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Choose and build the right chart for your marketing data. A chart-type reference (bar, line, funnel, scatter, heatmap, and more) covering when to use each and how to read it, paired with mockup generators for charts and data tables and guidance on turning metrics into a clear data story.
14 curated resources across metrics, tools, and articles
Core glossary terms, formulas, and benchmark context for this topic.
A chart that uses horizontal bars of varying lengths to represent and compare data values across categories.
A chart that uses vertical bars of varying heights to represent and compare data values across categories.
A chart that displays multiple bars for each category to compare different metrics or groups side by side.
A bar chart variation where bars are divided into segments that represent different components of a total.
A visualization that displays data points connected by straight lines to show trends and patterns over a continuous interval.
A chart that displays quantitative data using the area between the line and axis to emphasize magnitude of values over time.
A visualization that displays sequential data as it moves through a process, typically showing decreasing values at each stage.
A circular chart divided into sectors representing proportions of a whole.
A chart that displays the relationship between two numeric variables.
A chart that displays the distribution of continuous data using adjacent bars.
A two-dimensional visualization using color intensity to represent values.
Interactive calculators, analyzers, and generators to apply these concepts.
Deep dives, benchmark reports, and strategic analysis from the AdSights blog.
Choosing a chart is a decision about the question, not the data. Before picking a type, name the relationship you want the reader to see: a comparison between categories, a trend over time, a part-to-whole breakdown, a distribution, a relationship between two variables, or a drop-off through stages. Each of those maps to a small set of chart types that encode it honestly — and a much larger set that will technically render but mislead.
For most marketing reporting, four families do the heavy lifting. Bar charts (horizontal when labels are long or categories are ranked, vertical for a handful of ordered categories) win comparisons. Line and area charts own change over time — they match how we read left-to-right and make trends, seasonality, and inflection points obvious. Funnel charts express stage-to-stage conversion and where prospects drop. Scatter plots reveal relationships, such as spend versus ROAS across campaigns, that a bar chart flattens away.
Part-to-whole is where most dashboards go wrong. A pie or donut chart is readable only with two or three slices; beyond that, a sorted horizontal bar or a stacked bar communicates share far more accurately because the human eye compares lengths better than angles. Distribution questions — "is this average hiding a bimodal split?" — call for a histogram or box plot, not a single summary stat that a noisy metric can quietly distort.
Whatever you choose, the craft is in the defaults: start bar axes at zero, sort ranked bars by value rather than source order, label directly instead of forcing a legend hunt, and pick a color palette that survives color-blindness and grayscale printing. The tools below let you mock up any of these chart types — and the accompanying data table — with realistic styling before you build the real thing, while the glossary entries cover when each one is the right call.
