There are obvious reasons that explain the ambition of 83% of the companies to invest in big data in 2019. Research at McKinsey reveals that around 50% of enterprises confirmed that utilizing big data revolutionized their business operations – particularly marketing and sales. Consequently, the global revenue is projected to cross $103 billion in 2027 from current $43 billion. One of the most notable instances which are assisting in achieving this feat is big data in media.
Psychographic Segmentation with Big Data Solutions
Customers are only going to subscribe for a video on-demand service if the provider is able to convince them. The latter needs to find out what drives customers to download the app and which type of content do they want. The answers to these questions vary depending on age groups, socioeconomic situations, trending programs, and user interests.
It is practically inefficient to determine these factors at the level of individual subscribers. Using big data, you can identify the viewers with similar interests and demographics before grouping them together. This grouping, technically referred to as psychographic segmentation, provides the outcome which can then be used to offer video content relevant to each subscriber’s interest.
Apart from consumer analysis and determining consumer trends, big data analytics in media also enables VoD service providers to sketch consumer journey map. The compilation of this map allows companies to find the path followed by consumers before becoming subscriber. Similarly, it also allows determining the causes of drop in subscription percentage.
In all, psychographic segmentation and consumer journey ensure effective market research in VoD industry.
Smart Filters for Big Data in Media and Entertainment
The websites and apps for social media, public relations, and discussion forums often feature instances of hate speeches, abuse, and graphic violence. Facebook alone has 2.38 billion active users as per Statista figures from March 2019. With billions of users participating in online social activities and discussions, the amount of inappropriate content is also growing.
It is impossible to filter each comment, post, picture, and video manually. All notable social networks are and discussion forums have placed multiple checks so that inappropriate content can be removed as soon as possible. The pace of tech development is too fast for legislators to develop corresponding laws in time. Thus, the governments are trying to regulate such platforms with filters using big data without compromising free speech.
Spam and Intrusion Detection for Enhanced Data Security
Cybersecurity challenges are posing more threat than ever as data security is becoming one of the top concerns for service providers, regulators, and consumers alike. IBM research reveals that cost of breach involving over a million records is $42 million. Every breached record costs $148. Since most of the consumers of VoD and social media are non-technical users, they are prone to falling for spam emails and other intrusion scheme.
Big data in combination with machine learning and deep learning algorithms including Naive Bayes and Multilayer Perceptron (MLP), respectively can aid in developing filters which detect spams and issue an alert. Top media outlets have placed comprehensive intrusion detection and prevention algorithms to ensure excessive data security.
Data Science in Media Industry for Predictive Analytics
It is crucial for a service provider in any industry to have knowledge about changing trends. Big data allows companies to make strategic decision making and corporate planning by forecasting future. This big data forecast in media industry depends on relevant data acquired from credible sources.
The predictive analytics based on future projections enable service providers to outperform their competitors by working on content which is projected to be in high demand. It is notable big data in media and entertainment requires authentic data because acquisition of data which is inconsistent, irrelevant, or unreliable results in worsening of analysis. Such erroneous analysis would generate incorrect predictions, and hence result in inefficient corporate planning.
Intelligent Self-trained Virtual Assistant
It would be unwise to keep human assistant who listens and notes down queries and complaints of subscribers. This age of AI provides highly efficient virtual assistants that are more far productive than human for the same job. Using virtual assistants does not only reduce cost but also enable you to offer seamless services.
The most attractive feature of modern virtual assistant is its ability to train itself. In essence, such a software system uses past interactions and improves itself using reinforcement learning technique. You do not need to wait for the system to get matured before using it for interactions with consumers. Instead, Mob Inspire provides such systems which are already trained over variety of datasets.
Virtual assistant is one of the most widely used big data applications. Even the companies with absence of large-scale data are also utilizing robotic assistants. They can provide round the clock access to remote assistance. These systems are not only capable of responding the issue but solving it as well.
Redefining Marketing Strategy
Crafting consumer journey is one of the marketing phases that target customers. However, there are other metrics as well which are essential to determine for marketing. Every significant marketing campaign requires extensive analysis on financial situation. Big data in media industry allows predicting the projected growth volumes in response to various campaigns so that campaigns can be prioritized.
For these reasons, the top providers of video on-demand services are emphasizing on marketing, particularly instant gratification. They are able to assess what consumers would like to watch and present the most relevant results. The remarkable return reflects in 26% growth rate of Netflix as indicated by financial report of Q2 2019.
Mob Inspire is performing research and development in big data for a data now. In this period, we have assisted dozens of clients to refine or redevelop their architecture by using big data solutions. We look forward to developing new partnerships in the industry. Contact us today so that our experts can help you in the most appropriate way.