What this prompt does
This prompt designs a data-driven infographic layout with visual hierarchy, chart choices, icon placement, and a top-to-bottom narrative flow. You give it the [infographic_topic], the [target_audience], the number of [data_points], and the [narrative_arc] the piece should tell, plus [brand_colors] and a [visual_style]. ChatGPT then defines the format and grid, the header, the data sections, the chart choices, an icon system, citations, and a closing call-to-action.
The variables control structure and density. [dimensions] and [distribution_channel] set the format (a long-scroll blog embed behaves differently from a Pinterest pin), [column_count] and [section_height] establish the reading rhythm, and [section_count] divides the narrative into chapters. For each section the prompt picks the best chart type for that data and specifies [annotation_style] callouts, while [icon_count] defines the recurring icon system, [citation_style] formats the sources, and [cta_destination] sets the closing action. Because it maps the narrative arc to sections with visual anchors, the output keeps a dense story readable from top to bottom.
When to use it
- You are laying out a data-heavy infographic and want the narrative flow planned before designing.
- You have a set of data points and aren't sure which chart type fits each best.
- You need a long-scroll format with visual anchors that guide the eye section to section.
- You want a consistent icon system woven through the piece to reinforce concepts.
- You need proper source citations formatted for credibility.
- You are briefing a designer and want a section-by-section layout spec.
Example output
The output is an infographic layout specification. It sets the [dimensions] and grid for your [distribution_channel] with [column_count] columns and a reading rhythm anchored every [section_height], a header occupying up to [header_percentage] of the height, then [section_count] sections each with a sub-heading, a chosen chart type with justification, the exact values to display, and [annotation_style] callouts. It specifies an [icon_count]-icon system, a methodology footer in [citation_style], and a closing CTA to [cta_destination]. You then hand it to a designer or image tool to render.
Pro tips
- Make the
[narrative_arc]a real story with a beginning and payoff, not a list of stats, so the sections build on each other. - Match
[dimensions]to the[distribution_channel]— a Pinterest pin and a LinkedIn carousel need very different aspect ratios. - Provide accurate
[data_points]; the prompt chooses charts for the data you describe, so wrong inputs yield the wrong chart choices. - Keep
[section_count]aligned to your data — too many sections for a thin story leaves empty filler, too few crams it. - The chart recommendations are sound, but confirm each chart truly represents your data honestly before rendering.
- This produces a layout spec, not a finished graphic, so feed it to a designer or image generator with your real numbers to build it.
