It may well be one of the biggest challenges of running a theater or venue: knowing what to program to attract the target audiences you aim to reach. Conversely, for artists, creators, and impresarios, it is often a question of which venues they should visit during their tours to draw interested audiences to their shows and reach existing or new audiences.
DIP can provide a solution here. This initiative by three major industry associations in the Dutch performing arts sector is a central information platform designed to improve efficiency through a digital infrastructure that streamlines work processes and collects and unlocks data. DIP offers three modules that provide insights into ticket sales, audience information, and contracts. Currently, more than 150 theaters and venues and about 200 artists and impresarios are connected—about 85 percent of the sector.
‘We want to encourage organizations to base their decisions more on data: which offerings match the intended audience?’
One central tool
These organizations and artists share their data or contracts anonymously via the monitor. ‘Previously, audience information was stored in all sorts of separate tools,’ recalls founder Joep Grooteman. ‘As the former head of communications at ITA, I know how challenging that was. By collecting this knowledge in one place, we can benchmark more easily.’
By sharing this data, theaters and venues can reach more audiences, Grooteman reasons. ‘We want to encourage organizations to base their decisions more on data: which programs match the intended audience? This can be done, among other things, with the audience monitor, which provides organizations with insights into the profile of their visitors.’
Predictive power
This year, a predictive model called the Audience Demand Forecasting Model, based on artificial intelligence, has been added to the audience monitor. The tool, developed by Predictive AI, is currently being tested and is not yet available to users. This AI tool predicts how many tickets for a particular artist or performance will be sold, even before the program is booked. Grooteman: ‘This is interesting for programmers, who cannot possibly be aware of all available offerings or may want to step outside their own expertise. Lesser-known creators also benefit: without all this data, venues would be less likely to take the risk of putting an unknown act on stage. This creates a more diverse offering, with room for both well-known and lesser-known artists.’
There are also advantages for artists, creators, and production houses: they can use this information to determine where it is profitable to perform or where they can reach new audiences. This prediction is based on audience behavior: which tickets they purchased before and what their online interests are.
‘The goal is for the tool to function better than one person could, complementing the expertise of the programmer’
Goals first
According to Grooteman, it is not the intention for programmers to blindly follow the tool’s outcomes. ‘The tool is a resource for programmers to perform their work better or more efficiently. The information helps you make well-founded choices,’ says Grooteman.
Edsart Udo De Haes, founder of Predictive AI, adds: ‘Although the reliability of the predictive model is very high, only people can determine what the intended audience of a performance is and how to mobilize them. The tool also helps to be realistic about turnout: you don’t have to sell out the venue every night, as long as your choices align with your organizational goals.’
Cultural organizations usually have various goals: not only occupancy and revenue but also societal goals, such as programming a diverse offering and reaching new audiences. The DIP tool can support both types of goals: not as a determining factor but as an aid. The initial results show that using the tool pays off: it accurately estimates the expected turnout of a performance.
Black box
Some people find it unsettling that the tool operates on artificial intelligence, Udo de Haes notes in the conversations he has. ‘It remains a black box into which you feed a lot of valuable data. Moreover, people expect perfect outcomes. That’s not always possible. The goal is for the tool to function better than one person could, complementing the expertise of the programmer.’
The system continuously improves itself by checking its own predictions. Grooteman and Udo de Haes are also constantly looking for ways to optimize the tool. For example, the predictive model is currently being tested with a few theaters, thanks to funding from Innovation Labs. Additional financing is needed to bring the tool to market.
The ambitions for the future go beyond just deploying the predictive model. ‘What other information can we provide about a venue? How do we collect data about creators who are just starting out? What information do programmers need to use the tool as effectively as possible? We are working on all these questions,’ Grooteman sums up. ‘We want to serve the sector as best as we can.’
Tips from DIP and Predictive AI
Let humans and AI collaborate. Two always know more than one. Use artificial intelligence not to eliminate human roles but to fill in human blind spots.
Combine data forces within your sector. By collecting information together, you gain more insights than you could on your own.
Continue to define your own strategy. Use artificial intelligence to pursue predefined goals. Ultimately, you are in control.
Author: Anne van den Dool
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