Over the past number of years, there has been an increased focus on data-driven digitalization with big data technologies expected to reach $57 billion by 2020. Its effects can be realized across every industry including the media industry specifically the advertising operations.
As the media industry continues to grow at an unprecedented rate, media companies need to be early adopters of new technologies such as big data. With an increased target on digitalization and data-driven advertising and marketing, there has been a revolution in the media industry with regard to the use of data and analytics.
The key problem which drives media companies to look at the capabilities of big data includes the need to reduce the cost of operating in a highly competitive landscape while continuing to generating high revenues.
As the future of the industry is dependent on the amalgamation of both digital and analytical solutions, we examine how big data is shaping the future of the media advertising industry for ad operations.
1. Audience Predictions
As publishers and media companies begin their data-driven journeys, for the first time data is being used on a large scale in order to deliver the right content to the right people on the right platform at the right time.
With the scope of big data being collected nowadays and the potential to mine it to understand what content, movies and music consumers want is huge. It has been highlighted that data obtained on user behaviors via social media often reveals overlooked factors that have the potential to drive customer interest.
As consumers nowadays have the choice to select from formats such as on-demand, streaming media, pay-per-view, subscription-based and many more, most content is now delivered via various digital channels allowing media houses to collect, analyze and interpret user data efficiently and effectively. For example, Netflix interpreted the amount of viewership information to conclude which fiction dramas were favored by their consumers. With this data, it secured the right to broadcast the most favored drama ‘House of Cards’ by outbidding competitors.
Similarly, YouTube has interpreted vital statistics in order to deliver users with what they like the most. Information gathered allowed YouTube to learn about what video viewers enjoyed the most, which devices were used for streaming and the duration for which particular videos were viewed.
2. Improved Targeted Advertising
With advertising crucial in the media industry, in previous years it was purely conducted on the basis of assumptions. However, nowadays companies are harnessing big data in order to understand preferences providing in-depth customer insights such as when they would watch advertisements and at which particular time. This improved visibility helps ad ops position advertisements at specific time slots for higher conversion rates.
As big data makes it possible to understand digital media consumption, behavior can be used with traditional demographic data to provide personalized advertising. Big data applications improve ad targeting amid increasingly complex content consumption behavior. As consumers nowadays have access to multiple devices, big data insights help to understand when consumers use a second screen so that campaigns can be optimized across devices. Digital conversion rates can also be increased by offering micro-segmentation of customers across advertising networks and exchanges.
With social media platforms and YouTube providing better data for targeted advertising, it cannot be denied that TV still attracts attention. According to Fox Media, in 2017 they confirmed that digital viewers and TV viewings tuning their content were able to see the same advertisements. These advertisements were selected on the basis of Video Quality Score (VQS), using Moat which provides real-time, multi-platform and actionable marketing analytics. In addition to Fox, leading media companies such as NBC, Vice, The New York Times and CBC have begun using Moat.
Due to the preceding benefits, big data analytics is slowly becoming a choice for various media organizations worldwide. It creates an ecosystem allowing customers to take center stage. Ultimately, success in the media industry entirely depends on the user-experiences which deliver.
3. Expanded Customer Acquisition & Retention
Increasing customer churn is highly important for media companies. Nowadays, most customers resort to both social media and review sites before viewing particular series, movies, shows, music programs or downloading publications. The evolution of big data has allowed media companies to design tailored strategies in order to attract and retain customers. By leveraging various data sets, companies can understand consumer’s likes and dislikes, why consumers subscribe and unsubscribe thus helping media companies develop and tailor attractive promotional and product strategies and in order to attract and retain customers.
Unstructured big data sources are best handled by data applications such as call detail records, email, and social media can often be overlooked factors when looking at customer interests and churn.
Companies such as Warner Bros implemented software applications with sales data in order to gain quick access to actionable, accurate reports in order to support and accumulate knowledge in order to obtain insights to expand customer acquisition and retention.
4. New Product Development & Content Monetization
Big data and analytics can aid media organizations to generate additional sources of revenue. With accurate data, incentivization of consumer behavior can be undertaken which can help reveal the true market value of content or identify potential new product or service opportunities.
An example of this includes the Weather Company, owners of The Weather Channel (TWC) which is also co-owned by IBM. TWC used big data in order to observe and under customer behavior with regards to specific weather conditions.
Using the data available to them, they have created the new WeatherFX marketplace which allows advertisers to correlate their display advertisements with weather events based on various products which would most likely to sell in correlation with particular weather conditions. TWC is estimated to earn at least half of their advertising revenue using the results of big data analytics.
Mobile profusion and bandwidth expansion make it possible to engage with a larger chunk of digitally connected audiences for content monetization as big data facilitates zoning in the right content which the audience prefers.
5. Media Scheduling Optimization
Up until a couple of years ago, there was a gap between both the distributors and consumers. However, with the evolution of digital media platforms, this has changed, making it easier for distributors to approach potential consumers without the need for an intermediary.
Social networks allow distributors to create personal connections with consumers. Connecting with consumers via the scheduling of media streams in order to maximize profits. With the scaling ability of big data, information can be analyzed at granular levels such as ZIP code levels for localized distribution.
An example of this includes the release of Bollywood film Chennai Express, prior to the release, movie-related tweets generated more than 1 billion impressions and tweets with relevant hashtags generated more than 750,000 impressions during a 3-month campaign. As a result of a number of data analytics sources and marketing the film established several new records which to date remain unchallenged. It is probably one of the quickest films to enter the billion-dollar club.
The “Big” Future Ahead
Big data has the ability to provide numerous opportunities in the media industry as it can help navigate the biggest changing factor in the industry – customer behavior.
Analytics can aid media companies to solve decisions quickly such as which formats and channels do customers prefer, which content is likely to be consumed at which time and on what device, in order to develop personalized experiences. As it can also inform with regards to the constant shift in customer preferences, this enables a reduction in customer churn, establishment of alternative revenue channels along with the ability to increase customer acquisitions and retention via data intelligence.
Ultimately, big data creates an ecosystem where customer experiences are at the forefront. After all, the media advertising industry succeeds on the end-user experience it creates.