6 Big Data Analytics Strategies Optimizing Media Advertising

With digitalized marketing, and data-driven advertising, and marketing, the media industry is experiencing a revolution in the deployment of data analytics.    

FERMONT, CA: The paradigm of advertising has changed with technology, as more advertisers keep redirecting their budgets towards digital, and internet-based video advertising. This change was motivated mainly by the growing use of big data across multiple internet platforms. So, how precisely is big data driving digital video ads? Over the past few years, time spent on connected devices has risen quickly, prompting a transition from television advertising to digital advertising. The reason for this fast development is due to enhanced use and adoption of social media platforms, as well as apps for video streaming.    

By using big data analytics, businesses can recognize unique user behavior patterns, trends, and relationships. Therefore, they can target audience more accurately while formulating their advertisements. Big data analytics are used in a variety of ways such as to boost revenue, comprehend client sentiment in real-time, promote efficiency in marketing, and boost ratings and viewership. As the industry's future depends on the combination of digital and analytical solutions, there are few ways in which big data analytics can help in video advertising and content monetization.

Attracting Viewer Interests

The media industry's scope and ability to mine large quantities of data to understand what content, shows, films, and music clients prefer, is huge. Viewing history, searches, reviews, ratings, place and device information, clickstreams, log files, and social media are just a few sources of information that help identify audience interests.

Intelligent Marketing 

This element helps track, clean, and bring ordinary channel-specific information into a single consistent record scheme. From marketing Key Performance Indicators (KPIs) to profound insights, everything is continuously measured and easily obtained from a trusted cross-device perspective of the customer's trip. The tool helps leverage complex algorithms of attributions to move beyond measuring the last click, to make informed and confident decisions on how best to allocate marketing spending to drive growth efficiently. 

Ad Targeting

Big data allows the understanding of digital media consumption and behavior to be used in conjunction with traditional demographic data to deliver personalized advertising in the right context, at the right time and in the right place. Big data apps enhance ad targeting in the midst of increasingly complicated behavior of content consumption. Since customers simultaneously access media and entertainment on various devices, it is useful to use big data insights to comprehend when customers use a second screen to optimize campaigns across devices. Media and entertainment businesses can also boost digital conversion rates by providing their advertising networks and exchanges with micro-segmentation of clients. 

Real-Time Analytics

Real-time analytics is the use of all accessible customer and company information, procedures and techniques to serve clients and the company itself "at the point of need." With customer-facing procedures, companies can determine how they implement their marketing policies and tactics. In this case, real-time analytics fundamentally enables marketers to generate value for their clients. Real-time analytics algorithms deliver insights into quick performance. Consequently, key choices and content improvements can be made instantly. The use of real-time analytics creates more opportunities for a business to win the race with rivals.  

Content Distribution 

The contemporary social networking environment offers an excellent opportunity for media and entertainment companies to implement their marketing strategies with a strong tool of social media content distribution. General trends, the behavior of customers, preferences, experiences, interests, and stories are now accessible in one click for large media companies. Distribution of content mainly relies on a statistical analysis of social media. Content distribution particularly depends on the analysis of social media statistics. This identifies the targets readers. The synergy with a user via social network proves to be extremely efficient in the promotion of the media and entertainment outcomes. 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 with the users’ needs.  

Analyzing Customer Insights

A general tendency of data science application provides countless advantages to people in business around the world. The algorithms assist in collecting and analyzing the customer insights and make use of the output. All remarks, posts, likes and dislikes, opinions, subscriptions, etc., present a vast floor for extracting ideas for media and entertainment companies. The data analytics algorithms process the data, filter, classify, and group the coincidences, and draw conclusions that allow media and entertainment firms to know their customers better. Predicting the future revenues, response and attitude of clients, planning, and constructing effective marketing strategies — would all become a reality with advanced analytical solutions.  

Analytics can help media businesses to rapidly resolve choices in terms of formats and channels that clients prefer, content that is likely to be consumed, and devices and methods that create customized experiences. This allows for the establishment of alternative revenue channels along with the ability to increase customer acquisitions and retention via data intelligence, and a reduction in customer churn as well. Big data analytics ultimately generates an ecosystem in which customer experience is at the forefront.