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What data does your cultural organization have on hand?

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Are you aware of where your arts/cultural organization is collecting all this data? And what can you do about these data?

The world is living and thriving on data, the legitimate ones. In this post, I will highlight some areas where data capture happens.

Guest Journey

Let's map a guest's journey to an organization.

  • It can be individuals or a group of people.

  • The first touchpoint of data would be at the parking lot.

  • If they are walking in, then it would be the ticket counter.

  • Once inside, they would stop

    • at the performance/exhibits

    • cafeteria

    • gift shop

    • paid experiences.

  • Audience interactions with your staff have a wealth of data

    • Their queries

    • requests for facilities like wheelchairs, audio guides or tours.

  • Some observational data are

    • washroom breaks,

    • where people rest,

    • what holds attention.

  • Then, there is the interaction in digital.

    • the online ticket booking platforms

    • social media interactions

    • digital interactions - subscribers and Whatsapp messages,

    • calls received.

While some of these data are collected daily, the question is how often you use them. Some data is simple addition; others need time to analyze and interpret to make them readable. This information helps to strategize and utilize resources optimally.

Let's look at what some of these data can tell us.


The first choice of data analysis would be the number of

  • vehicles

  • cycles

  • walk-ins.

The secondary level of analysis can look at:

  1. how do the audiences commute? Perhaps a larger percentage of owned vehicles could indicate that many visitors are local.

  2. how long does each stay, and if there is a correlation between larger groups and longer time spent or vice versa

  3. Are there repeat customers (going by vehicles numbers)

  4. Will a parking incentive help? What would be the cost implication?

Ticket Counter

It can give insights about

  • the number of visitors.

  • highlight repeat customers and members.

  • An aggregation would talk about footfalls and timing spent at the organization.

Here is where the group's demographics and contact information are collected.

These data points can also reveal

  1. What kind of audiences visits the organization? Are there more individuals or families? Perhaps base this on groups with kids – it would be an assumption. Do they align with the target audience you have in mind?

  2. Can repeat audiences help them identify patterns and interests? Does it have a bearing on the programming?

  3. If there are promotions run, how do they affect footfall, and did they attract the audience it was intended for?


These are examples of what you can do with data over a timeframe. It would help you understand trends, one-off days etc. These questions take effort to analyze and add value to your stakeholders. It gets the attention of decision-makers, funders, government, and researchers.

The organization generates a wealth of internal data.

  • Be it resources consumed - electricity or water

  • resources wasted - food, waste generated and recycled

  • productivity studies - employees, volunteers, interns.

Like any other study - these thoughts come with their caveats.

Interpretations must be contextual to your organization. The data collection points might not always say the same things.

For a performing arts space, what time people come in might not be a great indicator. It could highlight the audience who comes early. A better question might be - does different performance timing attract or deter the audience? A late-night show might not attract people who stay far away and rely on public transport.

As you understand the information gaps, it will make the relevant data collected, and it is transparent.


I hope this information kindled some thought. I look forward to hearing about them in the comments section, or I am just a DM away.

What do you think are some other caveats where the above data collection won't work; or places that data is generated and often missed? Let me know below!

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