Big data analytics has become a game-changer in most, if not all, types of modern industries over the last few years. Some of the key big data applications for modern companies include enhancing customer experience, achieving cost reduction, better-targeted marketing, and improving existing processes. Several recent data breach incidents have also made enhanced security an important goal for big data analytics to accomplish.
Big Data Analytics in the Media and Entertainment Industry
Media and entertainment companies are shifting to a content-centric model in order to embrace a customer-centric world. The ultimate aim of companies in the sector is to reduce customer churn by delivering top-notch customer experience. With smartphones and associated digital media becoming the major source of entertainment, it is high time for media companies to leverage big data analytics to create a connection with their customers. However, the ability to access, analyze, and manage large volumes of data while rapidly evolving the information architecture is becoming increasingly critical for companies in the media and entertainment industry who are determined to improve business efficiency and performance. Furthermore, media companies often face the challenge of correctly identifying why some customers subscribe and unsubscribe to their content or services. Media companies also face difficulty when it comes to analyzing why and how customers react to pricing and subscription models. Big data analytics can enable a better understanding of the consumer as the content is created to ensure success.
Analyzing large data sets is one of the biggest problems affecting the business outcomes of media companies today! Get in touch with our industry experts to know how big data analytics can help you gain a leading edge.
Big Data Applications in the Media Industry
The future of the media and entertainment industry is largely dependent on the amalgamation of both digital and big data analytics solutions. The rapidly rising digital consumerism offers a plethora of opportunities for media and entertainment companies to leverage big data analytics for better customer engagement. Below are a few examples of how media companies can benefit from big data analytics:
Predict What Audiences Want
One of the primary big data analytics applications in media companies is to understand what the target audience wants. The amount of data that media companies gather gives them ample opportunities to leverage big data analytics capabilities to understand the demand of the genre of shows, music, content for a given age group on various different channels.
Big data analytics gives companies in the media and analytics industry a better understanding of the digital media and the consumption behavior of users across various platforms. By using traditional demographic data, companies can personalize advertisements to suit the needs of specific users. Using big data analytics and offering micro-segmentation of customers to their advertising networks and exchanges, media and entertainment companies can also increase digital conversion rates.
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Content Monetization and Product Development
One of the key big data analytics applications in the media industry is that it helps in additional revenue generation for media and entertainment companies. Accurate data gives companies the ability to incentivize consumer behavior and, in the process, reveals the true market value of the content that has been generated.
Using insights from big data analytics, media companies are able to understand when customers are most likely to view content and the devices that will be used to access the content. With the scalability of big data analytics, this information can be analyzed at a granular ZIP code level to facilitate localized distribution.
Insights on Customer Churn
A serious menace that media companies find almost impossible to tackle is customer churn. It has been found that a considerable population of customers share their reviews through social media. Until the advent of big data analytics, combining and making sense of all the user-generated data from multiple sources, including social media was next to impossible. With the advent of big data analytics, it is now possible to know why customers subscribe and unsubscribe from a particular type of content. With the help of big data analytics, it becomes easier to clearly gain insights on what kind of programs they like and dislike.
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On he flip side, implementing big data analytics in media and entertainment comes with its own set of challenges that media companies must overcome.
Big Data Challenges for Media Companies
The unprecedented rate of growth of the media and entertainment industry is forcing companies in this sector to keep up with the rapid pace of change. The shift from traditional platforms to online channels paves the way for media and entertainment industry companies to implement big data analytics technology to gain a more profound understanding of customers’ needs. But, with the rapid adoption of digital technologies, the media industry does face a few big data challenges, which slows down their progression. To completely realize the potential of digital technologies, media companies should successfully tackle these big data challenges:
Numerous instances of the breach of personal data and media are making consumers more sensitive towards their data. Additionally, policymakers have also addressed their issues and have implemented regulations for companies handling personal data of customers. Regulations have also been imposed on companies that broker personal data to media houses. Such big data challenges can pose problems when it comes to accumulating sufficient user data, without which conducting accurate analysis is impossible.
Lack of Financial Muscle
Media start-ups and SMEs often face challenges related to adequate financial capital. While accounting for cost factors to implement big data analytics, companies need to analyze several factors like data storage costs, infrastructure costs, data processing costs, and human resource costs. Although it is relatively easy to start a new company producing content, games, or apps, it can prove difficult to scale up without significant investments.
High bandwidth requirements
Today, audiences consume a large part of the content via online platforms. High-speed broadband is a must to facilitate this. However, the penetration rates of high-speed broadband services aren’t as impressive across the world as it is in metro cities. This largely reduces the potential customer base and allows data collection from only urban segment consumers. Analysts lose the opportunity to gain insights from customers who lack access to high-speed broadband and, therefore, resort to traditional platforms.
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Piracy and Copyright Issues
Piracy and copyright issues have been a major concern for the media and entertainment industry over the past several years. However, the advent of the digital medium has created new big data analytics challenges such as the problem of account sharing. A large number of people gain access by sharing account information and passwords for the majority of video streaming sites. Analysts will have a tough time performing analysis on customer behavior and preferences as they cannot pinpoint the demographic details of the user. Furthermore, in some cases both the child and the adult may be using the same account, here an effective judgment is impossible on who prefers a specific genre.
How to Overcome Data Security Issues Facing Media Companies?
Companies in the media and entertainment industry are collecting and using a huge amount of data. This gives rise to concerns over security issues that can compromise even locally generated information. With several instances in recent times reporting data breaches especially in the media and entertainment industry, it has become imperative for companies in this sector to make data protection a priority and establish strict security measures. We, at Quantzig, have identified some of the critical ways in which companies in the media and entertainment industry can guard data against breaches in both big data analytics deployments and any software that accesses the data:
Ensure Endpoint Security
Trusted certificates at each endpoint will help to ensure that the company’s data remains secure. Additional measures that companies in the media and entertainment industry should use include regular resource testing and allowing only trusted devices to connect to their network through the use of device management (MDM) platform.
Prevent Insider Threats
It is not just external threats that media companies must combat but also several internal security risks which include disgruntled or simply careless employees. Such challenges are faced by media companies where employees who work with the data are not fully educated on proper security practices and behavior, including data scientists and software developers. So, it is vital to provide digital security training to all employees.
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Analyze and Monitor
A big data analytics solution that includes tools for both analysis and monitoring in real-time can raise alerts in events where a network intrusion is detected. But this can result in large amounts of network data. The goal is to provide an overall picture of what’s happening over sometimes large networks from moment to moment. Companies in the media and entertainment industry may not have the resources to monitor and analyze all the feedback generated, including false alarms as well as real threats. Here, big data analytics itself can be used to improve network protection. The company’s security logs can be mined for abnormal network connections. This will make it easier to identify actual attacks as opposed to false alarms.
Research suggests that a large number of companies across industries have already invested in or are planning to put in their money in big data analytics due to the huge impact of big data analytics globally. The media and entertainment industry stands out as a prompt adopter of big data analytics solutions because a huge volume of data is generated digitally in this vertical and enables change in the consumer research programs.