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EthOS vs. Traditional Qual Research Methods

EthOS vs. Traditional Qual Research Methods

Continuous vs. Momentary Insights

Traditionally, interviews and focus groups have been the backbone and default methods used when trying to understand people’s thoughts, behaviors, and experiences. These methods involve direct interaction and structured settings where a researcher guides discussions and inquiries. While these methods are highly effective at capturing detailed narratives, they are inherently limited by their momentary nature. These sorts of insights are more of a timestamp or snapshot of behaviors and thoughts at a specific point in time, which offer valuable but static insights.

One major limitation of these methods is their inability to track changes over time. Interviews and focus groups typically occur just once over a short duration of time, and they lack the longitudinal data needed to observe how perspective and behavior change over a lengthier time horizon. This can significantly impact the study of dynamic subject matter, where changes, patterns, and trends are crucial for comprehensive understanding.

EthOS addresses these limitations by enabling continuous data collection over extended periods of time. During studies, participants can document their experiences in real-time, providing a snapshot and a dynamic and evolving narrative that reflects a broader and more detailed spectrum of thoughts and behavior.

Participant Comfort

Typically, traditional research methods are conducted in research labs or meeting rooms where researchers and participants interact live—controlled, structured, and efficient. However, these sorts of conditions can inadvertently influence behavior and responses in unnatural and counterproductive ways. The presence of a moderator and the awareness of being observed can lead participants to act out of the ordinary, affecting the insights’ impact and authenticity. Participants may feel a need to perform or act in ways they perceive as socially desirable or give less feedback so as not to come off as negative or overly critical. These less-than-candid responses drawn during traditional methods can be detrimental to businesses trying to tap into the wants and needs of their customer.

For example, a team has set out to do some discovery research on daily stressors. The researchers may set up participants to share real-time entries about their challenges with household tasks and mundane daily experiences like the morning commute. These in-situ responses reveal richer detail and emotion than one may gain from a one-time interview. EthOS ensures that data reflect the true experiences that participants are having, which enhances the overall quality and reliability of findings.

Researchers can capture participant experiences anytime, anywhere

Anytime, Anywhere

With the ability to observe and collect information from a broad spectrum of participants regardless of location and timezone, companies can procure findings from consumers representing their user base.

Quantitative vs. Qualitative Data

Qualitative and quantitative data just work better together. Instead of solely qualitative data from an interview or quantitative data from a spreadsheet, the two data types can weave a compelling and insightful narrative into the spectrum of thoughts, behaviors, and motivations that drive your audience. Without one, the results can be narrowed and assumptive rather than broad and deep.

EthOS bridges that gap by offering researchers the opportunity to collect both quantitative and qualitative data. This combination provides more context and a greater holistic view of the customer experience. For example, to study the usability of a product, a team may use EthOS to gather qualitative feedback from a usability test as well as collect quantitative data from a large set of real user sessions. This dual approach enables correlations between measurable trends and personal insights, leading to more actionable and profitable conclusions. EthOS enhances the richness and depth by integrating both types of data.