Home Data Science

Top 9 Data Science Use Cases in Media and Entertainment

January 6, 2019
in Data Science
Top 9 Data Science Use Cases in Media and Entertainment
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Big players in the media and entertainment market every day face new challenges of the digital reality. The customers tend to search for the service that may be available at any time and any place regardless of the circumstances. This sphere becomes more and more competitive every day.

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Modern trends in the application of data science in various aspects of everyday life establish new rules and require extra creative thinking from media and entertainment holders. Big data may be used for many goals varying from rising the profit to improving views and comments. The benefit of data science application is evident for big broadcasting or gaming enterprises, the media, etc. In this very way, they make their data work for them. In the case of media and entertainment, considerable attention is paid to the audience. Thus there is a direct dependency between the customer’s choice and the company’s action.

In this article, we would like to familiarize you with the most vivid and remarkable data science use cases in media and entertainment.

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.

At this point, personalized marketing algorithms come to rescue the big media empires. These algorithms mainly spread their operational potential to four dimensions. First of all, the algorithm is capable of recognizing new and old customers and dragging out useful information from them in real-time mode. Also, the algorithm may perform a cross-channel tracking of both familiar and unfamiliar visitors. Personalized offers and messages are tailored according to the behavioral insights and personal data gained. At last, all this personal data is used to promote the media content among the customers’ groups which may prove to be the most responsive and influential.

Personalized marketing strategies allow tailoring of the general website content to the taste of any visitor.

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.

Customer sentiment analysis algorithms lie within measuring positive and negative language manifestations. In this case, natural language processing guarantees the analysis of textual conversations. The algorithms are capable to classify the posts, messages, conversation fragments by the sentiment they express defining the emotions hidden behind the context.

Modern tools used for customer sentiment analysis can distinguish between six emotional states as defined by Paul Ekman. Thus, the customer’s sentiment may not only be classified as positive or negative but also provide more concrete information. In this way media and entertainment companies can increase positive mentions of their names, to create a positive image and develop relevant content.   

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.

Real-time analytics algorithms provide the output extremely fast. Therefore, crucial decisions and improvements to the content may be carried out immediately. Utilizing real-time analytics gives the company more chances to win the race with the competitors.

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.

Modern recommendation engines use matching algorithms processing the data and attach tags to the words bearing emotional attitude as well as matching previously mentioned or searched items. On this basis, accurate, relevant and appealing recommendations and suggestions are made.

The providers are eager to develop a content bearing the emotional attachment to a viewer. Thus, the appropriate content would reach the right viewers at the correct time.

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.

Content distribution largely depends on analysis of the social media statistics. Specially developed tools allow identifying the target readers, the most effective channels and even when the user will be the most responsive to the message. These actions become possible due to sophisticated algorithms spotting coincidences and matching them to the users’ needs. The synergy with a user via social network proves to be extremely efficient in the promotion of the media and entertainment outcomes. As far as, social life goes hand in hand with entertainment, news feed, gossiping, cinema, gaming, etc. Successful content distribution strategy is well organized, prepared, targeted, relevant, flexible and gradual.

Object detection and classification

The internet encompasses loads of information, and these vast amounts are continually growing. It hosts thousands of website and platforms dedicated to media and entertainment containing links, posts, video and audio files, films, games, and applications, etc. This fact may cause some difficulties in the search.

Object detection and classification algorithms help to filter, match, classify data, recognize images, make link-building. Thus, the adds of an appropriate or irrelevant product will not appear on your way. Lot of inconveniences and misunderstanding may be avoided. As a result, media or entertainment provider ensures a good content, attracts and retains users and promotes its services.

Collecting and analyzing customer insights

A general tendency of data science application brought numerous benefits to people in business all over the world. The algorithms help to collect and analyze the consumer insights and make use of the output.

In relation to areas of media and entertainment all the comments, post, likes and dislikes, views, subscription, etc. present a vast ground for extracting the insights. The algorithms process the data, filter, classify and group the coincidences, obtain the most valuable pieces and draw conclusions allowing the media and entertainment companies to know their customers better. Predicting the customers’ reaction and attitude, future profits, planning and building successful marketing policies – all these become a reality due to the insights.

Leveraging mobile and social media content

Mobile and social media content is considered to be a fundamental to assure interaction between the company and the customer. Reports, passionate discussions of posts, likes and shares are all the media and entertainment companies hunt for.

First of all, leveraging mobile and social media content increases the number of channels and the amount of data exchanged in real-time. In its turn, the data provide enhanced targeting capabilities. In other words, having the insights of viewers the media and entertainment companies tailor offers and recommendations to suit the needs of very targeted audience group. Secondly, adopting the mobile content makes the companies’ services more available and easy to reach. Text mining, speech and image recognition and sentiment analysis prove to be very useful in this case.

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.

Thanks to the data science algorithms big media enterprises can make data work and bring profit. Media content analysis is a well-developed methodology aiming at analyzing the message of the content and its connotation. The process of the media content analysis consists of three major levels: capture, understand, present. The algorithms track the patterns and coincidences in the text. After that, the data is prepared for processing. The frameworks define the sentiment of the text. Thus its influence on the user may be predicted.

According to the output, the message of the text may be modified, or a general tendency of the content may be defined.

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. 


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