Qualitative research is a valuable method for exploring complex topics that cannot be easily measured quantitatively. With in-depth interviews, focus groups, and observations, researchers can obtain rich and nuanced data to gain a deeper understanding of human experiences and perspectives. However, conducting qualitative research does not come without its challenges. In this blog, we’ll explore the basics of qualitative research, common challenges, best practices, and how generative AI can assist with taking qualitative research to the next level.
What Is Qualitative Research?
Qualitative research is a method that seeks to understand human behavior, beliefs, attitudes, and experiences through non-numerical data. Researchers collect data through open-ended interviews, focus groups, and observations to develop an in-depth understanding of a particular topic. It allows for a flexible approach to data collection and analysis, enabling researchers to explore unexpected findings and generate new theories.
Through qualitative research, researchers are able to capture insights that explain the “why” of consumer behavior. At the heart of a customer-centric strategy lies the “why” and “how” behind interactions with brands, emphasizing the focus on feelings and human understanding. This is beneficial for many reasons, namely: gaining a deep understanding of audience emotions, motivations, and needs.
Top 5 Challenges Related to Qualitative Research
While qualitative research allows organizations to understand their consumers on a deep level not possible with purely quantitative data, qualitative research studies also present unique challenges.
- Study setup and design: Researchers must ensure that their study design is unbiased and consistent, that their data analysis is reliable and credible, and that deep understanding can be applied at scale.
- Survey respondents: In order to design a strong qualitative research study, it’s important to find the right respondents. Writing screening questions that capture the target audience is difficult, and can be especially hard when the study seeks qualitative findings rather than quantitative ones.
- Moderator selection: To ensure the study is designed in an unbiased fashion means that moderators need to understand how to guide the conversation in a way that provides honest, helpful feedback.
- Data analysis: Due to the quantity of data and information gathered through qualitative research, it can be both time consuming and challenging to effectively pull out key themes and information. This is where Generative AI has the potential to help reduce the time to summarize key findings.
- Extracting clear insights: Unlike quantitative research where findings can be categorized into clear “buckets,” qualitative research contains countless variations of how consumers feel about your product and brand. As a result, analysis at scale is a challenge, which can ultimately slow down the process of extracting insights that impact business decisions.
Qualitative Research Best Practices
To overcome these challenges, you should adhere to best practices when conducting qualitative research. Read on for a comprehensive list of best practices to apply to your research studies.
- Develop clear research questions: The difference between a successful study and an unsuccessful one where results are skewed comes down to the research questions. As you write your questions, avoid being biased or leading respondents to think a certain way (for example, “What do you like most about our product?”). It’s also important to focus on the experiences that actually happened for the consumer as they relate to your product, rather than generalized preferences. Finally, keep questions simple and direct; it’s important not to overwhelm survey respondents by asking for too much on disparate topics. Learn more about how to develop clear research questions in this blog post that includes strong examples of questions you can adapt and use for your own studies.
- Focus on attracting the right participants instead of any participant: The easiest place to start when selecting participants for your qualitative research study is to go back to your company’s roots: your target buyer personas. Be sure to include a mix of your buyer personas so you obtain a holistic view on how customers feel about your brand and its products. To narrow down the pool of participants to your buyer personas, conducting a pre-screening assessment is helpful. This way, you know for certain that you’ll be speaking with the people most likely to interact with your company.
- Use tried and true qualitative research collection methods: Live interviews and focus groups are established methods for collecting qualitative research data. In-depth one-on-one interviews allow you to drill into how consumers feel about your brand on a deep level. In a more private setting, people feel at ease to share their own personal experiences as opposed to potentially being influenced by a group. That being said, focus groups are a familiar and effective way of collecting data. This method is especially powerful if you want to spark conversation led by a skilled moderator.
- Pick a skilled moderator: A skilled moderator will understand how to get the most out of customer conversations. They will help the participants feel at ease and be an excellent listener who pays attention to details big and small. They should also know how to keep the conversation on track while ensuring that each participant has the chance to contribute. Lastly, a strong moderator will align with your vision for a discussion guide, and plan to moderate the discussion with your study hypothesis at the forefront of their mind. This leads us to the next element of qualitative research best practices.
- Do the work beforehand by crafting a strong research plan: You should have a clear understanding of how to create a research plan that includes a hypothesis and discussion guide. Specifically, as you craft a discussion guide, it’s important to keep in mind that you’re not writing a script. Instead, you’re writing a blueprint outline that includes key elements such as an introduction and specific questions, leaving room for the flow of the discussion to influence how you interact with participants. For an in-depth overview on crafting powerful discussion guides, click here.
- Make a plan of attack for analyzing the data: Your strategy for analyzing the research data in order to obtain impactful, meaningful insights needs to be considered from the start. Effective qualitative data analysis centers around seeking to understand sentiments, listening for certain words or themes coming up often, and making connections between demographics and survey responses. This can be difficult if everything is recorded via video and then translated into a written transcript, so having a simple way to watch short snippets of responses from multiple respondents and utilize tagging for certain words and emotions is critical to ensure your team is focused on the insights gained versus time spent organizing survey responses.
Moving Business Forward with Generative AI
Even for organizations who utilize qualitative research methods often, adhering to best practices without missing a beat can feel overwhelming. Thankfully, generative AI can assist with creating a strong qualitative research study from start to finish. By using machine learning (ML) algorithms, generative AI can identify patterns and themes in large datasets, assist with coding and categorizing data, and help researchers identify emergent themes. The labor-intensive aspects of qualitative research as described above can be reduced dramatically with use of Generative AI.
Much of the qualitative research process is spent on pre- and post-customer interaction, including survey setup and respondent screening, as well as data analysis. Utilizing generative AI to help with these aspects of research setup and data summaries at scale makes extracting qualitative insights easier than ever before. For example, with Discuss Genie you can quickly summarize findings and eliminate hours of analysis. Generative AI can take much of the guesswork out of qualitative research, allowing teams to unlock new insights and discoveries in a smarter and faster manner.
Empower your team with a purpose-built platform for enabling qualitative research that turns people’s experiences into insights using generative AI. Get to know Discuss Genie, your Generative AI qualitative research assistant built to make your team look like geniuses.
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