Why does structuring every ethnicity survey question matter?

Well-thought-out survey questions for ethnicity support the research efforts of businesses, governments, and research organizations. How? They help them understand how diverse audience demographics, such as backgrounds, cultures, and unique orientations, impact stakeholders’ strategies, branding, and search for broader inclusivity. The questions include gathering data on employees’ and customers’ affiliations, aspirations, influencers, and preferences to identify:

• Potential planning gaps
• Undervalued audience motivations
• Policy and practice equity or unfairness
• Audience perceptions of friendliness

This covers various surveys, from census reports to consumer and workplace diversity, equity, and inclusion (DEI) surveys.

Why Precision in Survey Questions About Ethnicity is Critical

Unfortunately, poorly framed ethnicity questions and survey programs with little forethought can create extraordinary ethnic data biases. These ultimately mislead stakeholders in constructing programs to engage diverse audiences. For example, in the health arena, a few racial and sample ethnicity survey questions that have created bias are as follows:

1. Perinatal mental health research during the COVID-19 pandemic uncovered that:

• 52% of the studies reflected sample compositions of over 80% white participants.
• 68% of the studies failed to offer detailed non-white participant descriptions, preferring broad categories like ‘ethnic minorities.’
• While racial data reporting is always a sensitive matter, this under-represented Black women’s elevated postpartum depression risk and maternal death rates connected to the pandemic.
• The prevalence of cross-sectional designs and social media recruitment guilty of the above errors significantly limited lower-income individuals’ participation in progressive health programs.

2. The Bidil study, a clinical trial that tested heart failure drug efficacy on self-identified African Americans, reinforced harmful racial stereotypes. Why? “Self-identification” alone was far too general. It inadequately covered ancestral genetics and complex social and environmental factors that inevitably contributed to disparities in health outcomes.

How to ask ethnicity questions in surveys

1. Frame every ethnicity survey question correctly

In surveys, both ethnicity and race play significant roles as identity markers, where:

• Ethnicity relates to cultural background, language, shared traditions, religion, and beliefs.
  • Examples of this are Latino, Irish, Italian, or Jewish
• Race involves physical characteristics like skin color, hair texture, or eye shape.
  • Examples of this are White, Black, Asian, or Native American.

Confusion often reigns when organizations, governments, workplaces, and educational institutions request your personal data in their applications and surveys. Why? Definitions are murky, messy, imprecise, and generally unsatisfying. That’s because it’s more “feel and art” versus science.

According to Tomás Jiménez, a sociology professor at Stanford University, “It comes from an observation of how people use these ways of categorizing themselves and each other.” Unfortunately, this lack of exactness frequently distorts feedback interpretation when relating demographics to outcomes.

2. Follow these step-by-step guidelines to get your survey questions for ethnicity right:

• Be clear and transparent about why race and ethnicity (R&E) are crucial to your data relevance. Throwing R&E into the mix as a standard practice, eventually leading nowhere, can be distracting and a waste of time.
• Where appropriate, choose to include options like “I prefer not to say” or “Other”.
• Create a dividing line between ethnicity and race concept questions, favoring specific versus generalized multiple-choice options. For example, replace “Asian” with “Japanese,” “Chinese,” “Korean,” or “Asian – other.”
• Use open-ended with closed-ended questions for better results. An ethnicity survey question example in this category is “What are your most important cultural influences?” or “How would you describe your racial origins?” They complement each other by compensating for their respective advantages and disadvantages. Consider the following:
  1. Closed-ended responses are easy to measure (i.e., quantitative), whereas you cannot do that with open-ended answers (i.e., qualitative).
  2. Using the two types together adds to the ratings with insights into why the scores are what they are.
  3. Closed-ended questions alone cannot evaluate the emotional and cognitive drivers behind audience responses. Open-ended probes can.
• Stay within your audience parameters by ensuring inclusivity that connects compellingly with your audience.
• Don’t hesitate to offer survey response options in multiple languages. Aligning with your audience’s first-language preferences compellingly indicates that you recognize their uniqueness and meaningful differences.
• Avoid ambiguous language, jargon, and potentially offensive content when phrasing your questions.
• Inject various well-conceived and fine-tuned inferences that may be meaningful for regional surveys where respondent audiences interpret things differently.
• Use the cloak of anonymity to ensure respondents that their racial and ethnic responses won’t boomerang against them.
• Don’t transgress regulatory rules and laws in your survey protocols. For example, the following are formats that govern different surveying initiatives:
  1. US – Census Bureau classification rules
  2. UK – ONS Ethnicity Groupings
  3. Globally – Ethnicity survey variations in Asia, Latin America, and Africa
  4. Data privacy laws – GDPR, CCPA, and best practices for compliance

Sample ethnicity and race survey questions

Based on the guidelines above, here are some innovative thoughts on leveraging ethnicity, culture, and race-centric questions. These provide groundbreaking insights into your marketplace and business with questions and cross-correlations that don’t offend:

FIRST SCENARIO:
Question 1: “What is your gender identity?”

1. Female
2. Male
3. Transgender
4. Nonbinary
5. Other (please specify)
6. I prefer not to say.

Question 2: “Which category below fits your background best?”

1. White/Caucasian
2. Asian
3. Native Hawaiian or Pacific Islander
4. Hispanic or Latino
5. African-American
6. Native American
7. Two or more
8. Other (please specify)
9. Unknown
10. I prefer not to say

Question 3: “What’s your first language?”

1. English
2. Spanish.
3. A Chinese dialect.
4. French.
5. Russian.
6. Dutch
7. Other (please specify)

As follow-up questions to each of the above questions (i.e., Question 1, Question 2, and Question 3 above), I suggest the following:

For employees – Follow-up Question A: In your answer to Question 1/2/3 above, how has it impacted your progression in the company? OR

For customers – Follow-up Question B: In your answer to Question 1/2/3 above, how has our brand aligned with your gender/ethnicity/first language?

1. Advantageously
2. Disadvantageously
3. Not decided yet
4. I don’t know
5. Other (please specify).

Follow-up Question 3 to both 1 and 2 above: Can you tell us why you answered Question 1/2 the way you did?

SECOND SCENARIO

Question 1: “What’s your age range?”

1. Under 18
2. 18-24 years old
3. 25-34 years old
4. 35-44 years old
5. 45-54 years old
6. 55-64 years old
7. 65+ years old

Ask the following two questions but not directly after Question 1 above:

Question 2: “Which of the following cultures fit your lifestyle best?”

1. Gen Z
2. Millennial
3. Baby Boomer
4. Generation X
5. None of the above.
6. I prefer not to say.

Question 3: “What date were you born?”

What’s the logic behind these interlinked but separated questions?

• Many people aren’t willing to divulge their age, often understating it (especially women), which means that responses to Question 1 may be untrue.
• However, the same reticence doesn’t exist when surveys ask people their birth date or generation affiliation (i.e., people tend to tell the truth about these).
• When you compare Question 2 and Question 3 answers to Question 1, you may detect an age discrepancy, leading to the conclusion you have an audience motivated to look and feel younger than they are (i.e., a psychographic segmentation).
• It’s pertinent for researchers in industries like luxury autos and fashion (e.g., cosmetics, scents, and apparel) to benefit from an insight that gives them a compelling point of difference to promote.

THIRD SCENARIO

Your question for global locations: The following is acceptable (as clues to cultural affiliations): “Where do you live?”

1. United States
2. Mexico
3. Canada
4. Brazil
5. Spain
6. France
7. Other (please specify)
8. I prefer not to say

The same question (“Where do you live?”) applies to regional or more localized surveys with different closed-ended response options:

1. City (please state)
2. Zip code (please state)

Cross-correlating these answers to the scenario questions above will create multi-dimensional insights. Knowing an exact neighborhood can give you extraordinary clues regarding religion, ethnic origins, and more.

I suggest contacting a customer and employee experience expert like Sogolytics to structure a survey program that optimizes your ethnic questions to fill in the gaps demonstrated by my example on “age” above. Its team will use AI-enhanced customized templates to quickly derive the most from your feedback with AI-enhanced personalized templates.

Traps that disrupt your ethnic questioning

In our article above, we highlighted that closed-ended questions with insufficient multiple choice options, non-anonymous with threatening overtones, and poor transparency are severe issues that repel participation. However, on a more subtle level, poorly designed questionnaires can still deconstruct responsiveness when the following closed-ended defects creep into the content:

1. Questions around sophisticated words that respondents with English as a second or third language (even English first language speakers) cannot understand:

• Two examples: “Our SM messages are intuitive.” Agree | Disagree AND “Did you find our UX/UI website instructions optimal?” Yes | No
  • Both are challenging to understand and made doubly tricky with limited answer options.
• “How do you feel about our recent algorithm explanations?”
  • An open-ended question that should be closed-ended, as follows:

    “How easy was it to understand the explanation of how our software can help you?”

    • Fully understandable.
    • Partially understandable.
    • Not understandable.
    • I haven’t read it.
    • I’m not sure.

2. Questions open to interpretation, confusing, ambiguous, or double-barreled

• “How much do you agree that the staff was not being unfriendly?” (Good luck to anyone who can fathom this out!)
  • Instead, “How do you rate our client support’s friendliness?
    • From zero to 5.
    • 0 = Extremely unfriendly.
    • 5 = Extremely friendly.
• “How satisfied are you with our product image and customer responsiveness?” (With one rating option, how does a respondent score the variables if they like one but not the other?).
  • Instead, remove “customer responsiveness” and rephrase it as “Choose an option below that best describes our brand value.”
    • Meets all its promises.
    • Meets some of its promises.
    • Meets none of its promises.
    • Not sure.

Conclusion

From corner to corner of this article, you will find examples of how leading survey questions routinely skew ethnicity data. I also provided guidelines on addressing this, alongside a consistent, watertight guarantee of respondent confidentiality/anonymity to erase bias in every ethnicity survey question.

I suggest partnering with Sogolytics, a company that knows the ins and outs of ethnic sensitivity in survey structuring. They can cover all your needs, from developing templates to customized closed-ended and open-ended questionnaires and ethnicity checks with AI scanning for biased or confusing questions. Their guarantee of best-industry standards means no reinforcing stereotypes, only great take-home value objective ethnic data. Contact us today for a no-obligation conversation about your survey needs.

Asking the right ethnicity survey questions doesn’t just help you collect better data—it’s a powerful step toward inclusion. If you’re ready to build smarter, more respectful surveys, Sogolytics can help. From customizable templates to advanced analytics, we’ve got you covered.

FAQs

Q1: How do well-thought-out survey questions about ethnicity help my surveys?

A: It’s important to design surveys that use diverse audience demographics, such as background, language, affiliations, customs, and race-centric preferences to impact your decisions and branding with broader inclusivity.

Q2. What are the nine primary rules for asking the right ethnicity questions?

A:

• Be clear and transparent about why race and ethnicity are relevant to your data.
• Provide multiple-choice questions like “I prefer not to say,” “other.” or “I don’t know” as options.
• Create a dividing line between ethnicity and race concept questions.
• Use both open-ended and closed-ended questions.
• Stay within your audience parameters when formulating questions.
• Avoid ambiguous language, jargon, and potentially offensive content when phrasing your questions.
• Make your surveys anonymous.
• Don’t transgress regulatory rules and laws in your survey protocols.
• Don’t hesitate to conduct surveys in multiple languages, aligning with your audience’s first-language preferences.

Q3. Can I use ethnicity in my questioning to get more out of my surveys?

A: Undoubtedly. Please read the examples above and talk to Sogolytics to provide an AI-powered framework.