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Feature Matrix Reveal

Le tableau comparatif, révélé une ligne à la fois.

Une matrice fonctionnalités par options révèle d'abord son squelette, puis une ligne complète à la fois avec des coches qui apparaissent de gauche à droite, pour finir sur une bande de conclusion nommant le gagnant pour un cas d'usage précis. Conçu pour les vidéos comparatives, les explicatifs de prix et les guides d'achat.

Aperçu de Feature Matrix Reveal
Idéal pour
Testeurs, marketeurs produit et créateurs de guides d'achat
Temps nécessaire
30 min
Niveau
Débutant

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Contenu du pack

Un fichier SKILL.md (le guide pratique) + un modèle de départ. Aperçu :

Feature Matrix Reveal

When to use

  • A comparison video lines up 2–4 products, plans, or tools against the same set of features
  • A pricing explainer must show what each tier includes without flashing a wall of checkmarks
  • A buyer's guide compares options feature by feature and lands on a recommendation
  • A product launch video shows how the new option stacks up against the old one and the rival
  • A tutorial explains which plan a viewer needs by walking the feature rows that matter to them
  • You have a table that is genuinely useful, and a static screenshot of it would get skipped

Workflow

  1. Build the matrix (input: your comparison → output: matrix data)
    Columns: 2–4 options (products, plans, tiers). Rows: 5–8 features, each one a real decision factor — not filler ("Colour: yes"). Every cell holds exactly one of three values: a check (✓), a cross (✗), or a short value ("10 GB", "$29", "Unlimited"). No paragraphs in cells, no footnotes inside the grid. Order the rows by decision weight: the row that most often decides the purchase goes first. Name the columns with the option names, not "Option A" — the viewer must be able to read the verdict off the headers.
  2. Lay out the grid (input: matrix data → output: layout)
    Header row in bold with a tinted background; feature labels in the left column, left-aligned, in a smaller but readable size (≥16px at 1080p). Columns equal width; rows equal height. Cell contents centred. Use one accent colour for checks (green or the brand accent) and one muted colour for crosses (grey or soft red — never bright red, which reads as an error). Zebra-striping or hairline dividers separate rows; pick one, not both. The grid must fit the frame with ≥40px margins — if it does not fit, cut a row, not the font size.
  3. Reveal the skeleton first (input: layout → output: frame keyframes)
    The grid frame enters before any data: header row fades + slides down 8px over 250ms, then the feature labels fade in left-to-right staggered 40ms apart over ~300ms. The cells stay empty — the viewer sees the shape of the comparison before any verdict appears. This skeleton beat takes ≈550ms total. Never reveal a checkmark before its row label exists; a floating ✓ with no label is noise.
  4. Reveal row by row (input: frame keyframes → output: row choreography)
    Reveal one full row at a time, top to bottom, 500–700ms apart. Within a row, the cells pop left to right, 80ms apart: each cell's content scales 0.6 → 1.0 over 180ms with ease-out back, plus a 150ms fade. Checks get a tiny extra beat — a 200ms ring or scale pulse on the check itself — so the eye registers "included" rather than just "something appeared". The row's feature label brightens to full opacity as its cells land (labels start at 60% so the active row visibly steps forward). Between rows, hold 150ms of stillness: the stagger must read as deliberate pacing, not lag.
  5. Land the takeaway row (input: row choreography → output: verdict beat)
    After the last feature row, reveal a final takeaway strip below the grid: one line naming the winner for a named use case ("Best for solo creators: Option B — every row you need, nothing you don't"). The strip slides up 10px + fades in over 300ms, starting 300ms after the last row settles, in a tinted band distinct from the grid. If there is no single winner, the strip states the split honestly ("Pick A for storage, B for collaboration"). Hold the full grid + takeaway for ≥1.5s so the viewer can scan the whole comparison.
  6. Check the matrix reads as a comparison (input: finished motion → output: verified animation)
    Freeze the final frame and ask: can a viewer find any single cell's meaning in under a second? If two columns look identical, either the rows are wrong or the options are not really different — fix the data, not the animation. Check on a phone screen: if the grid needs squinting, split it into two grids of 2 columns each rather than shrinking the type. Never let a cell wrap to two lines; a wrapped cell breaks the row rhythm.

Aperçu du modèle

Feature Matrix Reveal — Starter Template

Fill in every {placeholder}. Cells hold ✓ / ✗ / short value only — no paragraphs in cells.

Matrix data

  • Options (columns, 2–4): {option_1} | {option_2} | {option_3} | {option_4}
  • Rows (5–8, ordered by decision weight, most decisive first):
  • Row where the favourite loses (include it): {feature_n — option_X loses here}

Layout

  • Header: {bold}, tinted background {hex} · Feature labels left-aligned, ≥{16px}
  • Columns: {equal width} · Rows: {equal height} · Cell contents: {centred}
  • Check colour: {accent_hex} · Cross colour: {muted_grey_or_soft_red_hex}
  • Row separators: {zebra_striping | hairline_dividers} — pick one

Le pack de compétence lui-même (SKILL.md + modèle) est rédigé en anglais.

Pro — les 511 compétences

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