Washington D.C. – Canada’s audience measurement organization for TV and radio, Numeris, is embracing what analytics can do for its internal organization.

The company, which was founded in 1944 as a division of the Canadian Association of Broadcasters as the Bureau of Broadcast Measurement, is the primary provider of viewership numbers for TV and radio broadcasters in Canada. In 2001 it shortened its name to BBM Canada, and in 2014 it went through a full rebrand to become Numeris.

Back in 1964, the non-profit organization became one of the world’s first ratings services to use computerized sample selection, and in 2004 it teamed up with the United States’ Nielsen Media Research for its portable people meter system for TV. Now Numeris has turned to SAS Institute Inc. for the SAS Platform and the analytics resources that accompany it.

According to Derrick Gray, director of audience measurement science at Numeris, the organization was looking for a business intelligence solution like the one SAS provides.

“The ability to start leveraging the open source platforms together on SAS is key for me. We are building a data science team right now, and we are getting a little bit of pressure to develop a high level data analytics team,” Gray told Canadian media at the SAS Analytics Experience 2017.

For now, Numeris is using this technology for operational data that can help the company ‘drive down costs and increase quality’, explains Gray. The company’s sample data comes from phone calls, and with fewer participants answering their phones it takes more effort to reach the 180,000 respondents required in the dairy markets and to maintain the 11,000-person electronic measurement panel that the organization needs to produce those radio and television audience estimates.

“To get our ideal sample number we have to dial around 2 million households annually. With SAS Viya [SAS’ artificial intelligence platform], we will be able to shift to a centralized business intelligence tool,  SAS Visual Analytics, so users from across departments can collaborate,” said Gray.

The inter-departmental cooperation that comes with this technology is key for Gray, who wanted to alleviate the reliance other departments had on his in order to create dashboards and reports. Beforehand, those departments had to come to his for help, while now they have the ability to self-serve.

“More people will have access to common, consistent data, allowing Numeris to quickly see patterns and explore insights so we can easily maintain our existing list of households, dial fewer numbers, and improve participation outcomes,” Gray added.

As for when these analytics technologies will be used in the actual audience metrics collected by the organization, that may be some time off. Due to Numeris’ governance structure, it has a pretty strict governance process that requires this technology to go before various committees before it can be implemented.

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