Art organisations to bring in data scientists to lure new audiences

Examples include mapping ticket sales and weather to see if there is a pattern

Nick Clark
Tuesday 10 February 2015 19:39 GMT
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The National Theatre in London
The National Theatre in London (David Samuel/Creative Commons)

Some companies bring in “artists in residence” to boost creativity in the workplace. But in a reversal of that trend, three of the UK’s biggest artistic organisations are now recruiting “data scientists in residence” to develop their businesses through what has been described as a “cultural Moneyball” programme.

Two expert data scientists will spend the next six months in residence at the National Theatre, the Barbican and the English National Opera.

The programme will explore new ways arts organisations can take advantage of the volumes of data they create better to understand how to bring in new audiences.

Examples include analysing social media to understand their existing and potential new audiences, and even mapping ticket sales against weather to discover if there is a pattern.

The Signal and the Noise: The Art and Science of Prediction by Nate Silver, famed for his accurate prediction of US voting patterns, was hailed as the “root text” of the project by Anthony Lilley, the chief executive of creative technology company Magic Lantern.

He added that there are “elements of Moneyball”, the book which later became a Hollywood movie about how Oakland As, the baseball team, flew in the face of conventional wisdom and used rigorous statistical analysis to build a team that could compete with the best on a fraction of the budget.

Alison Whitaker and Eva Kabzinska have already started working on The Arts Data Impact project, set up by The Audience Agency, a not-for-profit consultancy working with cultural organisations to build audiences.

Cimeon Ellerton, head of programme at The Audience Agency, said: “A lot of arts organisations generate data at a vast rate, some of which we can capture and some we can’t and a lot we don’t know what it’s telling us.”

He added: “They will ask what data is there, how they are using it, what aren’t they using and bring in new skills for analysis you may not have thought of.”

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