A leading question contains an opinion or viewpoint that pushes the interviewee to respond in a particular way.

How you frame your interview and survey questions can change the answers you get.

And, ultimately, make the research reliable – or unreliable.

What does a leading question look like?

Leading questions are found in every industry – from journalism to copywriting.

In journalism, ethics come into play.

Asking leading questions can present the interviewee positively or negatively, depending on how the writer edits the quotes.

In messaging research, though, leading questions are mostly unintentional because you want to get the best answers from your customers.

And asking great questions is how you write great copy.

Let’s try a little quiz:

Which question do you think is NOT a leading question?

  1. Our customer service team always gets 5-star reviews! How was your experience?
  2. How do you find the user experience on our app?
  3. Which restaurant do you prefer to order from, McDonald’s or Wendy’s?

If you said question #2, you’d be correct.

It’s the only question that doesn’t limit the respondent’s answers.

Question #1 leads with an interlinking statement.

The statement “always gets 5-star reviews” makes the respondent think they should be answering more positively.

Even if their experience wasn’t amazing, they’re second-guessing that opinion because they’ve just been told everyone else gives stellar reviews.

Question #3 is based on assumption.

This type of leading question assumes that the respondent likes to order from the two restaurants.

It gives no option if the respondent doesn’t care for either. They have to choose one of the two.

The big issue with both questions is they give the respondent a limited choice of answers.

Text reads: A biased question example is, "What about your recent experience with our phenomenal customer support team did you enjoy the most?"  An unbiased questions example is, "What prompted you to reach out to our customer support team?"  The biased or leading question makes the assumption that the customer had a positive experience. 
The unbiased question asks about the circumstances behind the customer's decision-making without the lack of objectivity.
Jen Havice

“Leading questions introduce bias into your research”

Says Jen Havice.

And she should know. Research is what she does.

According to Merriam-Webster, bias occurs when one outcome is favored over another and is encouraged in the testing process.

We’ve all been in those situations where someone asks us a question, but they already know the answer they’re looking for.

And you’re left wondering, “Well, why did you even ask me?”

Image of Leonard (man with glasses and brown shaggy hair) from the Big Bang theory. Text reads: Are you even listening to me?!
Source

The same thing can happen with leading questions.

When you try to sway your respondents one way, they’re left feeling unheard because they couldn’t answer honestly.

This leaves you with unreliable data because the answers were what you wanted to hear.

Not what your respondents wanted to tell you.

Re-wording a leading question to get reliable data

If there’s bias in your questioning, there’s most likely bias in your copy.

And no one wants that.

So how do you fix the leading question?

Write out your questions beforehand.

This way, you can objectively look at your word choices.

Have someone else read your questions and ask if they felt they should answer in a certain way.

Don’t assume.

You’ve heard the saying about what happens when you assume things, right?

Image of Lorelai from Gilmore Girls (brunette woman wearing a professional suit). Text reads: You know what they say when people assume things?
No, what do they say?
That you shouldn't.
Source.

By assuming your respondents’ knowledge, feelings or preferences, you’re cutting off their ability to give you a truthful answer.

  • Always include an “other” option in surveys with space to provide details.
  • For questions that might be sensitive, have a “prefer not to answer” choice so that people continue with the survey.
  • In an interview, try your best not to put words into people’s mouths.

For example, “it seems like you really struggled with…” or “you must’ve been angry when that happened.”

Instead, ask, “how did you feel when…?” or “was it easy or hard to…?”

Watch your wording.

Sometimes the words we choose are not the most effective to remain completely objective.

Even seemingly minor uses of words like “old” and “new” can impact the reliability of the answers to your questions.

Text reads: Is the new design easier to use than the old one? The use of "new" and "old" cues respondent expectations, which are also primed to consider whether the changes make the website "easier" to use.
Was one design easier or harder to use than another? This phrasing eliminates the bias introduced by old vs. new and gives equal weight to a positive or negative experience.
CXL Blog

Stay neutral.

To ensure you get reliable data, Jen offers this:

“Stay as neutral as possible with your wording and steer clear of framing the question positively or negatively.”

Jen Havice

Using adjectives like “excellent” or “horrendous” can compel your respondent to answer in a similar way.

Instead, ask the respondent, “how would you describe…?” or “what do you think about…?”

You can see how these questions are becoming more open-ended, which is how most of your research questions should be.

You can ask the right questions!

Asking leading questions is usually an unintentional habit when we research, but you can get better at avoiding them.

In this video, Anna Bolton explains how she used surveys and reliable data to write a sales page for Copyhackers.

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Practice makes you better

Writing survey questions without bias can be tricky.

It takes commitment and a bit of practice to look for potential bias every time you ask research questions.

  • Reading over your questions and getting a second set of eyes on them will make it easier to ensure you stay neutral.
  • Focus on the language you use and be clear and concise when writing the questions.
  • Remember that honest answers = reliable data.

And that reliable data will give you awesome insights to use in your copy.