Understanding users takes more than just numbers or personal stories. It takes both. Big data helps you see what is happening across your product. Thick data enables you to understand why it is happening.
Big data gives you scale. Thick data gives you depth. Used together, they create a complete picture of the user experience and support better decisions.
What big data shows
Big data is made up of large sets of behavioral information collected through digital tools. It comes from user activity like clicks, views, time on task, page visits, conversion rates, and feature use. This data is typically tracked automatically and analyzed at scale using tools like Google Analytics, Amplitude, and A/B testing platforms.
Big data answers questions such as
- How many users completed a specific task
- Where users tend to drop off in a process
- Which version of a feature performs better
- How engagement varies between user segments
It helps you spot trends, measure outcomes, and make evidence-based decisions with confidence.
What thick data explains
Thick data focuses on the personal, emotional, and contextual side of user behavior. It comes from direct interaction with users through interviews, usability testing, field studies, diary studies, or contextual inquiry.
Thick data answers questions like
- Why users are confused, hesitant, or frustrated
- What motivates users to act in a certain way
- How emotions and environments shape their experience
- What deeper needs or pain points drive behavior
It helps teams empathize with users, uncover hidden insights, and design for real human needs—not just surface behavior.
How each type of data is collected and analyzed
Big data is collected through tracking tools, analytics platforms, product logs, and automated systems. It is often handled by data analysts or data scientists using tools like dashboards, statistical software, or programming languages such as SQL or Python.
Researchers collect thick data through conversations, observations, and open-ended studies. It is often recorded in transcripts, notes, and videos. Analysis involves identifying themes, building narratives, and synthesizing insights using qualitative methods like coding, affinity mapping, or thematic analysis.
Big data requires technical skill and statistical reasoning. Thick data requires deep listening, empathy, and synthesis.
Why do you need both
Relying on one type of data gives you an incomplete view. Big data shows the “what” but often misses the “why.” Thick data shows the “why” but not how common that behavior is.
Using both together lets you:
- Identify patterns and understand the reasons behind them.
- Confirm or challenge assumptions.
- Prioritize problems based on scale and impact.
- Design solutions that are both useful and meaningful
- Create experiences grounded in both logic and empathy.
For example, big data might show a drop in task completion. Thick data might reveal that users feel overwhelmed by unclear instructions. Combined, this insight can lead to better design decisions.
Strengths and limitations
Big data is suitable for
- Measuring behavior at scale
- Tracking product performance over time
- Running experiments like A and B tests
- Supporting decisions with clear metrics
Its limitations include
- Lack of context and meaning
- Difficulty identifying cause and effect
- Risk of misunderstanding data without human insight
- Requires technical tools and skills
Thick data is suitable for
- Understanding user motivations, emotions, and context
- Discovering pain points and unmet needs
- Generating ideas and improving empathy
- Supporting early design decisions
Its limitations include
- Small sample sizes
- Time-intensive collection and analysis
- Limited ability to quantify patterns
- It may be harder to communicate to data-driven stakeholders
Key takeaway
Big data tells you what users are doing. Thick data tells you why they are doing it. Both are essential.
Together, they help you make smarter decisions, solve real problems, and build experiences that truly connect with users. Big data brings confidence through numbers. Thick data brings clarity through human insight.
Tools like Userlytics allow teams to gather thick data at scale through usability testing, interviews, and user recordings. When paired with behavioral analytics, you get a full view of the experience, from what users do to how they feel, and everything in between.
