Clarity in communication: Why It Matters in UX Research (& How to Get It Right)

As UX researchers, we’re all about understanding users. But what happens when our own communication becomes a barrier to understanding? Unclear instructions, ambiguous language, and even seemingly minor oversights can significantly impact the quality of our research data and ultimately, the effectiveness of our designs.

A Case Study in Clarity:

Recently, I drafted a call for participants in a research study. It looked like this:

Are you:

  • A new joiner who started within the last 6 months? ✅
  • A line manager with a direct report who joined within the last 6 months? ✅
  • Part of HR, Security, IT, or Facilities and worked on inductions in the past 6 months? ✅

If you answered YES to ANY of these, we want to hear from you!

While my final sentence aimed for clarity, my colleague Sebastian suggested adding “or” between each bullet point. This simple change, he argued, would further enhance clarity, especially for participants who might skim quickly.

The Power of “Or”:

Sebastian was right. Adding “or” between criteria offers several benefits:

  • Reduced cognitive load: It eliminates the need for participants to mentally parse complex sentences, making it easier to understand the requirements.
  • Improved scannability: The clear separation between options makes it easier for users to identify if they qualify quickly.
  • Minimised ambiguity: It removes any doubt about whether someone meets one or more of the individual criteria.

Your UX Research Clarity Toolkit

While adding “or” is a powerful tool, it’s not the only way to achieve clarity in your UX research communication. Here are some additional tips:

  • Plain language is your friend: Ditch the jargon, technical terms, and complex sentences. Aim for clear, concise, and direct communication that everyone can understand.
  • Provide context: Briefly explain the purpose of your research and how it benefits participants. This helps them understand why their input matters.
  • Pilot test, iterate, and improve: Conduct a small-scale test with representative participants to identify any areas of confusion or ambiguity in your communication. Use their feedback to iterate and refine your message.
AI generated image of an Indian UX Researcher thinking
AI generated image of an Indian UX Researcher

Click here to read: A UX Researcher’s Guide to Multiple Cohort Participant Recruitment.

Takeaway

Clarity is not a one-time fix; it’s an ongoing process. By actively seeking feedback, iterating on your communication, and employing these tips, you can ensure that your research participants understand your requirements, leading to richer data and more impactful UX design outcomes.

Author

  • Richa Deo

    I teach professionals how to master new skills and help marketers get their content discovered by AI search engines.

    Who I Am
    Former Indian Navy Judge Advocate General (JAG) officer. Published children’s book author (19 languages, Pratham Books). Television scriptwriter (Chhota Bheem). At 47, learning competitive pistol shooting and documenting the journey.

    Currently: UX Researcher and Product Strategist at British Telecom, transitioning to Product Management. My diverse background informs my approach to meta-learning and AI-driven content strategies.

    What I Do
    Meta-Learning & Skill Acquisition
    I teach professionals how to learn faster without skill paranoia. Using proven frameworks, I help individuals master new skills and reinvent their careers at any age.

    AI Search Optimization
    I help marketers and content creators optimize their content to get cited by AI search engines like ChatGPT, Perplexity, and Claude. The shift from Google SEO to AI search changes everything about content strategy.

    Travel
    Authentic experiences from remote India. This blog started as travel writing—those posts are still here, now being optimized as my AI search testing ground.