We find out what’s going on via websites and buy the tickets through online ticket sellers rather than at the box office. We tell our friends about the shows, concerts and exhibitions we have been to when we are at a party or via apps and chats. In short, we create an incredible amount of data through our online presence, as does your audience. You can get to know your audience by collecting all or some of this data. Below we will tell you how to do this.

How to analyse data

Formulate your objective
Every data analysis starts with the formulation of an objective. It helps to define this objective by consciously choosing not to do certain things. The more this objective is aligned with the existing goals of your organisation, the more effective it will be. Below we help you get started.
What questions would you like answered?
Using the objective as a starting point, consider questions you would like the data to answer. Data by itself does not tell us anything. A list in Excel that shows all the sales data of the past 5 years does not tell you anything about the possible locations where you might find your audience. You can only derive insights from these data if you pose a question. The more specific your question is, the more specific the answer and therefore the measures you can take. We give two examples below.

Ask questions related to your objective. This is the only way to obtain valuable information from your data.

Select a data source
Segmentation can be a good method if you wish to know more about the needs of a new or existing audience. Do you want to know when an email should be sent out? Link the transaction data to the data in your newsletter. In other words, you’ve got lots of different options at your disposal. Do not hesitate to ask for help. There is a lot that can be done. The effectiveness of the answer can be significantly increased by engaging external experts.
Evaluate the results
The results should give a specific answer to your question. You can use this answer to ask a different question or to take action.

Two examples: repeat visits and new audiences

Cultural organisations often have the following objectives: to encourage repeat visits by their existing audience or to tap into new target groups. Data analysis can help you with this. Below we give two examples of how you can use data analysis.

Objective 1: increase the number of repeat visits by the existing audience

Some venues in the cultural sector see fewer repeat visits than others. Questions we could ask in this case are: what would be the perfect time to mail my current audience; for example directly after their last visit, or is it better to wait a week? You can research this with a/b tests. What target group visits what events? Use segmentation models. Does this group feel there’s something missing, resulting in a decrease in the number of repeat visits? You can get an answer to this question through the use of a questionnaire.

Objective 2: Identifying the needs of a new audience

It is important to look for sources outside of your own data if you want to identify the needs and wants of a new audience. After all, you don’t yet know who these potential visitors are. Some questions you could ask are: what target group lives in our city but does not yet visit my venue? What are their characteristics? Are there any sister organisations who serve another target group, with whom we could collaborate? You can get answers by using segmentation. The Cultural Segmentation Model (Opens an external link) can be useful here.