As one of the instructors for NN/G’s Writing Compelling Digital Copy course, I address important, timely questions in each training session to teach people what to write, how to structure it, and how to support the experience they’re working on.
This article pulls together the questions I get often, grouped by theme. Questions are becoming sharper and more specific as practitioners become more skeptical of AI answers and seek deeper, more nuanced thinking from people with real experience. They may even spark a few new questions of your own about UX writing.
Plain Language and Readability
What Reading Level Should I Write for?
This is one of the most common questions in training sessions. Aim for a 6th–8th grade reading level for general audiences. NN/G’s eyetracking studies show that users read only about 20–28% of the text on a page. Writing at a lower grade level helps people process information more quickly and with less effort, regardless of literacy level.
You can estimate reading level using tools like the Flesch-Kincaid readability metrics in Microsoft Word, or apps like Hemingway or Grammarly.
Does Writing at a Lower Reading Level Exclude Educated Audiences?
No. This comes up frequently, often framed as: “Our audience is C-suite” or “Our users are doctors.” Even experts are busy, distracted, and scanning on screens. NN/G’s research consistently shows that plain language benefits all literacy levels, including highly educated users. Everyone appreciates saving time and ease of understanding.
If Users Read Only 20% of a Page, Does Shortening Text Mean They Read Even Less?
Concise writing increases the proportion of content that gets read. When content is well structured, formatted, and written with the right level of concision, the 20% that users do read is more likely to be the right 20%, or the main messages and action items.
Does Plain Language Help Neurodiverse Users, Particularly Those with Dyslexia and ADHD?
Yes. Plain language, chunked content, descriptive subheadings, and bulleted lists benefit users with dyslexia, ADHD, and other cognitive differences. NN/G’s research on writing for lower-literacy users consistently shows that simplification helps all literacy levels.
Tone of Voice
What’s the Difference Between Voice and Tone?
Voice is your organization’s personality; it should stay consistent.
Tone is how that voice adapts to a specific situation and the emotion it evokes in the reader.
Your voice might be clear, calm, and direct, but your tone will shift depending on context: more empathetic in an error message, more encouraging in onboarding, more neutral on a policy page.
Just like a person, you always sound like yourself, but how you speak at a work meeting differs from how you speak on vacation.
Should Tone Vary by Channel and Context? And Should That Be in the Style Guide?
Yes. Voice is consistent; tone is contextual. Your brand voice shouldn’t change, but a legal disclaimer calls for a different tone than an onboarding welcome screen.
Think about the user’s emotional state: stressed (policy pages), excited (confirmations), or neutral (reference content)? Your content standards or style guide should document both stable voice attributes and tone-shift guidance across contexts and channels.
Can AI Tools Detect Tone of Voice? Is That Good Enough?
AI tools can approximate tone. They’ll tell you generally if something is friendly or formal, but they can’t predict how that tone lands with your users in their specific context. If the tone is off at the wrong moment (an error message, a billing issue, a sensitive interaction), it can erode trust quickly.
The right tone always depends on your specific audience and context. Usability testing and interviewing your real users is still the best way to learn.
Jargon, Acronyms, and Technical Language
When Is It Okay to Use Jargon?
Use jargon only when your audience expects and uses it. Before including a word that could be unclear to some users, make sure you have evidence from user research, survey data, or site-search logs that your audience understands and prefers a technical term.
If you haven’t tested or investigated your jargon words, don’t assume people will know what they mean. Words that make sense to you and your internal team (just because you use them all the time!) will not make sense to your users.
If your audience is mixed, lead with plain language and include the jargon in parentheses. For terms that appear often, repeat the plain-language version occasionally, as people don’t read everything top to bottom.
Should We Spell Acronyms Out Only on First Use?
No. Digital readers don't read top-to-bottom; they scan, enter pages mid-way, jump between sections, and often miss the first-use definition entirely. Just spell out the full phrase the acronym represents, unless it's so universally recognized that virtually no one in your audience would need the definition. For example, PDF, URL, or FAQ.
When in doubt, write it out.
Are Branded Terms Jargon?
Yes. A hospital link labeled MyCovenantHealth doesn’t tell users whether it leads to a patient portal, bill payment, or appointment scheduling. Patient Records & Insurance communicates purpose immediately. Branded names are meaningful internally but rarely self-explanatory. Always ask: Does this label clearly tell a newcomer what they’ll find if they click on it?
Structure, Links, and Calls to Action
Should Headings and Subheadings Be Literal or Clever?
Literal. Clear, informative headings and subheadings are more effective than vague or cutesy labels. Our Approach tells the user nothing. How We Reduce Processing Time by 40% tells them whether to keep reading. Each subheading should summarize the content it introduces.
Should We Use Learn More as a Link Label?
No, never. Learn More is a lazy link or button label. It tells users nothing about what they’ll learn or where they’ll go after clicking. It’s also a significant accessibility failure: screen readers will announce Learn More, Learn More, Learn More, across a page with no way to distinguish among them. The same issue applies to other vague labels like Shop Now, Discover More, Explore, View Details, or Read More links that describe the action, but not the destination.
Use descriptive link text that communicates what users get: See how we reduce processing time is specific and actionable.
Should I Include the Word Successfully in Confirmation Messages?
No, this word is usually not necessary. You successfully updated your password is redundant. We wouldn’t be confirming the action unless it succeeded. Let the design do the work: a green checkmark communicates success without the word.
However, if your brand voice is encouraging and conversational, the word can add warmth. Decide based on your voice guidelines whether adding an extra word is worth it and test it with users.
AI, SEO, Stakeholders, and Copy Testing
Can I Use AI to Write UX Copy?
Yes, but strategically. AI is genuinely useful for first drafts, headline variations, alternative-text generation, microcopy brainstorming, and getting past the blank page. The risks come from overreliance: AI output tends toward the generic, drifts from your brand voice, and has no knowledge of your users, your research, or your context. It also can't make the judgment calls that define good UX writing, like knowing what to cut, calibrating tone to an emotionally loaded moment, or recognizing when a label will confuse a specific audience.
Treat AI as a capable first-draft collaborator. Always edit with your audience in mind, never publish AI copy without review, and keep the strategic thinking.
In the Era of AI, What Metrics Should We Use to Evaluate Content Success?
Also commonly asked as, Our web traffic is declining as AI tools answer questions directly. If traffic is no longer the right metric, what should I look at instead?
Traditionally, traffic was used to assess engagement with content, whether people find, understand, and act on your copy. But as AI tools answer questions directly, site traffic declines and becomes less reliable as a metric for assessing content success.
As AI previews intercept more searches before users click, shift measurement focus to engagement and conversion metrics, task completion rates, and return visits. These tell you whether the people who do arrive are getting value. You can use referral traffic from AI tools in your analytics as a rough signal of how often your content appears in AI-generated answers. Just keep in mind it will significantly underrepresent reality, since only a small percentage of users actually click through.
In the Age of AI, Does SEO Still Matter and How Does It Relate to AEO, GEO, and All the Other Acronyms?
Yes, search-engine optimization (SEO) still matters. Answer-engine optimization (AEO) is about structuring content so AI assistants and voice-search tools can pull a direct answer from it.
Generative-engine optimization (GEO) is about making your content authoritative and structured enough that generative AI tools cite it as a source.
The underlying principles are the exact same ones that make content work for humans: clear structure, plain language, descriptive headings, direct answers near the top, and genuine authority on your subject.
Websites are shifting from being a destination people click on from search-engine-results pages to being a source AI tools quote. The inverted pyramid matters more than ever now, so lead with the answer, then support it. Keyword-stuffed content that was once gamed for search will perform even worse in an AI-mediated world. As we’ve always said, write for people first. Structure it for machines second.
How Do I Push Back When My Stakeholders Prioritize SEO over Users?
Analytics and heatmaps tell you what users click, not why they struggle. Good UX writing and good SEO are not in conflict with each other. Descriptive headings, clear link text, and plain language support both. Optimize for search to bring users to the page; optimize for users to keep them there.
Qualitative research uncovers content problems that no amount of guessing and pontification over a heatmap or analytics report can accurately explain.
How Do I Convince Stakeholders that Copy Matters?
Show, don’t tell. Eye-tracking videos (which we share in the course), usability-test clips, and before-and-after readability scores are more persuasive than process arguments. Frame everything around business outcomes: task-completion rates, time-on-task, and satisfaction all improve with better copy.
Are There Affordable Alternatives to Eyetracking?
Usability testing, first-click testing, cloze tests, and content-preference tests all surface content problems without the need for expensive hardware.
Traditional heatmap tools (which use scroll behavior, dwell time, and cursor positioning rather than hardware and software that’s calibrated to a human’s actual eyes), like Hotjar and Lucky Orange, can provide valuable directional data. Keep in mind, the data provides a very rough approximation and doesn’t tell you about what text people actually paid attention to.
If you can’t afford an eyetracking study using the specialized hardware and software from organizations like Tobii, use these as lower-cost approximations of eye-tracking results that practitioners often use for directional guidance.
Conclusion
Questions and challenges related to UX writing usually stem from organizational constraints: legal requirements, stakeholder preferences, and assumptions about how people read. No matter your skill level with UX writing, using data to support your recommendations, testing with real users, and focusing on how people actually read can lead to better decisions and better experience outcomes.
If you’re looking to build more confidence in these areas, NN/G’s Writing Compelling Digital Copy course goes deeper into the research, patterns, and practical writing and editing techniques you can apply right away. These are especially useful if you’re using AI in your content strategy practice or thinking about incorporating it.
I look forward to seeing you and answering your questions at an upcoming live online training session.
