Anywear’s Post

Let's chat about how researchers gather data. 🎯 There are two key methods: listening and observing. 👂 When we listen, we uncover the "why" behind actions and decisions, understanding motivations, beliefs, and values. 👀 Observation focuses on the "how," watching habits and behaviors to gain insights into choices. During data collection, researchers use techniques like viewing physical spaces, sharing digital activities, drawing emotions, and filling, sorting, or plotting information. 🖼️💬 Stay tuned for more insights on analyzing and synthesizing data! #UXResearch #AnalysisSynthesis #QualitativeData #ExpertInsight #usabilitytesting #userexperience #usertesting #userresearch #data #ux #lyssna #analysis #synthesis

Drowning in qualitative data? Don't fret! Let's explore two popular methods that can help you make sense of it all: thematic analysis and affinity mapping. Thematic analysis offers a structured approach to uncovering key themes, while affinity mapping provides a visual and collaborative way to identify patterns. Here's a quick rundown of how each method works. Thematic analysis: 🔖 Collect your data 🧩 Break it down into manageable snippets 🏷️ Code each snippet to categorize themes 🔄 Explore relationships between themes 💡Interpret themes to uncover meaningful insights Affinity mapping: 📊 Collect qualitative data from your study 📌 Visualize data snippets on a board 🌟 Group similar elements into clusters 🔎 Analyze clusters to identify patterns and insights Ready to unlock the full potential of your research data? Dive deeper into our latest article by UX expert Michele Ronsen for insights and practical tips - https://loom.ly/Iae4HBk #UXResearch #AnalysisSynthesis #QualitativeData #ExpertInsight #usabilitytesting #userexperience #usertesting #userresearch #data #ux #lyssna #analysis #synthesis

The 🔥 debate 🔥 about the relative merits of qualitative and quantitative UXR methods is almost as epic as the one about “Star wars” vs “Star trek”. Qualitative researchers talk about the dangers of relying on dry metrics and the lack of depth, while quantitative researchers scoff at N=8 and anecdotal evidence. Well I say, don’t hate, triangulate! Quant and qual need to rely on each other to create a 3D picture of the world just like our two eyes that see slightly different 2D views from their vantage points. Working together is pivotal to deliver reliable, rich insights that have both depth and breadth. ❓How can quant and qual work together? ✅ Qual can be an input into quant, where qual is used for initial exploration of a phenomenon in interviews or diary studies and quant is used for confirmation and understanding of the prevalence of the findings in surveys or logs. ✅ Quant can be an input into qual, where behaviour observed in logs analysis or surveys is explored in depth in qual in order to understand the underlying reasons and motivations. ✅ Quant and qual can be conducted at the same time and combined at the stage of insight generation where quant is used to confirm the phenomenon at large and qual is used to add color and depth. #ux #uxresearch #userexperience #userresearch #data #datascience

It is never only Qual or only Quant. It is always Qual + Quant that will give you the edge.

Absolutely! I always use a mixed methods research approach for my research. The quantitative data in the beginning of my research bolsters my qualititative data anaylysis (depending on the project).

Exactly 👌! Very well said Inna Tsirlin, PhD 😌! I’ve no idea why qual and quan sometimes appear as opposing forces, each pulling one end of the thread 🤔, when they actually complement each other🤷🏻♀️ #uxresearch #uxr #uxresearcher #qualitativeresearch #quantitativeresearch #mixedmethods #UX

Sometimes, you just don’t have enough sample… based on the niche nature of the audience or otther realities around timing/ budget. Micro Modeling provides an alternative to improve your business decisions with meaningful market insights.

Did you miss our live webinar? Catch it now on-demand! Thank you to Ben Cortese & Allie Pierce, PhD for their insightful session on Micro Modeling — our framework for using small sample alternatives in research, especially for trade-off activities. This webinar is a must-watch if you’re a market researcher, design researcher, UX professional, or data analyst working with limited sample sizes. See the first link in the comments to watch the webinar any time! #Webinar #MarketResearch

In celebration of #NationalPiDay, we are slicing up data viz by sharing tips on why many UX practitioners avoid using pie charts. • Pie charts are less effective for comparing #data. It is challenging for users to accurately compare sizes, angles, and proportions of different segments, especially when there are many segments or they are similar in size. • Pie charts require more space to display the same amount of information compared to other charts. This can be problematic for space-constrained situations like mobile interfaces or dashboards. • For folks who are #neurodivergent or have visual impairments, there may be difficulties distinguishing between different segment colors; excluding certain users from engaging with the data. Pie charts can be visually appealing but they can be less effective when conveying data. You can always opt for alternative visualization techniques that have better #usability and user comprehension: like the trusty bar.

I had the pleasure of participating in the Spring Data Visualization Society mentorship program and had some amazing sessions with Katie Bieber and Luciana Berghella Junqueira. If you're looking for a visualization specialist, I highly recommend Luciana Berghella Junqueira. Her expertise and insights will be invaluable. #DataVisualization #MentorshipProgram #ai #projectmanagement #productdesign #UX #userexperience #usability #business #strategy #innovation #productstrategy