Strengths and Limitations of Qualitative Research

Strengths and Limitations of Qualitative Research

Qualitative research has the potential to complement quantitative data by providing depth and perspective to statistics.

At its core, qualitative research data stems from the human experience. It can open a window into audiences’ minds that quantitative data just cannot show, and paint a richer, more holistic portrait of consumer behavior. While quantitative research can highlight overall trends in attitudes towards a product, qualitative data can inform why those trends exist and how to shape a product to better suit a company’s audience.

Strengths of Qualitative Research

Adaptability

Qualitative research can change on the fly, based on reactions and responses by the participants as they come in. As a research session continues, researchers can ask respondents why certain products appeal to them more than others, giving the company a more grounded understanding of their customers’ opinions of their products.

Example

During a research session for an upcoming movie, data pouring in shows that respondents have fairly neutral feelings towards Ending A and Ending B. A good qualitative researcher can alter the survey instantly, asking participants to elaborate on what aspects of Endings A and B that they find appealing. With this information, the movie studio can come up with an ending that incorporates the positive elements from both endings.

Subjectivity

For businesses, understanding the why behind successes and failures guides decision making in the future. Through subjective questioning, qualitative research allows consumers to explain the rationale behind their behaviors, thus informing companies on how to modify their products to better suit their audiences.

Example

A bank has rolled out a new user interface for its mobile customers, but has seen a sharp downtick in mobile logins. Through a qualitative session, the bank can discover what about its new UI is challenging for customers to navigate through – whether it is usability, aesthetics, or simply difficulty getting used to change. Quantitative data proves that users aren’t logging in as much – but qualitative data highlights the exact issue that the bank can fix.

More Opportunity for Collaboration

Qualitative data inherently allows for greater collaboration, meaning that researchers of all backgrounds can provide multiple viewpoints on a single data set. For instance, someone with more experience in advertising might view the data through a different lens than a researcher with expertise in human psychology – leading to richer, more rounded analyses that take into account a gamut of perspectives.

Creative approaches

Qualitative research methods embrace the notion that everybody has a unique voice. By relying on description, qualitative discussions have the potential to let the audience take control, reversing the standard researcher/responder dynamic. Questions can be lighthearted, and the respondents can inject humor in their answers.

Example

A snack food company is testing out a new mascot for its signature chips. Initially, the questionnaire asks participants whether or not they like the new mascot, but a few minutes into the session, the researchers start to allow for a bit more fun. Participants start replying with word associations, exaggerated reactions, and their own suggestions on how to make the mascot better. Not only is it a more enjoyable experience for the participants and researchers, but this also provides genuine opinions that quantitative research cannot show.

Limitations of Qualitative Research

Time and Labor Intensive

Qualitative research requires gathering troves of personal opinions, perspectives, and experiences from many people. As a result, collecting ample data from participants takes time, and compiling the data isn’t as simple as plotting it on a graph. The very nature of qualitative data means that researchers have to sift through each individual response to form a more thorough understanding of why participants felt or reacted to a product in a certain way. Since the responses are often descriptive rather than numerical, poring over the results will inevitably take more time than parsing quantitative data.

Correlation Does Not Equal Causation

You’ve probably heard way too often, “Correlation does not equal causation”. Well, the same applies to qualitative research. While it often support findings from quantitative research, it can be hard to prove a causality between the two. Discussions and questionnaires can produce thoughtful responses that bolster quantitative results, but researchers might hesitate to immediately draw a line between the two; more research is often necessary, adding to time and labor intensity.

Patterns Can Be Hard to See

One of the strengths of quantitative data is that results can be fairly easily replicated, proving or disproving hypotheses over large sets of audiences. Qualitative data, due to the breadth of emotions, reactions, and responses from participants, doesn’t have the same replicability. One responder might have a completely different answer to a question than another, making broad categorizations difficult.

How Is Invoke Different?

Invoke Is Big Qual. An Invoke LIVE session brings every stakeholder together on a consumer-led journey that leads to a real-time decision.

  • It’s inclusive, bringing together showrunners, marketing, brand managers, business executives, and market researchers on an hour-long conversation with your target audience.
  • It’s conclusive, enabling you to probe audience sentiment, test concepts on the fly, attain clarity about strategy and message – and make the right decisions, often by session’s end.
  • It’s organic and illuminating, offering rich and sometimes unanticipated insights into how your audience view you and their world: the Why behind the What.
  • It’s qual and quant simultaneously, with audiences of many hundreds in a single session.

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Dushyant Naresh About the author
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