Getting to Know Your Audience – Data Gathering for Beginners • Arthouse Cinema Hub

How well do you know your audiences? In the day to day rush of running a busy venue, it can be hard to carve out time for statistics and analytics. For many working in the cultural sector, “data” can also be a bit of a scary word, and it’s not always easy to know where to start if you want to begin collecting more meaningful information about your visitors. Nevertheless, getting to grips with who your audience are, how they behave and what attracts them to your cinema, can be a gamechanger, helping you make better, safer and more efficient decisions, backed up by facts.

Ahead of European Arthouse Cinema Day 2025, we were joined by Bernd Zickert, (General Manager) and Nathalie Kaiser (Manager, Statistics and Research) from the media measurement and analytics company Comscore, for a free workshop introducing some of the fundamentals of data gathering in the arthouse cinema sector. Here are some key takeaways from their presentation:

There are three main kinds of data you can collect. Factual data is objective, trackable and numbers-led, e.g. admissions, showtimes, dates, concession sales, click rates on social media. Observed data is collectable and subject to interpretation. This is information which you observe without talking directly to the audience, such as perceived age and gender of the audience, the group setting, and the reactions of audiences leaving the screening. Finally, poll data is information you gain through talking to your audience, usually through surveys. This category could include exact demographics, preferences, behaviours, motivations, ratings and perceptions.

Different kinds of data have different pros and cons. 

Factual data is objective and easy to track, but it can also be limited in terms of insights because it doesn’t tell you the “why”, the reasons for the patterns you see. Observational data allows for deeper insights, but can also be time consuming and subjective, which makes interpretation harder. Poll data offers unique knowledge and can be converted into a customer loyalty tool, because it tells you what your audiences really care about, but it can be difficult to obtain because you need expertise and time to analyse the results.

Looking at how key titles are received at your venue now, can help you predict how future releases might perform.

Start by determining the criteria which might influence the reception of your chosen title. Choose a few elements that might be most relevant for you to track, e.g. the film itself (the genre, the talent, critical reception), the date, the showtime, the day of the week, the weather, the number of tickets sold, the audience gender split, and their approximate age. You also might want to take some general notes about the group setting. Are there lots of couples in the audience? Mainly families? How are concession sales? Are there any holidays or rival local events that might be affecting audience numbers? How are your audience reacting as they leave the cinema? The more you track the better, but if your resources are limited this can be as simple as noting any clear trends to get you started.

Once you establish your criteria, you can start building a database. This can be a straight forward spreadsheet, with one row per screening recording your results under key headers. Ideally, talk to your co-workers to ask them to support the data collection. Missing one or two screenings is not a huge problem, but generally you need to be consistent to get meaningful results. It’s best therefore to try and track most of the screenings for one title at first, to get the process started. As you continue, you’ll start to figure out which factors are the most relevant for future evaluation.

When you have your data, look for patterns.

Start by looking at the audience as a whole. First look at gender distribution, age and group setting, and see what similarities (if any) emerge across the screenings. The look at the wider picture. Do concession sales show any trends? How were these factors affected by the showtime or the weather outside? Do audiences attending the screenings in different timeslots leave the film with different emotional reactions? How do weekdays compare to weekends? When you see patterns, you can start to formulate a hypothesis.

Once you have a hypothesis, test it out.

Identifying bigger picture trends – e.g. “the audience skews to couples aged 30-50 for this title” – but also where your data deviates from these trends – “except in the late night screening slots, which were dominated by male friend groups under 30” – can help you draw more detailed conclusions. Once you have a hypothesis, you can find more data to see if that backs up your hunch, or you can try acting on your idea to see if that affects results.

For instance, if weekday screenings are dominated by loyalty card holders, it might make sense to run a targeted campaign around your loyalty cards over the weekend, when it’s more likely to connect with people who are not already members. If your weekday evenings are dominated by couples, you could try a date night ticket-concession promotion and see if that increases concessions sales. If a film is very controversial, you could offer post screening discussions or programme notes to build a conversation with your audience.

Ultimately, good data reduces risk and makes decisions easier

Knowing your audience can help you be more specific in your selection of films, work out which time slots work best for certain genres, nail down a target audience and speak directly to the people who the film has been made for. Ultimately, getting these factors right will increase customer retention and satisfaction, and help you make smarter, safer programming and marketing decisions.