Marketing / Taking the Mickey: how Disney uses analytics to tell stories

Taking the Mickey: how Disney uses analytics to tell stories

DISNEY HAS been telling stories since the 1920s when Mickey Mouse and his friends were first drawn. And today it is among the most respected companies for using data and analytics to communicate an effective narrative to its fans.

The company gathers and analyses a wealth of information from across its media and retail platforms, which helps it to produce engaging content its audiences will enjoy. “Without analytics we would never know what the data is telling us or have a clear understanding of what consumers will find relevant,” says Disney’s head of audience strategy EMEA Richard Ellwood. “We also need to know which data to ignore because we generate so much.”

Ellwood has worked at Disney for nine years, extracting and contextualising information from different data points to help the business make strategic decisions.

For the recent hit movie Star Wars: The Force Awakens, the brand collected data from social media, box office ticket sales, retail transactions of toys and above-the-line TV marketing.

“We take a data analytics approach to everything we do because it has a huge impact on our marketing strategy,” says Ellwood. “The secret is to combine structured and unstructured data so we get an understanding of why people are behaving in a particular way.”

He cites the example of how data is used around one of its most popular shows, the Mickey Mouse Clubhouse TV series on the Disney Junior channel. By monitoring social media and understanding how, when and where people are watching, the company makes sure the content remains credible and the characters and stories resonate with the audience.

“Also, if we know what devices people are watching on we can adapt the content. Children and parents would probably not watch a movie on their phone but they might view short form content.”

Ellwood says brands should work with data specialists or recruit in-house talent to make the most of data analytics.

“You do need advice on what data is valuable and to understand issues around privacy,” says Ellwood. “Sometimes you think the data is suggesting a certain outcome when you explore and analyse it. However, when you link it with another set of data you can see that is not the case.”

He says marketers must regularly mine and clean their behavioural data to ensure it remains relevant because viewing and purchasing habits can change so quickly.