Designing great products isn’t just about creativity or intuition. It’s about understanding real people, their challenges, and how they use what we build. At BrightHR, that means grounding our design decisions in evidence, not assumptions.
Even the most experienced designers, myself included, are not the users. We bring our own perspectives, but they never perfectly reflect the reality of a small business owner trying to approve holidays on their phone, or an HR manager uploading staff documents during a busy Monday morning.
That’s where data-driven design comes in.
What We Mean by Data-Driven Design
Data-driven design is about making decisions based on insight, not opinion. It’s the ongoing practice of using real evidence from user behaviour, feedback, and testing to shape what we build, prioritise, and improve.
At BrightHR, this mindset runs through everything we do. From how we plan usability studies to how we measure adoption in Power BI, every design decision is supported by data.
A designer’s instinct is valuable, but when it’s paired with data, it becomes powerful. It’s the difference between guessing what might work and knowing what does.
The Two Sides of Design Data
When we talk about design data at BrightHR, we usually split it into two complementary types: quantitative (what users do) and qualitative (why they do it).
Quantitative Data
This is the measurable side of research. It helps us identify what users are doing, how often, and where they encounter friction.
We gather quantitative data from sources such as:
- Google Analytics 4 (GA4), to track event-level usage and engagement across BrightHR and Blip.
- Userpilot, which gives us visibility into feature adoption, engagement, and completion rates.
- Power BI dashboards, built from our data warehouse, which combine usage data, feedback, and operational trends to show performance over time.
- A/B comparisons conducted during usability testing sessions, used to validate hypotheses and assess which design performs better in controlled conditions.
This type of data helps us see what’s working and what isn’t. For example, if Power BI shows a drop in engagement for a feature, or GA highlights a high exit rate on a specific page, we know exactly where to focus our investigation.
Qualitative Data
If quantitative data tells us what’s happening, qualitative data helps us understand why.
We gather this through:
- User interviews and research sessions, where customers share how they use our products and what challenges they face.
- In-app surveys and feedback forms, often delivered through Userpilot prompts.
- Usability tests, both moderated and unmoderated, that help us observe real behaviours and friction points.
- Insights from internal teams, including Payroll, Sales (NSOs), and Service, who have daily contact with customers and can share recurring pain points or requests they encounter.
The best results come when we combine the two. The numbers tell us where to look, and the conversations tell us what to change.
Making Sense of the Data
Collecting data is only the start. The real challenge is turning findings into meaningful insight that informs design.
At BrightHR, we use empathy maps to visualise what our customers are thinking, feeling, and doing as they interact with our software. This helps our teams step into their shoes and design with context, not assumptions.
We also rely on affinity mapping to group and identify patterns from qualitative data. Whether it’s sticky notes on a FigJam board or tagged feedback in Airtable, clustering observations helps us uncover recurring themes and understand what matters most to users.
For quantitative insights, Power BI plays a central role. It allows us to visualise usage trends, engagement dips, or adoption growth across products. For instance, a spike in help interactions might signal confusion in a workflow, while a rise in mobile sessions could influence how we prioritise responsive design improvements.
Presenting Data to Win Hearts and Minds
One of the most important parts of data-driven design is how we communicate it. Data only becomes meaningful when people can see the story behind it.
When we present research or analytics findings at BrightHR, we don’t just show raw numbers. We:
- Pair metrics with user quotes and screenshots that bring context to the insight.
- Connect findings directly to business outcomes, such as retention, engagement, or reduced support demand.
- Use clear visuals from GA, Power BI or Figma, helping teams quickly grasp what’s happening and why it matters.
The aim is always to help stakeholders see the customer’s reality and understand how user needs align with business priorities. When we tell a compelling story with evidence, design recommendations become much easier to adopt.
Why Data Matters to Designers
It’s easy to think that “data” belongs to analysts, but for designers, it’s essential. Every decision, from a button label to an onboarding flow, benefits from evidence.
At BrightHR, data doesn’t replace creativity; it enhances it. We still experiment, prototype, and explore bold ideas, but we validate them through testing and observation. That balance helps us move fast while staying confident that what we release will truly help our customers.
Key Takeaways
- Designers are not users, and data bridges that gap.
- Use both quantitative and qualitative data to build a full picture.
- Present findings in a way that connects with people, not just numbers.
- Link data back to real user needs and measurable outcomes.
- Keep the process continuous: observe, test, learn, and refine.
At BrightHR, this approach has become second nature. Every initiative, whether improving our holiday booking journey, enhancing Blip’s mobile experience, or developing new AI features, begins with the same question: what does the data tell us?
In short:
Data doesn’t replace design instinct. It strengthens it.
When creativity and evidence work together, we build products that don’t just look good, they work brilliantly for the people who rely on them every day.