Visualised #4: After The Interval

On 23 March, the UK went into ‘lockdown’ in response the COVID-19 pandemic. By that point, many cultural organisations had already taken the decision to shut their doors and were dealing with the fallout from cancelled performances.

Several weeks on, venues are still unsure about when they might start opening their doors and welcoming back audiences. With so many unknowns, data about audiences’ attitudes towards live event booking was urgently needed.

Enter Katy Raines of Indigo - marketing and fundraising consultants for the cultural sector - who set about organising the After The Interval survey:

A free national online survey designed to capture audience views on returning to arts events, booking tickets now and in future, and missing out on live events during lockdown.

192 organisations in the UK and Ireland sent out a standard form survey to their mailing lists and around 86,000 people responded. Individual organisations have immediate access to their own data and responses are aggregated into a national data set for wider sharing amongst the sector.

Katy asked if we’d be interested in helping to visualise that aggregated data and we jumped at the chance (I should point out that nobody’s being paid to do any of this).

The dashboard and findings

You can read the first After The Interval report here. I’ll let you discover the findings there.

Here’s the interactive After The Interval dashboard…

Behind the scenes

The survey has been built using SurveyMonkey. The responses are sent to us as CSVs and we put them into Google Sheets where we do a small amount of data wrangling. The dashboard has been built with Google Data Studio.

The bulk of the work on this was done by Alix Marion, with Chris Unitt chipping in feedback every so often.

What you can see right now is a beta version done within quite a quick turnaround. While it works fine, we want to provide more ways to interrogate the data. We also want to find ways to make it run more quickly which may include adding the data into BigQuery, especially when data from further rounds of the survey come in.

We hope it’s useful and gives organisations some guidance to feed into their scenario planning.

Want more visualisations?

This post is part of our Visualised series where we take cultural sector data and make it more accessible through visualisations.

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