The 21st century witnessed a revolution due to the arrival of the internet. The media and entertainment industries have always been in the frontline in this process. The way in which people used to entertain themselves has completely changed. Their preferences have shifted from cable TV to OTT (Over the Top) services which provide services according to their tastes and preferences. The entertainment and media industry is expected to grow at a 4.4 percent compound annual growth rate. The reason for this massive growth? Hyper-personalization. The hyper-personalization and niche market that OTT has created for itself has changed the working of the whole entertainment industry. Websites like Netflix, Amazon Prime, etc. have realized the importance of “data” generated by consumers in order to increase profits.
Quantzig, global data analytics and advisory firm reported that three trends would dominate the media and entertainment industry. Out of which emergence of data models occupied the third position.
History of Content and Viewership:
Before the Internet, people usually used to entertain themselves through Television which hosted various daily soaps, news, films on dedicated channels. The TRPs of these shows were then measured and based on that time slots were allocated to them (like day-time and prime-time). Prime-time was mostly allocated to the shows which had the highest TRP. People had to take out time during that specific time slot to watch that show and had to wait for either the next day in case of daily soaps or a week in case of weekly shows. The concepts which were in trend were repeated so that production houses can capture the maximum audience and profits.
The internet changed it all. The internet gave birth to the combustion engine of the 21st century i.e., Data. A huge amount of data is generated all over the world due to mobile phones, computers, and other devices. The arrival of streaming sites introduced a brand-new dimension of content to the consumers. The storylines were unique, unconventional, and bold which television failed to show. The web series explored various aspects of a complex human being and their faults which allured people more towards these streaming sites and resulted in mammoth success.
Personalization:
The secret behind the success of these OTT platforms (specifically Netflix and Amazon Prime) is content personalization. They managed to push the right content to the right people at the right time which was achieved through data analytics. These OTT platforms rely heavily on data analytics platforms and techniques to keep track of the activities of the consumers. The streaming cycles/preferences of the consumer are observed and tracked and based on those new recommendations are given to the customers. They come under the “You may also like this” section. Hence, it gives effective and personalized options to the consumers.
Data also induced production companies to produce content according to the preferences of the users. Data analytics provide insights regarding the content that the people are liking and accordingly, the company can design its strategy for further production of content. Thus, it helps in selecting a target audience. Netflix stated that while producing “House of Cards” they knew that the show is going to be a hit because data inspired the creative direction.
Data analytics can predict consumer behaviour in long term too. Jon Davis, director of EU music partnership at Shazam explained how data analytics helps the app to predict the playlist of popular songs two months in advance. Spotify creates playlists automatically according to the listening patterns of the consumers. Thus, predictive modelling helps media and streaming companies to anticipate consumer behaviour and predict what would be popular in the future. It also helps in identifying micro-segments of customers.
Advertisements can be one of the biggest sources of generating revenue for a streaming site. By understanding consumer preferences, behaviour, and activity across various platforms through data insights, hyper-personalized advertisements can be fed to them to which they can interact, thus increasing revenue for the service.
For Example – YouTube is known for attaching advertisements in the videos which are present on its platform according to the user’s search history, preferences, or activities on the Internet. Based on that, it generates revenue.
This hyper-personalization has facilitated consumers to get hooked on the streaming platforms and also create a value-added experience for them.
The Challenges:
There is no doubt that a massive amount of data has opened up enormous opportunities for the entertainment industry. But there exist some challenges that are hard to ignore. They are as follows: -
PRIVACY OF CONSUMERS:
Numerous instances of data leakage have been reported worldwide, which have made consumers sensitive about their data and how it is being used. This causes a lack of collection of data which causes discrepancies in analysis.
To tackle these issues, regulations have been placed on companies that broker personal data to media houses.
FINANCES:
One of the biggest challenges related to data analytics especially in media start-ups and SMEs is the lack of infrastructure that can interpret data due to limited finances. While accounting costs for implementation of data analytics, companies needed to look out for various factors like data storage, processing, and human resource costs.
But with the advent of SaaS and cloud storage solutions, this problem seems to be resolved.
HUMAN RESOURCE:
More data existent has raised the demand of data scientists all over the corporates. But there is a significant imbalance between the demand and supply of data scientists. That is the reason why the salaries of data scientists are skyrocketing these days and the media industry is the biggest victim of this.
The Future of Data Analytics in Media and Entertainment
Art and Science were always seen as two different domains citing different meanings and opinions about the world. But the usage of data analytics, Artificial Intelligence, and Machine Learning (ML) techniques have bridged this gap. The whole entertainment industry has begun drawing insights from it.
Earlier, only OTT players used to be concerned about data that is circulating but with time directors and producers of movies that air at cinemas realized that tracking historical data and using analytics can act as a full-proof plan for making their newer projects successful. With hundreds of millions or a billion dollars invested in a single project, it becomes quite crucial to make them successful and that success depends on the audience.
Researchers say that this new science has arrived and is here to say. The future, of many industries including the media and entertainment industry, depends on it. As this blend of art and science continues, it requires a lot more interconnection so that the outcome achieved is smooth and desirable.
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