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Feature Matrix Reveal

La tabella di confronto, rivelata una riga alla volta.

Una matrice funzionalità-opzioni rivela prima il suo scheletro, poi una riga completa alla volta con segni di spunta che compaiono da sinistra a destra, chiudendo su una striscia conclusiva che nomina il vincitore per un caso d'uso specifico. Pensato per video di confronto, spiegazioni di prezzi e guide all'acquisto.

Anteprima di Feature Matrix Reveal
Ideale per
Recensori, marketer di prodotto e creatori di guide all'acquisto
Tempo necessario
30 min
Livello
Principiante

Installala in 3 passaggi

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Cosa contiene

Un file SKILL.md (la guida operativa) + un modello di partenza. Un'anteprima:

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.

Anteprima del modello

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

Il pacchetto della skill (SKILL.md + modello) è scritto in inglese.

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