Electronic Arts: Leveling Up Data Across Screens

“There is literally a game for everyone,” said Colleen Nuffer (seen here), Global Media Planning and Activation Lead, Americas, Electronic Arts, in opening her keynote speech at Monday’s MediaPost TV and Video Insider Summit in Scottsdale, Arizona.

EA’s latest game came out last Friday. “District 9” director Neill Blomkamp created a short film to tell the story behind “Anthem.” Rated T for Teen. There was an emotional response, with over 3 million views on YouTube alone. “We need to take the same mindset as we approach media,” she said, noting the connection between science and art.

“We understand the value of data. We cannot lose sight of the art that goes with the planning.”

Data drives deeper player understanding. EA’s CMO decided to combine analytics and marketing teams. Study player motivations -- around why people play. Are they part of the team? Who is the game made for? Study player behavior: who, how, what? What platforms are they playing on? How do they feel when they lose or win? 



She showed a passionate team player, “Dave.” He enjoys the team aspect, is a fan of BioWare, plays NBA Live, enjoys comic books. His favorite team is the Warriors. “We start our media planning by understanding our players.”

There is art in planning: contextual relevance, leaned-in audience. There is a team of search, social experts going through cross-channel training right now -- truly integrated.  Showing “Anthem” in cinemas, aligning when “Captain Marvel” was coming out in order to engage “Dave.” Big NBA strategy, All-Star game. Validated through data-driven insights.

“For Dave, we assume he’s not into traditional TV. Mobile surpasses TV in time spent. Backing away from TV entirely? No, taking a second look at our TV investment to make sure it is the most impactful.” 

It's difficult to reach the human attention span. The line between gaming and entertainment is becoming blurred. 

The landscape shifts -- look at scale, targeting. There is a shift to data-driven, addressable or programmatic. We're also looking at information for traditional TV. 

Maximizing impact: finding times when consumers are truly engaged and receptive, and using our data learning to apply to channels that aren’t as data-driven.

In the end: 1. Utilize data to validate decisions; 2. Apply learning to traditional linear to maximize impact; 3. Test, test, test. 

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