UX Writing (Deep Workflow)

UX writing is interface design with words: reduce cognitive load, prevent errors, and build trust. It is not marketing polish bolted on at the end.

When to Offer This Workflow

Trigger conditions:

• - Confusing errors, high drop-off flows, empty states that feel broken
• Inconsistent terminology across product
• Accessibility review flags unclear labels or verbose instructions
• Preparing voice & tone guidelines for a design system

Initial offer:

Use six stages: (1) context & users, (2) voice & tone, (3) clarity & structure, (4) errors & recovery, (5) forms & validation, (6) a11y & localization. Ask for screenshots, current copy, and metrics (support tickets, drop-off).

Stage 1: Context & Users

Goal: Copy matches mental model and emotional state.

Questions

1. 1. User goal on this screen—primary action?
2. Stress level: billing, security, health—tone adjusts
3. Expertise: first-time vs power user—progressive disclosure

Constraints

• - Character limits in UI components; legal must-review text

Exit condition: Scenario brief per screen or flow—not generic “friendly.”

Stage 2: Voice & Tone

Goal: Consistent personality with flexible tone by context.

Voice (stable)

• - Principles: e.g., clear, respectful, confident, human—pick 3–4 and define anti-patterns

Tone (situational)

• - Success: brief affirmation
• Error: calm, no blame; next step forward
• Empty state: invite action without condescension

Terminology

• - Glossary: “Workspace” vs “Project”—one term per concept; align with engineering names users see in API/docs

Exit condition: Before/after examples for three contexts (success, error, empty).

Stage 3: Clarity & Structure

Goal: Scannable text—front-load meaning.

Practices

• - Titles specific: “Payment failed” not “Something went wrong” (unless generic is truly unknown)
• Buttons use verbs: “Save address” not “OK”
• Sentence case per style guide; avoid ALL CAPS except acronyms
• Numbers/dates: user locale; relative time when helpful (“Updated 2 min ago”)

Microcopy hierarchy

• - Primary message → secondary detail → tertiary learn more

Exit condition: Redundant words cut; one idea per sentence in critical paths.

Stage 4: Errors & Recovery

Goal: Users understand what happened and what to do next.

Structure

• - What happened (plain language, no codes alone)
• Why (if known and helpful—not stack traces)
• What to do (steps, link to support, retry)
• Support path when stuck

Security

• - Don’t leak whether an email exists on login if policy requires ambiguity—coordinate with security

Exit condition: Top 10 error states have rewritten copy + engineering alignment on truth of messages.

Stage 5: Forms & Validation

Goal: Inline help and validation text accessible and timely.

Practices

• - Label every input; don’t rely on placeholder alone as label
• Errors associated programmatically (aria-describedby); announce on submit failure
• Password rules visible before typing when complex
• Success confirmation for destructive actions

Tone on errors

• - Avoid shame (“Invalid input”) → neutral (“Enter a date after Jan 1, 2024”)

Exit condition: Form review checklist applied to highest-traffic form.

Stage 6: Accessibility & Localization

Goal: Text works for screen readers and translation.

Accessibility

• - Alt text for meaningful images; decorative marked so
• Instructions not color-only; error identification not by color alone

Localization (i18n)

• - No concatenated strings with word order assumptions across languages
• Punctuation and formality per locale—pseudolocale QA for overflow

Exit condition: String extraction friendly; no embedded HTML in strings without plan.

Final Review Checklist

• - [ ] Voice/tone documented with examples
• [ ] Critical paths scannable; verbs on CTAs
• [ ] Errors: cause + next step + support path
• [ ] Forms: labels, validation, a11y association
• [ ] i18n-safe string patterns

Tips for Effective Guidance

• - Read aloud—if awkward, revise.
• Pair with design: copy length affects layout; don’t fight the grid blindly.
• For AI products, clarify machine vs human responsibility in copy.

Handling Deviations

• - Dense enterprise UIs: prioritize task efficiency over personality.
• Regulated industries: legal review loop—suggest plain alternatives, not legal advice.