Faceless explainer
Three-point data explainer
Turn a small set of verified numbers into a fast visual explanation with one chart idea, three claims, and a useful conclusion.
- Level
- Beginner
- Working time
- About 75 minutes
- Possible cash cost
- $0 using a free design plan and owned narration
Source note: Fewertools authored this fictional local-cycling data study using synthetic numbers and diagram descriptions.
Start here
Your simplest route
- First move
- Choose three verified numbers that answer one question and keep the source links beside the script.
- Tool path
- Spreadsheet or notes
- Design tool
- Voice recorder
- Simple timeline editor
- Finish line
- A 30 second explainer with one question, three sourced figures, and one conclusion the viewer can repeat.
Prices checked 18 August 2026. Free allowances and prices can change.
Observed
- Each scene shows only the number needed for the sentence being spoken.
- The same scale, colors, and label positions are reused across all three figures.
- The final scene explains what the numbers mean instead of adding a fourth statistic.
Likely
- The creator simplified the data before opening the design tool.
- The visual system was duplicated between scenes rather than rebuilt each time.
Needs you
- Verify the source, date, unit, and comparison behind every number.
- Decide whether the conclusion is descriptive or supported strongly enough to recommend an action.
Beginner route
A route you can follow
Write one data question
Frame a question that can be answered with exactly three figures and one plain-language conclusion.
Check: Every chosen figure helps answer the same question.
Build one visual grammar
Choose one scale, two colors, one type size, and one label position, then reuse them for every scene.
Check: The viewer does not have to relearn the chart between figures.
Narrate the meaning
Say the figure once, explain why it matters, and leave the full source in the description or credits.
Check: The voice adds meaning rather than simply reading the screen.
Check the claim strength
Confirm units and dates, remove causal language the data cannot support, and preview every label at phone size.
Check: The final statement is accurate, legible, and no stronger than the evidence.