Dashboards are a powerful way to present complex data in a glanceable, visual format—but only if they’re designed well. Unfortunately, we’ve seen far too many dashboards that fail in this aspect. Some are overloaded with data, others fail to highlight what truly matters, and many lack explanations, leaving users confused and frustrated. In this article, I’ll walk you through the core principles and best practices of designing a dashboard that’s not just visually appealing, but actually useful.

What makes a dashboard UI good?

Think about the last time you used a dashboard to find something. Maybe it was an online banking app to check your balance, an investment dashboard to track your portfolio, or a health app to review your vitals over time. Now, ask yourself these questions:

• What was your goal when opening the dashboard?
• What specific data did you need to achieve that goal?
• Did you find that data easily?
• If so, how smooth or frustrating was the process?
• How did that information help you make a decision?

If the experience was quick, intuitive, and useful, the dashboard was probably well-designed for your needs.

In my experience, a good dashboard UI follows three key principles:

1. Easy to understand – It presents complex information clearly, with explanations and hints to help users make sense of the data.
2. Glanceable – It has a clean, structured layout that lets users find key insights fast, without distractions.
3. Insightful – It guides users deeper into the data, offering tools for exploration while ensuring clarity at every step.

Let’s see these principles in detail and explore how you can achieve them.

Principle 1: Easy to understand

A well-designed dashboard UI simplifies complex data, making it effortless for users to interpret information. 

The ease of explaining a dataset is crucial. Users need to be able to look at the information and make sense of it without any external support. Make sure that the visuals have concise titles, clear and understandable names for the data, and well-written descriptions.

When designing a dashboard, don’t forget about the context. Users should immediately understand what they’re looking at, why it matters, and how to act on it. To achieve this, ensure that every visual, metric, and interaction is intuitive. Titles should be concise, and labels must be clear. Make sure to include descriptions, which should be written in plain language.

If a user needs extra guidance, help should be readily available. Tooltips, inline explanations, and interactive hints can provide additional context without cluttering the interface. For example, a small info icon next to a chart can display details about the data source, the meaning of the metric or the calculation method when hovered over. These small details make a huge difference in usability, and prevent frustration, too.

Best practices

• Design for different levels of data literacy – Some users are data experts, while others need simpler insights. Ensure the dashboard works for all audiences.
• Follow accessibility standards – Prioritize readability with high-contrast colors, clear typography, and a structured layout. Avoid jargon where possible.
• Use onboarding and tooltips wisely – Provide contextual help through tooltips and onboarding guides. Keep explanations concise and non-intrusive.
• Test with real users – Validate tooltips, labels, and onboarding flows to ensure they’re genuinely useful, not just added as an afterthought.
• Leverage AI for smarter insights – Implement context-aware explanations, free-text search, and adaptive layouts that respond to user needs.

Principle 2: Glanceable

A dashboard should provide immediate clarity. With a clean, structured layout, key insights should be visible at a glance, without distractions or unnecessary clutter. Users shouldn’t have to dig through layers of information to find what matters most.

When a user opens a dashboard, they have only a few seconds to find what they need. To test its effectiveness, let’s combine Steve Krug’s Trunk Test with a 5-second test.

Here’s how it works:

Imagine your user is blindfolded, placed in a car trunk, driven around, and then suddenly dropped onto your dashboard. They have just 5 seconds to scan the dashboard before being blindfolded again.

In that short time, can they tell where they are and what they should do next? If not, your dashboard UI, labeling, or visual hierarchy likely needs improvement.

Best practices

• Use colors and shapes intentionally – Leverage them to group information, highlight key data, or indicate trends (e.g., red for decline, green for growth). But avoid overuse: visual elements should enhance clarity, not overwhelm users.
• Focus on decluttering and reducing – As you’re adding a piece of information to the dashboard, double-check if it is really needed there. Ask yourself these questions:
  
  • Does this data really need to be shown?
  • Are we sure this data needs to be shown?
  • Does it have to be shown this way? Is there any other way to show it?
• A content-first approach ensures dashboards remain focused and effective. Before adding a new element, ask:
  
  • Does this data truly need to be shown?
  • Is this the best way to present it?
  • Could it be simplified or grouped with something else?
• Stick to familiar UX patterns and conventions – Dashboards are about efficiency, not visual novelty. Using well-known icons, layouts, and interactions reduces cognitive load and helps users find what they need at a glance.

Principle 3: Insightful

A well-designed dashboard does more than just display data—it helps users uncover meaningful insights. It serves as an entry point for exploration, providing interactive tools like filters, drill-down options, and contextual explanations that allow users to analyze data in a way that suits their needs, while still maintaining clarity at every step.

Users often won’t find the answers they’re looking for on the surface alone: they need the ability to explore, manipulate, and refine the data to reach deeper insights. Do you remember the five questions from the beginning of this article? A truly insightful dashboard ensures those questions have a clear, actionable answer.

To achieve this, structure your dashboard with a hierarchical layout that guides users toward discovery. Information can be revealed progressively, either within specific visuals or across the entire page, reducing cognitive overload while keeping advanced data accessible.

Best practices

• Use a hierarchical layout – Guide users from high-level summaries to detailed breakdowns, so they can explore deeper layers of data naturally.
• Implement progressive disclosure – Display only essential information upfront, revealing more details as users engage with the dashboard, right when they need it.
• Enable powerful search and filtering – Let users manipulate data easily through search bars, advanced filters, and sorting options to find exactly what they need.
• Leverage AI for contextual insights – AI tools can provide smart suggestions, anomaly detection, and natural language queries to help users make sense of complex data.
• Offer customization options – Allow users to rearrange, resize, or hide widgets so they can personalize their dashboard experience.
• Enhance interactivity with data visualizations – Instead of relying solely on static visuals, incorporate interactive charts, tooltips, and drill-down options that allow users to explore data dynamically and uncover deeper insights when needed.

How to create your dashboard UI?

1. Start with Research

Before designing a dashboard, conducting thorough research is essential. A dashboard isn’t just a collection of charts and numbers, it’s a decision-making tool. To make it truly effective, you need to understand who will use it, what insights they need, and how they will interact with the data.

Discovery Research: Defining the Foundation

Discovery research helps establish the purpose, audience, and structure of your dashboard. It can start with competitor analysis, proper desk research, combined with a set of interviews. Consider the following key questions:

• Who are your users, and what are their needs? Identify different user groups (e.g., executives, analysts, team leads) and tailor the dashboard accordingly.
• What decisions will they make based on this data? Every dashboard should help users take action, whether it’s monitoring performance, identifying trends, or optimizing workflows.
• What key metrics matter? Prioritize only the most relevant KPIs to avoid information overload.
• What is the context of use? Consider where and how the dashboard will be used:
  
  • Who will interact with it?
  • How often will they access it? (Daily, weekly, monthly?)
  • On what platform? (Desktop, mobile, integrated within another system?)
• Are you replacing an existing solution or building something new?  When you’re redesigning an existing dashboard, analyze pain points and limitations from the current version. If it’s a new solution, identify key user needs that need to be addressed.

Evaluative Research: Testing with Real Users

Once the initial design is ready, testing with real users is crucial to ensure the dashboard is intuitive, useful, and aligned with their needs.

• Conduct usability tests to observe how users interact with the dashboard. Are they finding key insights easily?
• Gather feedback through  user interviews or surveys to refine data presentation, layout, and navigation.
• Identify pain points where users struggle—whether it’s understanding metrics, filtering data, or navigating between sections.

Skipping research can lead to overcomplicated and confusing dashboards that fail to deliver value. Investing time in both discovery and evaluative research ensures the final product is user-centric and actionable.

2. Choose a dashboard type

Different types of dashboards serve different purposes, depending on the audience, goals, and level of data complexity required. While some dashboards focus on long-term strategy, others are built for real-time monitoring or in-depth analysis. In most cases, dashboards combine multiple elements, making them hybrid solutions tailored to specific business needs.

Depending on those above, we usually identify 4+1 types of dashboards:

1. Strategic
2. Tactical
3. Analytical
4. Operational
5. Hybrid

Let’s explore them in more detail.

Strategic dashboards

Strategic dashboards support high-level decision-making by providing an overview of key trends and business performance over an extended period. They help executives, stakeholders, and department heads track progress toward long-term goals, such as company growth, market share, customer retention or compliance tracking.

Key characteristics:

• Focuses on big-picture insights rather than granular details.
• Displays historical trends and performance benchmarks to guide future planning.
• Often includes KPIs and goal tracking for company-wide initiatives.

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Tactical dashboards

Tactical dashboards assist managers and teams in making short- to mid-term operational decisions. They focus on comparisons, performance tracking, and optimization of ongoing projects. These dashboards often provide actionable insights that help refine projects and improve a department’s efficiency.

Key characteristics:

• Supports team-level decision-making and execution.
• Features sales performance, milestones, or marketing campaign data.
• Helps identify trends and patterns for process improvements.

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Analytical dashboards

Analytical dashboards provide a deep dive into large datasets, enabling users to explore, manipulate, and draw insights through filters, queries, and interactive visualizations. These dashboards are typically used by UX researchers, data analysts, product teams, and business intelligence professionals to uncover hidden patterns and optimize decision-making.

Key characteristics:

• Combines high-level summaries with interactive tools for deep exploration.
• Offers filtering, segmenting, and drill-down capabilities for precise analysis.
• Commonly used for user behavior analysis, market trends, and financial forecasting.

Operational dashboards

Operational dashboards are designed for real-time monitoring, helping teams measure, maintain, and respond to ongoing activities within a system or business. These dashboards are crucial for time-sensitive decision-making, often used in customer support, IT infrastructure, logistics, and finance.

Key characteristics:

• Displays live data updates on system health, incidents, and key operational metrics.
• Ensures immediate visibility into critical performance indicators.
• Helps teams react quickly to issues such as stock fluctuations, server downtimes, or traffic spikes.

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Hybrid dashboards

In practice, many dashboards don’t fit neatly into a single category. Hybrid dashboards combine elements of strategic, tactical, operational, and analytical dashboards to serve multiple needs within an organization. For example, a tactical dashboard might include analytical components to help teams see the analysis that supports the KPIs.

Key characteristics:

• Merges features from different dashboard types based on business needs.
• Provides multiple data views for different user roles (e.g., executives, managers, analysts).
• Offers a flexible structure, allowing users to switch between high-level overviews and detailed insights.

3. Avoid common mistakes

Even the most visually appealing dashboard UIs can fail if they don’t prioritize usability and clarity. Here are some of the most common mistakes that can impact dashboard effectiveness:

Ignoring user research and feedback 

The biggest risk in dashboard design is not understanding your users. Different user roles have varying levels of data literacy, and a dashboard that works for a data analyst may overwhelm a CEO or marketer. Skipping user research can result in dashboards that are either too complex or too simplistic for the intended audience.

Overloading with data

Trying to show everything at once leads to cluttered dashboards, making it harder to find critical information quickly. Poor information architecture can slow decision-making or even lead to misinterpretation of data if users can’t locate the right insights easily.

Using the wrong visuals 

 Just because a chart looks impressive doesn’t mean it’s useful. Mismatched visualizations—like using a pie chart for time-based data—can distort the message and lead to misinterpretation. Always choose the right data visualization for the type of insight being communicated.

Misusing colors 

Colors are powerful, but can also create confusion when used incorrectly. For example, using red and green to categorize data groups (instead of performance trends) may mislead users into thinking one category is “good” and the other is “bad.” Another example is forcing the use of brand colors for charts: they have a different purpose and they would limit options on charts. Always ensure color choices align with user expectations and accessibility standards.

Not aligning with engineering 

In most cases, dashboard UIs rely on chart libraries such as Chart.js, D3.js, or fl_chart for implementation. Once the initial design exploration is complete, collaborate with the engineering team to select the most suitable library that works well with the tech stack. After making a choice, ensure your design aligns with the library’s capabilities and limitations to avoid unnecessary engineering work and complexity.

Ignoring real-time updates 

In operational dashboards, outdated data can lead to slow response times and poor decisions. Imagine if Google only detected server failures 15 minutes after they occurred—by then, the damage could already be extensive. Live updates are crucial for dashboards that support critical, time-sensitive decisions.

Final Thoughts

A well-designed dashboard isn’t just a collection of charts and numbers—it’s a decision-making tool that should be clear, glanceable, and insightful. By following the right research process, structuring data effectively, and focusing on usability, you can create a dashboard that guides users effortlessly toward the insights they need.

Remember, a great dashboard is not about showing more data—it’s about showing the right data in the right way. Keep refining, testing, and iterating based on real user feedback to ensure it remains relevant, actionable, and easy to use.

Need help designing an intuitive, high-impact dashboard? Let’s chat! Our UX experts can help you create a data experience that truly empowers your users.