We find our information on websites and buy tickets through ticketing systems instead of at the box office. We tell friends about performances, concerts, and exhibitions at parties, but also via messages and chats. In short, we create a lot of data through our online presence, and your audience does too. By collecting (some of) this data, you can get to know your audience. Read below how to do that.
This is how you approach a data analysis
Formulate your goal
Every data analysis starts with formulating your goal. Define this goal by consciously deciding not to do certain things. The more the goal aligns with the objectives already present within your organization, the more effective it will be. Below, we help you get started with two possible goals.
Come up with questions
From the goal, think of the questions you want the data to answer. Data on its own does not provide insights. A list in Excel with all sales data from the past five years says nothing about where you can find your audience. Insights from data only emerge when a question is posed to the data. The more specific the question, the more specific the answer and the actions you can take. Below the step-by-step plan, you will find two examples.
Come up with questions that match your goal. Only then can you extract valuable information from your data.
Choose a data source
If you want to learn more about the needs of new or existing audiences, segmentation can be a good tool. If you want to know when to send an email, link transaction data to your newsletter data. In short, there are many possibilities. Don't hesitate to ask for help; much is possible. By hiring external expertise, the effectiveness of the answer can be significantly greater.
Evaluate the results
If done correctly, the results should provide a concrete answer to your question. With this answer, you can ask a new question or set up an action.
Two examples: repeat visits and new audiences
Cultural institutions often have the following goals: reaching the existing audience again or tapping into a new target group. Data analysis helps you to understand these issues. Below, we provide two examples to show you how such research can proceed.
Goal 1: Increase repeat visits among the existing audience
We see in several areas of the cultural sector that visitors are returning less frequently. Possible questions for this goal are: What is the ideal time to email my current audience (for example, just after they have attended or one week later)? You can investigate this with A/B testing. Which target group attends which programming? Work with segmentation models. Is there something they are missing now, causing them to visit less frequently? You can ask this in a survey.
Goal 2: Understand the needs of new audiences
If you are working to understand the wishes and needs of new audiences, it is important to look at sources outside your own data. This audience is not yet known. Questions that can be asked include: Which target group is present in my city but not yet in my institution? What are their characteristics? Are there colleague institutions serving a different target group with whom we can collaborate? You can investigate this through segmentation; the Cultural Target Group Model can help you with this.
Podcast Culture Shift Season 3
Understanding what your audience does, and especially what they don’t do, is essential. The British Design Museum in London uses data-driven audience management to improve their visitors' experience.
In the third episode of Culture Shift (Season 3), host Anic van Damme, sidekick Splinter Chabot, and innovation expert from the Rijksmuseum Evita Goettsch discuss the approach of this museum.
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