This post is part of our “Optimizing Your Arts Marketing Practice” blog salon.

Making the case for audience research

To communicate effectively, it really helps to know who you’re communicating with. As an arts marketer communicating on behalf of an organization, audience research is one of the most important tools we have to understand:

  • who our audiences are (or who we could newly bring into the fold)
  • what our audiences want, think, or respond to
  • where (and how big) the opportunity is if we launch a new program or performance
  • a perspective on how the status quo is going for our current audiences and therefore how much we should invest in changing our current approach

Using audience research to find the answers to those questions helps ensure the rest of our marketing budget is wisely spent and more likely to achieve our goals.

Audience research also is an integral part of being a diverse, equitable, and inclusive organization. If we only rely on the insights of our internal stakeholders to make decisions, we miss out on the diversity of perspectives from our audiences. No matter how large the organization or how diverse the staff, it’s impossible to capture the rich diversity of characteristics, insights, and lived experiences of all the many people who are among our current or potential audiences.

Even with all the benefits that audience research brings, it’s rarely planned for and budgeted into our marketing efforts or our strategic plans. Sometimes that’s because we’re not sure where to start or what an effective audience research process looks like. If that’s the case for you, come on up to Seattle for the National Arts Marketing Project Conference next month to learn more about a practical guide to actionable audience research. Read on for how to get the most out of your audience research process by balancing quantitative and qualitative approaches.

Data-driven approaches to getting to know our audiences

Surveys are one of the most common quantitative methods for collecting information about our audiences because most surveys tend to count data points (i.e. what percent of respondents said X). During an audience research process, you might also leverage an existing data source (like census data or your organization’s website analytics), conduct A/B testing (showing some audiences version A, showing different audiences version B, and comparing the response to each), or undertake a data-heavy observational study (measuring dwell time at an exhibit or biometric responses to a performance).

These audience methods are good for answering questions around who, what, and how many. As in: who are the types of people in our audience; what do they want from our organization or from their experience at an arts event; and how many people out there might be interested in something we’re considering doing.

Benefits to data-driven methods of audience research:

  • Scalable. You can collect and analyze more data points from more people. This larger set of data provides a higher confidence that what you discover in audience research applies to most people and allows you to find more nuanced differences between groups.
  • Cheaper. These methods typically require less time and money, which also makes it easier to collect information repeatedly in order to discover longitudinal trends, and across many demographic profiles for a more comprehensive analysis.
  • Less subjective. Data isn’t totally objective—it’s always filtered through the lenses and biases of the data collector—but having a collection of data points makes it easier to spot patterns and more likely that everyone who looks at the data agrees about what it means.
  • More truthful. Anonymous surveys and unobtrusively observing the behaviors of audiences can sometimes elicit responses that audiences wouldn’t feel comfortable sharing with us directly.

Challenges to data-driven methods:

  • Sensitive topics are tricky to navigate in a survey where you don’t have a lot of time to explain what you mean or make sure the audience feels comfortable with a line of questioning.
  • You have a predetermined, limited range of question topics and answer choices. The wild new idea or totally unexpected result rarely comes from a data-driven approach (alone) because there isn’t an opportunity to take the research question in a new direction based on the responses you’re getting.
  • Data typically can’t tell you why something is happening, only that it is happening. To get at the root of the reason why someone does or believes something, you often need a conversation.
Human-centered approaches to getting to know our audiences

Interviews are one of the most common qualitative methods to collecting information about our audiences and they can happen in many formats: in person, via phone, one-on-one, or in small focus groups. Depending on the research questions, you might also conduct user testing (watching audiences interact with an early version of something and asking follow-up questions about their experience) or ethnographic studies (watching audiences in their own environment to discover traits or behaviors the researcher wouldn’t have known to ask about).

These audience research methods are good for answering questions around why and what else. As in: why is this potential audience not engaging with our organization yet; or what else could we do to better serve our existing audience?

Benefits to these more humanistic methods of audience research:

  • Dynamic. You can change your approach on the fly based on what you’re hearing from the interviewee, you can take more time to explain or dive into a complicated issue, and during sensitive areas of discussion you can read the room and redirect conversation.
  • Immediate results. Sometimes all you need is one response to a user test to know something isn’t working the way you intended. Depending on your prototype (your early version of something), you might even be able to make changes in real time in response to audience feedback.
  • Stories are memorable. As you think about using the results of audience research to inform your practices, I often find that stakeholders are more likely to remember the story of a single audience member’s reaction to something than the percent of our audience who shared a similar reaction. Evocative stories typically come from these human-centric research methods.

Downsides to qualitative research methods are basically the inverse of data-driven methods:

  • Not as representative of the entire population because you’re only capturing insights from a limited pool of people.
  • Not as cheap to conduct this type of research because you are likely to need more time from a facilitator and more budget to incentivize audience participation.
  • Not as easy to find the threads of meaning in text-based transcripts or photos/video without a skilled researcher on hand.
  • Not as reliable to hear truthful answers to difficult questions; audiences are more likely to bend their answers to fit what they think you want to hear when they have to face you directly.
A balanced approach is best

Each type of audience research helps fill in the gaps from the other method. What people say is not always representative of what they do. Balancing quantitative and qualitative approaches shows you intention and action. Some stakeholders will only trust the data in aggregate, while others will latch onto a quote from a single individual. It’s best to include both types of research to make your final recommendations for change more convincing.

Throughout the research phase, try to conduct quantitative and qualitative approaches in a parallel, iterative approach so that insights from each can inform the other. You might:

  1. Start with a tiny bit of qualitative research to make sure you’re generally on the right path and have the opportunity to test potential questions.
  2. Scale up those questions to larger groups via quantitative methods that allow you to collect and analyze lots of data points.
  3. Use all that data to identify key lines of questions for your qualitative approach around “why” you’re seeing what you are in the data points and “what else” the data-driven approach might have missed.
  4. Return to the data set(s) if you uncover something unexpected in conversation and observations.

Want more tips on audience research? I hope to see you in Seattle for the NAMP conference Nov. 9-12, and join me for my session, “A Practical Guide to Actionable Audience Research.”