User interviews with accessibility users about their screen reader workflow reveal critical insights that traditional testing often misses. Conversational surveys make it simpler than ever to conduct these interviews at scale and reach users in their own language.
With AI, analyzing qualitative accessibility feedback and identifying pain points becomes effortless, letting teams turn raw narratives into actionable improvements—no specialized research skills required.
Why accessibility compliance testing isn't enough
Automated accessibility checkers only catch technical issues—and that’s not enough. According to industry studies, these tools typically identify between 20% and 40% of accessibility problems, while nuanced user challenges slip through undetected. Even the best automated systems, like Deque's, found just 57% of actual issues, leaving a significant gap in coverage. [1][2]
The reality is that accessibility users, especially those who rely on screen readers, hit roadblocks that no script or code scan can catch. Think about complex screen reader workflow challenges: inconsistent navigation patterns, confusing page structure, or forms that seem logical to sighted users but are a nightmare for a screen reader. Getting these insights means directly engaging users. If you want to truly understand usability, you need to create accessibility surveys that move beyond checklists and embrace real feedback.
Real-world context matters. Users don’t interact with your site in a theoretical vacuum—they’re bringing unique devices, browsers, and personal habits. A navigation shortcut that works on one site may collapse completely elsewhere. Without real user feedback, you’re testing code, not experiences.
User workarounds reveal design flaws. People develop unique strategies to cope with design shortcomings. Maybe they tab extra times, avoid certain features, or use braille displays to compensate for missing cues. If you’re not interviewing accessibility users directly, you’re missing critical workflow insights that could transform your product’s usability—and leave those workarounds behind.
How conversational surveys transform accessibility user interviews
Conversational surveys work like natural, intelligent chat interviews rather than soulless web forms. AI drives the process, asking smart follow-up questions about exactly how users interact with content or controls via screen readers. This means a respondent can describe their workflow in their own words, helping teams catch context and details that traditional forms always miss. For example, the AI might automatically prompt for more detail on a confusing interaction, referencing a specific screen or button.
The magic comes from dynamic follow-ups. As respondents answer, AI adjusts and goes deeper on pain points—turning a list of questions into a conversation. Learn more about this capability with our automatic AI follow-up questions.
Traditional surveys | Conversational AI surveys |
Rigid forms, no probing. | Feels like chat; AI asks for details and clarifies answers. |
Misses context behind usability issues. | Surfaces workflow breakdowns, navigational strategies, and emotions. |
Harder for accessibility users to share subtleties. | Users describe real-world challenges in their own words. |
These conversations build a powerful, nuanced dataset—surfacing frustrations, motivations, and clever hacks that don’t show up in automated audits. This is where real accessibility progress begins.
Setting up effective accessibility user interviews
Start by asking core questions about screen reader preferences and daily workflow. “Which screen reader do you use?” or “Describe a recent experience filling out a form on our site” are great openers for accessibility feedback. Open-ended questions matter most—they invite real stories, frustrations, and successes instead of clicking on a list of technical errors. It's equally important to set a tone that’s clear and respectful, helping every respondent feel comfortable sharing details about their experience. Our AI survey editor lets you adjust voice, phrasing, and logic just by describing what you want to update.
Here are a few example prompts for creating accessibility surveys that dig into real usability:
Write a conversational survey for screen reader users, focusing on how they navigate your product’s forms and what gets in the way.
Use this when you want clarity on workflow issues in forms, especially fields and buttons.
Create a chat-like survey to ask accessibility users which navigation shortcuts they rely on and where they get stuck.
Perfect for learning about common navigation pain points and header structure issues.
Draft open-ended questions that encourage visually impaired responders to share stories about features that work well or not at all with their screen reader.
This draws out positive examples and surfaces places that need improvement.
Timing matters for accessibility users. People working with screen readers may need more time to respond, so allow extra minutes for each survey session. You can also give helpful reminders that there’s no rush, making the process less stressful. Precise timing and clear instructions help improve response rates and depth of feedback.
Analyzing accessibility feedback with AI
Once interviews are complete, AI transforms a mountain of qualitative input into usable insights. AI automatically sifts through workflow descriptions and highlights recurring pain points, like unclear headings or confusing CAPTCHAs. With AI, you can get a summary of the most common and impactful issues across all user interviews, without having to code or manually review every comment.
On platforms like Specific, you can literally chat with AI about your accessibility responses. Want to know how many users struggle with dynamic page changes or inconsistent navigation? Just ask. Here are example prompts you can try during analysis:
Summarize the three most common frustrations screen reader users reported when using our checkout process.
Get a focused list of pain points, ready to pass to your dev or UX team.
What percentage of respondents said they skip interactive widgets, and why?
Understand where users give up and which elements need fixing.
Which forms or input types led to the most confusion or mistakes?
This quickly shows where accessibility is failing and prioritizes what to fix first.
Pattern recognition across users. AI isn’t just about counting keywords—it looks for meaningful themes, helping you spot where the same problem hurts many users. This lets you prioritize issues based on both frequency and workflow impact, so you’re always fixing what matters most for real users.
Getting started with accessibility user interviews
Transform your accessibility testing by letting users guide you to the real problems and opportunities in your product. Launching conversational surveys takes minutes, and accessibility users genuinely value the opportunity to describe their workflow through a friendly, chat-based interface. If you’re ready to close the gap between compliance and true usability, create your own survey and start surfacing authentic accessibility workflows at scale—it’s never been easier.