Publishers, broadcasters, news organizations, cable companies and gaming companies in the media and entertainment industry are facing new business models for the way they create, market and distribute their content. This is happening because today’s consumers search and access content anywhere, at any time and on any device. As a result, there’s increased pressure to execute new digital production and multi-channel advertising and distribution strategies that rely on a detailed understanding of consumers’ media consumption preferences and behaviors. And, as consumer interests shift from analog to digital media, there are substantial opportunities to monetize content and to identify new products and services.
With thousands or millions of digital consumers, media and entertainment companies are in a unique position to leverage their big data assets for more profitable customer engagement. Here are just a few examples of how media and entertainment companies can benefit from big data applications.
The scope of big data collected by the media and entertainment industry and the potential to mine it to understand what content, shows, movies and music consumers want is huge. Viewing history, searches, reviews, ratings, location and device data, clickstreams, log files and social media sentiment are just a few data sources that help take the guess work out of identifying audience interest.
Using insights from big data, media and entertainment companies are able to understand when customers are most likely to view content and what device they’ll be using when they view it. With big data’s scalability, this information can be analyzed at a granular ZIP code level for localized distribution.
By using big data to understand why consumers subscribe and unsubscribe, media and entertainment companies can develop the best promotional and product strategies to attract and retain customers. Unstructured big data sources best handled by big data applications such as call detail records, email and social media sentiment reveal often overlooked factors driving customer interest and churn.
Big data makes it possible to understand digital media and entertainment consumption and behavior that can be used along with traditional demographic data to provide personalized advertising in the right context, at the right time and in the right place. Big data applications help improve ad targeting amid increasingly complex content consumption behavior. For instance, since consumers access media and entertainment on multiple devices at the same time, it’s helpful to use big data insights to understand when consumers use a second screen so that campaigns can be optimized across devices. Media and entertainment companies can also increase digital conversion rates by offering micro-segmentation of customers to their advertising networks and exchanges
Big data can also help media and entertainment companies generate additional sources of revenue…suggesting new ways to incentivize consumer behavior, revealing the true market value for content, or identifying a new product or service opportunity. For instance, the Weather Company, owner of the Weather Channel network, has created a new WeatherFX marketplace service that allows advertisers to correlate their display ads with weather events based on which products are most likely to sell under different weather conditions.
Qubole’s platform for self-service big data analytics is used by more than 80 customers, including these leading media and entertainment companies:
Qubole is a significantly more polished product than EMR. Data scientists can explore their data in S3, create tables and query those tables all via an easy-to-use web UI
Qubole’s fantastic support has been key in our successful deployment. They continue to deliver of new features and revisit the ones that we ask for
Our goal at MediaMath was to take our existing industry leading infrastructure to the next level handling new complex analytics tasks. Qubole has helped us enable this goal with minimal risk.
Instead of worrying about provisioning clusters of machines or job flows or whatever, Qubole lets you focus on your data and your queries … The Qubole guys have been extremely helpful!
The service spins up users’ clusters only when a job is started, then automatically scales or contracts them based on the workload, and spins the servers down once the job is done.
Qubole’s Hadoop and Hive interfaces are vastly superior to the default CLIs, which scare business analysts and hinder meaningful analyses of the gaming logs that we collect. With Qubole, business analysts are self-sufficient in using a Big Data platform to meet their advanced analytic needs.
Online Gaming Company
top-performing technologies in the data industry are definitely taking aim at democratizing data tools and bringing the power of data to smaller businesses. This is a major change in the data industry, and Qubole Data Service is a great example
I’m very happy to be using Qubole in production. Qubole has saved me a lot of time, effort, and trouble in getting my data processing pipelines up and running. My data pipelines process Appnexus data in Amazon S3 which is then stored in Vertica. The engineering team understands the complexities and provided awesome support!
Real-time Ads Retargeting Startup
There’s a whole world of web companies, SMBs and other non-Facebooks or Yahoos that will want to use Hadoop but not want to run it in-house…offering a cloud service makes it easier for these users to get started with the platform and for Qubole to keep improving.
Qubole offers a big data ETL and exploration service through auto-scaling Hadoop clusters with a web user interface for data exploration and integration with various data sources. The service can do (nearly) everything EMR can do, and it goes further
Big Data Republic
Simba knows Big Data access. Qubole knows Big Data. Qubole’s founders authored Apache Hive, built key parts of the Hadoop eco-system and brought Apache HBase to Facebook
“The integration of Tableau and Qubole makes it faster and easier for our customers to operationalize Big Data…lowers the resource barriers to deriving the benefits of Big Data because customers can deploy our joint solution seamlessly and cost effectively.”