Channel 4 is a publicly owned, commercially funded public service broadcaster headquartered in London, England. Launched in 1982, Channel 4 is one of the UK’s premier public service TV channels.

Changing consumer lifestyles and the explosion of web-connected devices such as tablets, mobiles, consoles, and Internet-enabled televisions led Channel 4 to develop digital and video-on-demand (VOD) services so its viewers can consume content in new and diverse ways. The broadcaster’s 46 million viewing audience regularly access custom video-on-demand service 4oD, Film4, customized games, and social channels, as well as the main Channel 4 service.

The business success of these services created new challenges for Channel 4: the volume of largely unstructured web data flowing from the VOD platforms grew faster than its existing on-premises environment could manage.

With its business and brand missions to connect more personally with viewers and more closely with advertisers, Channel 4 realized it needed smarter, more agile decision-making in the commissioning, scheduling and monetizing of content.

To realize its business objectives, Channel 4 needed a proven high-performance data-analytics solution—a flexible, integrated service capable of capturing, storing, indexing, searching, mapping, analyzing and matching high volumes of viewer and platform data on demand.

When Channel 4 investigated the feasibility of using its existing data-analytics software to perform key tasks, the company found that it would take eight months to deliver the relevant base data for analysts to access. In contrast, by using Amazon Web Services (AWS) and Amazon Elastic MapReduce (Amazon EMR), Channel 4 could begin analyzing and modeling the data in just two and one-half days.

Amazon EMR runs across a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances that feature Intel Xeon E5 family processors. The combination of AWS and Intel together provides Channel 4 with the availability, flexibility, and virtually unlimited capacity of a cloud-based solution, with the proven power to process huge volumes of data.

Channel 4 also developed a Big Data control panel (BDCP), a web-based interface to allow analysts to spin up and spin down Amazon EMR clusters, submit queries through Apache Hive and Pig, monitor job status, and extract sample or actual data to run in modeling applications. BDCP puts convenience, control, power, and speed right in the hands of the people who need it, while providing a simple solution to a complex business problem. “With Amazon EMR, we can analyze 100 percent of the data, not just a sample,” says Sanjeevan Bala, Head of Data Planning & Analytics. “Traditional analytics can’t do that.”

Using the AWS Cloud allowed Channel 4 to avoid the need to invest in massive server infrastructure, disks, and CPUs and bring its registered VOD viewers closer to both content and advertisers, with benefits for both parties.

By analyzing repeat viewers, the broadcast company can better understand their preferences and behavior, schedule more relevant content, commission enticing new content, and connect more closely with viewers.

Its modeling systems can even predict the socioeconomic class, age, and gender of anonymous or unregistered viewers from content viewed, giving advertisers confidence in optimizing media placements. Channel 4 analysts can instantly provision the capacity they need from Amazon EMR to perform complex predictive modeling and other business-intelligence tasks with maximum speed, cost-efficiency, and return on investment.

Channel 4 can have a direct relationship with its nine million registered viewers for the first time, even modeling in-session data to deliver relevant ads before a program ends—an enviable advantage for any broadcaster. “In 60 minutes, Channel 4 can analyze and model in-session data to deliver highly targeted ads to viewers-before a program ends,” says Bala. “Using AWS has helped Channel 4 build ad revenues, enhance its marketing of content, and use detailed, dynamic data to open up exciting new business opportunities.”

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