A question of insight

In the rapidly evolving world of brand engagement and marketing, understanding your audience through effective market research is paramount. A well-designed questionnaire is a fundamental tool in this process, enabling you to gather accurate and insightful data.

This guide outlines the three crucial steps and best practice in designing a market research questionnaire, emphasising the importance of thoughtful construction to achieve meaningful results.

Step 1: Define Your Objectives

Start by clearly defining what you want to achieve with your market research. Your objectives will guide every aspect of the questionnaire design, from the types of questions you ask to how you plan to analyse the results. A lot of brands use market research to cover off many issues and while it might seem good way of getting consumer insight on a broad range of topics, the danger of this scatter gun approach is that you can only ask a limited number of questions on each issue. You could miss out on detail with such a broad brush approach.

Be clear about your priorities as a business and stick to gathering information about them. remember, that you only have around 15 minutes maximum to hold respondent's interest with an online survey, so prioritising is vital.

Step 2: Choose the Right Question Types

In market research, the types of questions you choose can significantly impact the quality and usability of the data collected. Here's a more detailed look at different question types:

Closed-Ended Questions: These questions are structured to provide specific responses. They are easy to analyse and are essential for quantitative analysis. Examples include single-choice and multiple-choice questions and rating scales.

• Example: "How often do you use product X?" with options 'Every day', 'most days', 'once or twice a week', 'less often than once a week','never'.
• Analysis Advantage: Simplifies data collection and analysis, allowing for straightforward statistical analysis.

Open-Ended Questions: These questions allow respondents to answer in their own words, providing richer, qualitative data. They are crucial for understanding motivations, feelings, and attitudes in depth.

• Example: "For what reasons do you buy product X?"
• Analysis Challenge: Requires thematic analysis or coding to categorise responses, which can be time-consuming but offers deeper insights.

Rating Scales (Likert Scale): Used to assess attitudes or opinions on a continuum. These scales are effective for measuring the intensity of feelings about a particular topic.

• Example: "On a scale of 1 (very dissatisfied) to 5 (very satisfied), how would you rate your satisfaction with product X?"
• Analysis Nuance: Allows for nuanced understanding of attitudes and can be used in various statistical analyses, including mean scores and trend analysis.

Ranking Questions: These questions ask respondents to prioritise or rank preferences in a specific order. They are useful when you want to understand relative preferences or priorities.

• Example: "Please rank the following features of product X in order of importance to you: Durability, Design, Price, Brand Reputation."
• Analysis Insight: Helps in understanding the relative importance of different factors and can inform prioritization in product development or marketing strategies.

When questions go bad

Getting it wrong has serious implication for your research. Here are a few examples of bad question design and the impact it has on the overall research.

Vague or Ambiguous Questions:

• Bad Example: "Do you think product X is just right for your needs?"
• Why It's Bad: The term "just right" is vague and subjective, leading to varied interpretations by respondents.
• Implication: Data collected will be inconsistent and unreliable, making it difficult to draw any meaningful conclusions.
• Solution: Ask respondents to select words from a list that best describe their attitude to the product or use a ratings scale to measure consumer responses to attributes such as price, design, effectiveness and so on.

Double-Barrelled Questions:

• Bad Example: "How satisfied are you with product X's price and quality?"
• Why It's Bad: This question addresses two different aspects (price and quality) simultaneously, making it impossible for respondents to give a clear answer if their feelings about each aspect differ.
• Implication: Responses will be confusing, and it will be impossible to discern which aspect (price or quality) the feedback is referring to.
• Solution : Ask about each attribute in turn.

Leading Questions:

• Bad Example: "Don't you agree that product X is the best in the market?"
• Why It's Bad: This question is leading, as it suggests an expected response, influencing the respondent to agree.
• Implication: Results will be biased towards positive feedback, failing to provide an honest assessment of the respondent's true opinions.
• Solution : Use statements and ask respondents to pick which one they agree with the most. It's important to have balance, eg two positive and two negative statements with a neither/nor option in the middle.

Questions with Assumptions:

• Bad Example: "Do you use product X daily, weekly or monthly?"
• Why It's Bad: This question assumes the respondent uses the product daily, which may not be true.
• Implication: Respondents who don't use the product daily might either skip the question or provide inaccurate responses, leading to misleading data.
• Solution: Split into two questions. First question should give a list, including yours, and ask which one is used (if any), and then ask a second on frequency of use.

Complex or Technical Questions:

• Bad Example: "What is your opinion on the efficacy of our product X's proprietary technology?"
• Why It's Bad: The question is too technical for a general audience and assumes a level of knowledge the respondent may not have.
• Implication: Respondents may be confused, leading to skipped questions or made up responses, thereby compromising the data's integrity.
• Solution: Use plain language and ask respondents to assess each attribute in turn.

Step 3: Design with Analysis in Mind

This step is crucial for ensuring that the data you collect can be effectively analysed to meet your research objectives.

• Align Questions with Objectives: Make sure each question directly contributes to the objectives of your research. If a question doesn’t provide data that can be used to answer your research questions, it might be unnecessary.
• Consider Data Analysis Methods: Think about how you will analyse the data while writing the questions. For quantitative data, consider the statistical tests you might use (e.g. regression analysis, t-tests) and ensure your question format is compatible. For qualitative data, plan for thematic analysis or content analysis and structure questions to facilitate this.
• Pre-coding Open-Ended Responses: If you plan to include open-ended questions, consider how you will categorise responses. Developing a coding scheme in advance can streamline the analysis process.
• Pilot Testing for Data Analysis: Pilot testing helps not only in refining questions but also in testing your analysis plan. It can reveal if certain questions are not yielding the type of data needed or if the responses are too varied to be analysed effectively.

Conclusion

In conclusion, a well-designed questionnaire is a critical tool in market research, providing valuable insights that can shape brand and marketing strategies. By following these steps and focusing on clear, unbiased, and purpose-driven questions, brand and marketing managers can ensure that their research effectively captures the voice of their customers, leading to more informed and impactful business decisions.

Remember, the key to successful market research lies not just in collecting data, but in collecting data that is accurate, relevant, and actionable.

With a bit of time and experience, brands should be able to navigate these steps. But if time is tight and experience limited we are happy to help ensure you get what you need from research. We offer a range of research services from a free questionnaire health check to undertaking the full process for you. Please get in touch to find out more.