| Chart type | Best suited to | Limit to respect | Planning use |
|---|---|---|---|
| Vertical bar chart | Comparing values or occurrences among categories; can show trends when the bars are time periods | Less natural for continuous trends than a line | Default for category comparisons such as plans, regions or teams |
| Horizontal bar chart | Comparing categories, with labels that are easier to read | Should not show time trends | Use when category names are long or numerous |
| Line chart | Values and trends over time | Not for nominal variables where the frequency distribution matters | Use for any metric where direction of change drives the decision |
| Pie chart | Proportions of a whole | People compare linear representations more accurately than area or circles | Keep for simple part-to-whole views, and pair with exact values when precision matters |
Chart guidance here draws on Eleken’s dashboard design examples and UXmatters’ dashboard design primer.
Good dashboard ui design serves a user goal rather than decoration: it gives the few KPIs that drive action prominent positions and picks each chart for the comparison it must support.
For wider context on interface decisions in software products, see our digital design guide for software.
What a good dashboard does for users
A good dashboard UI helps a specific person decide or act faster. UXPin defines a dashboard as a visual display of the essential information needed to achieve specific business objectives, and notes that dashboards are primarily used for tracking and analyzing KPIs. That definition has direct design consequences, because anything that does not help someone track a KPI or complete an interaction is a candidate for removal.
UXmatters makes the same point bluntly: an information dashboard is not eye candy. Treat decorative gradients, extra gauges and ornamental icons as costs, not features.
What goes wrong when the rules are ignored
- Information overload. UXPin observes that many dashboards suffer from it. Limiting the number of visual elements stops users being overwhelmed with too much information at once, so cut panels before you shrink them.
- Lost priority. Without a clear visual hierarchy, a dashboard can fail to communicate the relative importance of information. Users then scan everything with equal weight and miss the number that needed attention.
- Mismatched charts. A chart type that does not fit the comparison, such as a line for unrelated categories, makes the reader do extra work or draw the wrong conclusion.
- Decoration over function. Elements that do not support a goal or an interaction dilute the elements that do.
Organizing the dashboard layout
Dashboard layout should follow the user’s workflow, with the most important items placed prominently. The UXmatters checklist includes organizing information to support its meaning and use, and giving must-see items prominent placement and stronger visual treatments. In practice, that means deciding which KPI answers the user’s first question and placing it where the eye lands, then arranging supporting metrics around it by how they relate to that first number.
Hierarchy and placement
UXPin recommends a clear visual hierarchy to prioritize information. Size, position and visual weight are the tools you have. Make the primary KPI visibly larger or stronger than supporting figures, and group related metrics so a reader can tell which numbers explain which. If everything looks equally important, nothing will be read as important.
Splitting content across tabs
When a single screen cannot hold everything without crowding, divide it. In a SaaS case study, Eleken describes creating different tabs instead of squeezing all the data into a single screen. Tabs suit dashboards that serve several themes or audiences. They are a poor fit when users must compare figures from different tabs side by side, because the comparison then depends on memory.
Colour as a signal
Eleken calls color-coding one of the most important aspects of directing the user’s attention, and notes that green or blue and red are the go-to colors for yes or no situations. Reserve those colours for status so they keep their meaning, and avoid using red or green decoratively elsewhere. Colour should never be the only carrier of meaning; the accessibility section below covers contrast.
Matching dashboard type and metrics to layout
Decide which kind of dashboard you are building before choosing a layout. Eleken divides SaaS dashboards into three types: operational, analytical and strategic, and observes that operational dashboards are the most common. The type shapes which metrics belong on screen and how much interaction the layout must carry.
- Operational. Suits users monitoring current activity. Put the headline KPIs and status signals at the top and keep the screen quiet enough to scan quickly.
- Analytical. Suits users who need to explore. Eleken notes these dashboards do not only display data but let users slice and dice data points across multiple variables, so the layout needs room for controls and for views that change with them.
- Strategic. Suits users reviewing performance against objectives. Fewer, clearer KPIs and a clean hierarchy matter more than interactive depth.
This is where metric choice and layout meet. A KPI that triggers action earns a prominent card; a metric that only adds context belongs lower or behind a drilldown. If a metric cannot be linked to a decision a user makes, it is clutter. Layouts also have to survive different screen widths, and Responsive Web Design Examples: Practical Patterns That Scale In 2026 – Interestingdevelopment shows how interface patterns adapt across them.
Charts and data visualization choices
The table at the top of this article sets out which chart suits which question. The deciding factor is the comparison the user needs to make. For categories, bars work well; Eleken describes bar charts as well suited to comparing data across categories, line charts as useful for displaying trends over time, and pie charts as great for visualizing proportions. UXmatters adds the cautions: horizontal bars should not carry time trends, and line graphs should not be used for nominal variables where users care about the frequency distribution.
The pie chart deserves extra thought. UXmatters explains that people cannot compare area or circular representations as well as linear ones. If users must judge close values, a bar chart serves them better, and a pie should be limited to simple part-to-whole views.
Interaction: drilldowns and exploration
Interactions let users move from overview to detail, and the question to ask for each aggregated chart is the one UXmatters poses: would users want to drill down to more detail? If the answer is yes, a headline number should lead somewhere, such as a filtered view of the records behind it, rather than ending at the summary.
For analytical dashboards, slicing across several variables is the core task, so the controls that do it deserve a clear, consistent position next to the data they affect. For operational and strategic views, keep controls minimal so that the primary KPIs stay dominant. Where detail would crowd the main screen, tabs or a drilldown are better places for it than extra panels.
Accessibility, Figma checks and design systems
Accessibility is part of making a dashboard readable, not an add-on. Kalamuna describes WCAG 2.1 Level AA as the common standard for web accessibility, which makes it a sensible baseline for contrast and text sizing in dashboards. Because dashboards lean on colour for status, contrast checks matter most for the small labels, axis text and legends that carry the detail.
Figma, which Kalamuna calls the leading collaborative design tool, supports accessibility plugins. One contrast plugin assesses the colour contrast ratio of all visible text within a frame and reports against WCAG AA and/or AAA, so you can check a dashboard frame before it reaches development.
Text sizing in a design system
Kalamuna notes that one rem is always 16px in the browser, which helps when translating design sizes into scalable units. It also warns that Figma’s text-resizing function is not compatible with text sizes defined with Variables or Style settings. For a team that stores type sizes as variables or styles in its design system, that means resizing checks need another route, so confirm text scaling in the built interface as well as in the design file. Type choices also affect legibility in dense tables and tiles; Font Pairing Examples: Simple, Stylish Combinations You Can Use Today (2026) – Interestingdevelopment covers combinations worth considering.
Frequently asked questions
What makes a good dashboard UI?
It supports a user goal or interaction, shows the KPIs that matter in prominent positions, uses charts matched to the comparison, and avoids decoration and overload.
How should dashboard layout be organized?
Organize information to support its meaning and use. Give must-see items prominent placement, apply a clear visual hierarchy, limit visual elements, and move secondary content to tabs or drilldowns.
Which dashboard types should a SaaS product consider?
Operational, analytical and strategic. Operational is the most common; analytical dashboards add the ability to slice data across variables.
Can Figma check dashboard accessibility?
Yes, for contrast. A Figma plugin can assess the contrast ratio of visible text in a frame against WCAG AA and/or AAA, though text-resize checks do not work with sizes set through Variables or Styles.
