The key to an effective agile research strategy is understanding when — and when not — to use an agile methodology. Agile research is one tool among many that are available to researchers. Before we can think about where agile fits in processes and toolkits, we need to define the most basic delineation of research approaches. Traditionally, research data is thought of in terms of being either quantitative or qualitative. Here’s how we’ll define those terms:
- Quantitative data is measured in numerical terms. In other words, this data is chiefly valuable in its quantity: such as how many people respond to questions in a certain way.
- Qualitative data provides insight into feelings and reactions that cannot easily be translated into numerical values. This data is chiefly valuable in its descriptive nature: how are people feeling about a certain topic. This is revealed by choices of language and tone.
Agile research may be considered quantitative, qualitative, both, or neither. Getting caught up in that distinction isn’t as important as focusing on one of the most critical dimensions of agile: time. This means a key value of agile research is the timeframe in which it is delivered. Executed correctly, agile research is used early and often to generate a constant stream of data to inform decision points. Agile research techniques can generate a blend of quantitative and qualitative data that provide the necessary directional input at the right time to inform business decisions.
Any research methodology has corresponding strengths and weaknesses that must be weighed when selecting the right approach.
Because of the amount of structure inherent to a quantitative study, there is a significant amount of effort put into the design of these studies. It requires a level of research expertise to design, execute, and analyze a quantitative study. Typically, these studies are finite and provide a robust understanding of the subject of the research, which may be quite broad or address several objectives or hypotheses. The nature of most quant studies is that they tend to be time consuming to design and collect data.
Knowing how many people respond to a predefined set of response choices is useful, but it does not provide a full picture of people’s attitudes or context for why choices were made. It’s helpful to see that people select certain answers more than others, but researchers often need to understand why these people hold their opinions. That is a question most often answered through more in-depth, open-ended forms of research.
This is where qualitative research enters the picture. Qualitative research takes on a range of forms. It can be as simple as going to the nearest Starbucks and asking people to take a look at your website (sometimes called “café testing”). It can involve designing and moderating a focus-group discussion. It can be focused on collecting and analyzing videos of participants. The outputs of a qualitative study are unstructured or semi-structured in nature, such as open-ended text responses, recorded interviews, and/or transcriptions.
Qualitative studies often require people to invest a significant amount of time to share their thoughts with a researcher. Additionally, the results of qualitative studies do not have a set structure in the form of numerical values, which means it takes more time to synthesize the results. This is not to say there are not any tools to efficiently analyze qualitative data at scale. There are. However, they may not be fit for every purpose, and qualitative studies still typically involve a smaller sample size than quantitative studies.
There is an ever-growing need for research that falls between the rigorous quantitative research and traditional qualitative research. Agile research fills that gap.
Agile research provides guidance for making decisions that are too often informed by opinion, rather than data. It is research that is designed to be used early and often in the decision-making process, where the cost of making a misstep is outweighed by the cost of conducting the research.
Agile research studies are often used for:
- Early-stage discovery
- Idea, concept, or message testing
- Project or feature prioritization
The outputs of agile research studies typically:
- Are completed within days, not weeks
- Include feedback from a targeted set of participants
- Contain a combination of charts, graphs, and open-ended responses to inform a laser-focused decision point.
For more information, please download our white paper, The Quick Start Guide to Agile Research.
Roddy Knowles is VP of Research at Feedback Loop and, in addition to academic training in the social sciences, he has an extensive professional background in both qual and quant research. Roddy is a frequent speaker at industry conferences, award-winning author, and champion of research innovation and best practices. Passionate about giving back to the research industry, he currently serves as US Representative for ESOMAR, president of the Insights Association Southeast Chapter, and board member at MRII and WIRe.
We are grateful to Feedback Loop for sponsoring The Principles of Market Research course. Feedback Loop is the agile research platform for rapid consumer feedback. Farmers Insurance, Humana, Lending Tree, Uber, and other Fortune 500 companies trust Feedback Loop to bring the voice of the consumer into critical market decisions.