In research planning, it’s tempting to gravitate toward numbers. But communicators often need qualitative data instead.
By Mallory Peak, PhD
Vice President, Strategy and Insights
In this era of “data-driven communications,” many companies and organizations are averse to investing in research. They might spend big budgets on advertising — but not a fraction of those budgets to test the ads’ effectiveness.
Research programs can be cost-effective while prioritizing methods that yield information to help you make the best decisions. And when you make the investment, it pays off — helping your organization reach your actual audience, uncover depth and nuance, and avoid wasting budget on ineffective or even harmful communications.
Companies facing more data restrictions.
Privacy laws and stronger protection of consumer data are preventing easy access to market data. So companies and organizations face more pressure to develop their own research programs. In pursuit of data-driven communications, they are tasked with understanding their audiences’ behaviors and evaluating the efficacy of their own communications programs.
They sometimes find that these tasks get expensive and ask themselves questions like these:
Instead of compensating focus group participants, can we just include anyone who’s willing to show up for free?
Instead of recruiting a representative sample of perspectives, can we just share a survey with our personal contacts?
Why should we engage people for qualitative insights if we already have click-through rates or can buy market research data that’s out of context?
Some organizations are saying, “Yes, and yes, and let’s just look at those click-through rates!”
But along the way, they’re discovering a few things.
They aren’t measuring much that’s meaningful.
Quantitative research focuses on numerical data, using surveys or analytics to measure trends, preferences, or behaviors across a big sample. Quantitative methods help measure the frequency of something: an attitude, a belief, a behavior.
Qualitative research, on the other hand, is exploratory. It reveals underlying motivations and opinions through methods like interviews, focus groups, or observations.
In research planning, it’s tempting to gravitate toward quantitative methods. Most people are more familiar with quantitative data. Putting a hard number to a phenomenon seems more “legitimate.” But communication decisions more often require qualitative data to understand why an attitude, a belief or behavior persists.
This bias often leads organizations to try to engineer quantitative methods to get qualitative findings. Have you ever conducted a survey with mostly open-ended questions? You probably didn’t really want to measure something. You wanted to talk to people about the breadth of their experiences, not count them. The qualitative method won’t get you what you really need.
Traditional market-research data and AI tools leave a lot of people out.
Effective recruiting for a survey or focus group means intentionally creating a sample that represents the audience you want to engage. That means partnering with community organizations, engaging people one on one, or adapting research methodologies so they’re accessible by people of different ages who have different abilities and cultural norms.
All that can feel complicated and get expensive. So, to save on costs, organizations often end up engaging people for research who they already were reaching with their messages — because they’re the easiest to reach. Everyone else continues to be left out.
Secondary methods of research, or research that exists already, face similar challenges. Market research focuses on majority opinions. People of color, queer people and religious minorities are often left out, or they’re included so minimally in U.S. market research that their opinions in summation resemble stereotyping. For regional campaigns, market research tools are increasingly limited by data restrictions, sample size and timeliness.
And AI, while fast and convenient, just regurgitates biases in existing content.
Assumptions are expensive.
When companies and organizations invest in effective research plans, they avoid spending money to build creative that doesn’t work and more money to place it online, on TV or other media. These organizations risk paying money to alienate their audiences.
Communication professionals are often encouraged to work from intuition. We learn that being “data-driven” means combing the quantitative data readily available and taking a calculated risk.
But our job is to reach hearts and minds. So much of effective communication is in the details – in the way we tell a story, in the ways we represent real people, and the ways we build connections with each other. That goes for research, too.