Every industry in the world is moving towards data-driven decision making, then one of the most popular and highest grossing industries definitely has employed analytics and data sciences in its operations. We are talking about the media and entertainment (M&E) industry. If you are associated with the industry in any way and your question is how to use analytics to maximize the potential in this industry across all domains, you are at the right place!
The increased technological and digital revolutions have caused a data-enabled revolution within the media and entertainment industry. You can see a perfect convergence of digital and analytical solutions in this industry.
Before we move on to how analytics can be employed in the media industry, let us understand its needs and priorities. The trends of media and entertainment industry are primarily driven by the changing needs of the digitally savvy audiences and their preferences. Most of us now want to use entertainment means not only to recreate and relax but also to stay on top of advancements, world events and our respective interest areas- all this while on the move!
Our fast-paced lives have pushed the entertainment industry to alter their content and the war of delivering it to us rapidly. While the primary intent of the industry lies in developing the best content for the audience, the media industry also tries to diversify into various channels for broadcasting information and entertainment content. Analytics can in fact steer media and entertainment towards burgeoning growth rates.
How can data analytics impact media and Entertainment?
If we just look at some facts and numbers, we can see a staggering amount of data from social media and online media being pulled and processed. As of 2017, Facebook is reported to collect and process over 500 TB of data on a daily basis. The search business market leader, Google handles 3.5 Billion requests every day. Amazon is another member of the big data league that receives around 152 Million customers’ purchase data daily. Having said that, big data is definitely an essential tool for the entertainment and media industry.
There are three main areas where big data has the potential to disrupt the status quo and stimulate economic growth within the media and entertainment sectors:
Products and Services: The industry can use analytics to design content. You can derive quantitative insights about the sentiment of the audience by analyzing large and heterogeneous datasets. You can also use analytics to analyze the content the competitors are running and use the insights to tweak your own content. That sounds a useful asset to have for news channels, is it not?
Customers and Suppliers: If you are associated with ambitious media companies, you know how important it is to know about the preferences, profiles and attitudes of the customer. This not only enables stronger relationships but also higher loyalty. Data and analytics can help you do that too!
Infrastructure and Process: Data-driven models often help companies automate and improve the efficiency of certain processes. Furthermore, by establishing pipelines to pull and process various kinds of datasets, media companies can do advanced analysis and gain an edge over the rest of the market.
Some critical applications of data analytics in the media and entertainment industry are:
Data journalism – This application uses analytics to derive insight, discover exciting stories, and generate excellent content. By enhancing the value of these insights, you can improve the quality of journalism and thus, enhance the brand value.
Social Media Analysis – Using batch and real-time analysis of social media data like tweets, images, comments and status updates to identify trends and content that can be fed as an input for creating services for the clients.
Cross-sell of products – Applications like recommendation engines of content using collaborative filtering, content-based filtering, and hybrids of both approaches can create additional points for a media platform. Everyone here knows about Netflix, don’t we?
How do we obtain this data?
Most of the data being spoken about in the analysis above is customer-centric or can be pulled from various media platforms. All this can be done using one tool- Web Data Scraping! Firms like Datahut can scrape data from multiple sources and store them in a structured file format. Social Media crawling, social listening, data scraping and web aggregators are not just jargons thrown around in the technical data-driven community. These are some of the tools and techniques used to scrape data from media platforms and websites.
To make it further accessible for you, we can assure that learning the basics of data gathering and analytics is not difficult! You have a lot of resources that can help you understand the technological aspects. For faster and efficient results, we at Datahut can offer you scalable solutions and services to convert all unstructured web data into structured data files.
A lot of this data, like Google search trends, is also available to the public for analyses and research. This data can either be pulled using APIs (application program interfaces) or be extracted using methods like web scraping.
How has the media industry used data analytics?
Online media platforms like Netflix rely on data analytics and data-driven decision-making tools for almost all their operations. One of the most popular use-cases is where Netflix monitors reviews, trends and customer sentiments to gain an edge over the competitors. They have used this data in the past to gain complete partnership rights for a leading political drama show.
The online content platform has been able to crunch the vast amount of viewership data to study their viewers. Using this data gives them an in-depth and fine-grained analysis of viewers’ habits over millions of viewings of shows. Some fundamental insights that Netflix has obtained are the attributes or qualities that cause a particular show to be popular or how long viewers had viewed similar programs, through seasons and individual shows.
Warner Bros. had partnered with Accenture’s Datamart team, Aprimo to use software applications along with sales data in order to obtain quick access to actionable, accurate reports to support spend decisions, accumulate knowledge and experience. These applications can also help them apply actionable insights to refine subsequent movie marketing campaigns with past ones, thus improving invoice collection efficiencies.
In the music industry, a lot of artists and production houses use data on the audience’s listening preferences and sequences to design albums and market their creations effectively. Music platforms can also use data to generate insights on how to optimize the playlist for the maximum impact at live events.
What can Datahut do for you?
Datahut has partnered with a lot of companies in the media industry to scrape data and help them with real-world business problems. We helped a customer gather data from forums that contain review and discussions about leading shows like Quantico. This data is then used to analyze the viewers’ sentiments and get a better understanding of peoples’ perception of the shows. This, as mentioned above is a vital tool for not only designing content but also for strategic marketing decisions like what shows and production houses to partner with, what shows to host and even what suggestions to give the viewer for his next or alternative watch.
If you are a content creator, such data can also be used directly by you. Imagine being a music creator and having the insights on what your targeted audience appreciated and did not like about your last album. It’ll certainly help you target certain strata of customers for your content and invest more resources to popularize the music among those listeners?
One significant observation that Datahut has had while working with our customers in the media and lifestyle sector was that the scope of data and analytics is not only limited to the conventional content-hosting platforms or artists. One of our customers wanted to use data and analytics to monitor fashion news websites and blogs to learn about upcoming trends, market preferences, and customer needs. Some particular keywords and phrases for instance, “denim jackets” or “cold-shoulder”, if gaining popularity would be of great interest to the customer.
However, here we will have to pull data and the associated insights immediately before the virality of the keyword reduces. Since the fashion industry, just like the media industry is highly volatile and fast-paced, data scraping for such use-cases should be automated, regularized and reported immediately. In a different case study, a customer wanted to make a library of all the news content their competitors are posting. If you want to get an understanding of when the competitors updated or omitted something later and why; this serves as a significant use-case.
We at Datahut have also helped our customers extract a significant component of alternative data, viz. web data, to predict market performance and design pricing and investment strategies. We helped a customer extract customer review data to, in turn, design a predictive analysis model that would predict how the Netflix stock is going to perform in the near future. Interesting, is it not?
What else can be done?
Although the above examples reflect the industry trends at scale, the possibilities are not limited to these. Even online blogs and platforms that host articles can employ analytics to make vital strategic decisions. If you are a writer, who publishes content on platforms like Medium, would you not want to gain insights on what your followers or the readers think of your content? While the comments and reviews would give you a direct insight on the same, the sparsity and lack of such direct feedback can be covered up with stats of your articles. Metrics like the ratio of the number of readers to the number of views, basically tells you if your articles’ theme intersects with the readers’ interests.
Several other entertainment and lifestyle companies can use data to design advertising campaigns, discount programs, and marketing campaigns. This data can also be used for designing dynamic pricing campaigns.
The Weather Channel (TWC), a privately owned weather business co-owned by IBM uses Big Data and inquisitive analytics to observe and study customer behavior in specific weather conditions.
It has been able to fabricate a marketplace, WeatherFX where sellers can advertise their products that show higher chances of selling in a particular weather scenario. Companies like BookMyShow predict a movies’ performance to design discount coupons and promotional offers for the audience.
While the opportunities are endless, it is on you to decide how to leverage big data insights into your company’s best interests. Firms like Datahut can help you procure the necessary data.
When you couple this with robust analytical solutions, you can optimize all your operations and processes.