When you open the Add a chart menu in Data Studio for the first time, the sheer number of options is either exciting or paralyzing depending on your disposition. There are time series charts, bar charts, scorecards, tables, pie charts, scatter plots, geo maps, treemaps, bullet charts, pivot tables, and more — each with its own configuration panel and a handful of ways to go wrong.
The good news: most GA4 dashboards only need five or six of these well. The bad news: the most common defaults — pie charts for channel breakdowns, line charts for everything time-related — aren't always the right call. This guide walks through every meaningful chart type in Data Studio, explains the GA4 use cases where each one shines, and flags the situations where a different chart would serve you better.
Scorecards and KPI displays
Scorecards are the single most underrated chart type in Data Studio. They're not glamorous, but a well-configured scorecard row at the top of a dashboard answers the most important question first: are our headline numbers up or down?
Displays a single metric as a large number, optionally with a comparison value and delta indicator. The most direct way to surface a KPI.
Shows a primary metric as a bar against a target value and optional performance ranges (satisfactory, good). Combines context with the raw number in a compact space.
Always enable comparison periods on scorecards. A number without context is noise. In the scorecard settings, set Comparison date range to Previous period and enable the delta indicator. A 12% increase next to the absolute number takes the same space and delivers ten times the value.
Time series and trend charts
These are the workhorses of any GA4 dashboard. The goal is to show how a metric changes over time — and to make it easy to spot anomalies, seasonality, and inflection points at a glance.
Plots one or more metrics across a continuous time dimension. The default choice for showing trends — sessions over time, revenue by day, conversions by week.
A line chart variant where a second metric is plotted against its own Y-axis on the right. Essential when two metrics have very different scales — for example, sessions (thousands) and conversion rate (percentage).
Bar and column charts
Bar charts — horizontal or vertical — are the clearest way to compare a metric across categories. For GA4 dashboards, that usually means comparing channels, landing pages, campaigns, or devices against each other. They get misused less often than pie charts, but there are still a few common traps.
Compares a metric across categories using horizontal bars. The horizontal orientation is easier to read when category labels are long — which they almost always are with channel or page names.
Shows two or more metrics stacked within each column, broken down by a dimension. Good for showing composition — how much of each channel's sessions came from mobile vs. desktop, for example.
Avoid 100% stacked bar charts for GA4 channel data. They show proportions but hide absolute volume. If organic traffic drops 50% but paid traffic stays flat, a 100% stacked chart will make organic look like it grew — because its proportion of a smaller pie increased. Absolute numbers almost always matter more than share.
Tables and pivot tables
Tables are the most information-dense chart type in Data Studio — and for GA4 reporting, that's often exactly what you want. A well-configured table with conditional formatting does the work of six bar charts in a third of the space.
A standard data table with conditional coloring applied to metric columns. The heatmap highlights high and low performers without requiring a separate chart — your eye goes straight to the outliers.
Breaks a metric down by two dimensions simultaneously — one as rows, one as columns. The most space-efficient way to surface intersecting patterns in GA4 data.
Pie charts and geo maps
Two chart types that look impressive in client presentations and work in a narrow set of situations. Both are regularly misused.
Shows the proportional share of a total across categories. Works only when shares are the primary story and the number of slices is small. Most GA4 use cases don't actually need share — they need volume.
Shades geographic regions by metric value. Visually striking and genuinely useful when geography is a real decision variable — localisation strategy, regional campaigns, or international expansion.
Scatter plots, treemaps, and advanced charts
These are Data Studio's power tools — genuinely useful in the right hands, but they require more configuration and more analytical maturity from the people reading them. Use them when a simpler chart genuinely can't tell the same story.
Plots items (pages, channels, campaigns) as points across two metric axes, with optional bubble sizing for a third metric. The best chart for surfacing opportunity gaps — high traffic, low conversion rate; or high spend, low revenue.
Represents items as proportionally-sized rectangles, coloured by a second metric. Each rectangle's area encodes volume; its colour encodes performance. Excellent for quickly identifying which pages carry the most weight and whether high-traffic pages are performing.
Shows a sequence of steps and how volume decreases at each stage. In GA4 terms, this is typically replicated using GA4's own funnel exploration — but a simplified version in Data Studio is useful for executive-level conversion flow summaries.
Quick-reference: chart type decision guide
Not sure which chart to reach for? Match your question to the right type below.
| If you want to show… | Use this chart | Not this one |
|---|---|---|
| A single headline number | Scorecard | Any chart — it's visual clutter |
| How a metric changes over time | Time series | Bar chart (no time axis) |
| Ranking categories by one metric | Bar chart | Pie chart (hard to rank slices) |
| Multiple metrics across many rows | Table with heatmap | Multiple bar charts (space-inefficient) |
| Two dimensions intersecting | Pivot table | Multiple separate tables |
| Share of a total (3–5 categories) | Pie / donut | Bar chart (when proportion is literally the point) |
| Geographic distribution | Geo map | Bar chart (hard to read country names) |
| Relationship between two metrics | Scatter chart | Side-by-side bar (doesn't show correlation) |
| Volume + performance at a glance | Treemap | Bar chart alone (misses the size dimension) |
| Progress against a specific goal | Bullet chart | Gauge chart (low precision, large footprint) |
The three chart mistakes that undermine dashboards
Most dashboard failures don't come from choosing the wrong chart type — they come from configuring the right chart type incorrectly. These are the three configuration mistakes that appear most often.
Using pie charts for channel breakdowns with more than five segments
GA4's default channel grouping has twelve segments. A twelve-slice pie chart is unreadable — slices for "Unassigned," "Display," and "Affiliates" at 2% each are visually identical and meaningless. Merge anything below 3% of total sessions into a single "Other" segment, or switch to a horizontal bar chart where the labels are legible and the values are sortable.
Line charts without a comparison period
A single line going up or down tells you almost nothing without context. A 15% drop in sessions over 30 days could be a crisis or the normal trough after a seasonal spike — you can't tell from one line alone. Always add the previous equivalent period as a second line, or enable the comparison shade. Every time series chart on a GA4 dashboard should answer "up or down compared to what?"
Tables with too many rows and no sorting
A table showing 200 landing pages sorted alphabetically is a spreadsheet, not a dashboard. Set a meaningful row limit (10–20 for most use cases), sort by your primary metric descending, and apply heatmap conditional formatting so the outliers are visible immediately. If someone needs the full 200-row dataset, that's a job for a GA4 Exploration or a BigQuery export — not a Data Studio dashboard.
Gauge charts and Bullet charts — what's the difference? Both show progress toward a target, but gauge charts (the speedometer-style display) are mostly decorative. They use a large amount of space to communicate a single number and a single target, with imprecise visual encoding. Bullet charts communicate the same information in a horizontal bar, with optional performance range shading, in about a quarter of the space. Always choose bullet over gauge when you have a defined target to track.
Chart types on mobile — what renders well
Data Studio reports are viewed on mobile far more often than most analytics teams expect. Stakeholders check dashboards on their phones before Monday morning meetings. Here's how the chart types hold up on a narrow screen, and what to do about the ones that don't.
- Scorecards: Render perfectly on mobile. Stack them vertically (2×2 or 1×4) and they become the most mobile-friendly summary possible.
- Bar charts (horizontal): Generally readable on mobile, especially when limited to 6–8 bars with short labels. Avoid long page-path labels that overflow.
- Time series: Acceptable on mobile — the trend is visible, even if precise values require a pinch to zoom. Limit to two lines maximum.
- Tables: Problematic on small screens. Columns truncate or overflow. If mobile viewing is common, limit tables to three columns maximum, or consider whether a top-five bar chart serves the same purpose more legibly.
- Pivot tables: Poor mobile experience if they have more than three column headers. Reserve for desktop-only pages and make that explicit in a page header.
- Scatter charts and treemaps: Largely unreadable on mobile — data points and rectangles lose their labels. Use these only on pages where desktop access is expected.
- Geo maps: Render adequately on mobile but require pinch-to-zoom for any useful interaction. Add a companion table with the top ten countries by metric for viewers who don't want to interact.
Build a mobile-first summary page. Add a first page to your dashboard that contains only scorecards and one or two single-metric bar charts — everything a stakeholder needs on a phone in 30 seconds. Keep the richer analysis pages for desktop. Label the first page clearly: "Quick summary" or "Mobile view." Most stakeholders will never click past it.
Want help choosing the right charts for your GA4 dashboard?
We audit and rebuild Data Studio dashboards so that every chart earns its place — the right type, the right configuration, and the right data underneath it. Book a free 30-minute session and we'll walk through your current setup and show you what could be clearer.