Each research question requires its own way of researching. For some research questions, the answer is best found by doing qualitative research. For other inquiries, quantitative research is more appropriate. But what exactly do qualitative and quantitative research entail? In this blog, I will explain this to you.

Qualitative research is aimed at obtaining information about what matters and why. It provides in-depth information by examining the underlying motivations, opinions, wishes, and needs of the research group.

The following methods are appropriate for qualitative research:

• Individual in-depth interview or a Duo interview;
• Group discussion;
• Observation;
• Mystery guests.

Quantitative research focuses on quantity. It gives you numerical results about a specific group. To speak of representative research, you need a minimum number of participants within your target group who give their opinion. For this, you can draw a sample. When this sample has a specific size and characteristics (depending on the research question), statements can be generalized to the entire target group.

For quantitative research, a (digital) questionnaire/survey is primarily used as a method. The answers from the questionnaire are then processed in a data processing program (e.g., Excel or SPSS), after which you can conduct analysis and calculation. Percentages and numbers usually describe the results.

In my next blog, I will explain for which answers it is best to do qualitative research and when, on the contrary, it is wiser to choose quantitative research.

A questionnaire is a commonly used research method to measure the effects of an activity, project, or program. The question is whether a questionnaire is always an appropriate method. Do you want to make statements about the entire target group and collect a lot of data? Then it is a smart method. Do you want insight into the underlying motivations and opinions of your target group? Then a questionnaire is a less wise choice. Why is a questionnaire a good method, and why a less good method? Here you will find the pros and cons explained:

Pros:

• It allows you to survey a large group of people. This is necessary if you want the results of your research to be representative of the entire research group. You can then make statements like: '80% of the visitors say they learned something from the activity'.
• An interviewer or observer cannot influence answers; this ensures objectivity.
• The way of asking questions is standardized, ensuring unambiguous answers.
• In-depth statistical analyses can be made, for example, to subgroups or to establish correlations.

Cons:

• You have little influence on the response rate, often resulting in a relatively low response rate with this method.
• The respondent cannot tell his story freely; the answers are primarily pre-programmed.
• Respondents tend to answer socially appropriately, even when it is anonymous.
• Underlying motivations are difficult to ascertain with a questionnaire, making the questions and answers superficial. There is no option for follow-up questions.
• Respondents cannot complete the questionnaire. If they quit at the halfway point, it is of little use.
• You can ask a limited number of questions, as response rates drop the more extended the questionnaire is.

In conclusion, questionnaires can be a valuable research tool when applied correctly and when the research objectives align with the method's strengths. They are particularly useful for gathering data from a large and diverse audience, enabling researchers to make generalizations and perform in-depth statistical analyses. However, the limitations of questionnaires, such as potential response bias, inability to probe underlying motivations, and low response rates, should be carefully considered. Depending on the research goals, it may be necessary to complement questionnaire data with other research methods, such as interviews or focus groups, to gain a more comprehensive understanding of the target group's opinions and motivations

When you conduct interviews, you can find out a lot. You collect primarily qualitative data. (There are some tricks to collect quantitative data as well.) Before you start an interview, it is crucial that you have well-defined interview questions. Because you don't ask questions just for fun: respondents have to answer the central question of your research. That is why I am giving you tips on how to design your interview questions as well as possible:

1. 1. Have clearly worded main and sub-questions ready.
   2. Ask questions that connect to your main and sub-questions. To ensure all of them can be answered, mark behind each question which main or sub-question the question connects to.
   3. Put the questions in a logical order that avoids overlap.
   4. Include introductory text in your interview questions. This text should state why participants are being interviewed and how long the interview will take.
   5. Formulate your questions so that the interviewee understands them. You can test this by practicing the protocol with your colleagues. This way, you will also notice if your questions are asked in the proper order.
   6. Make sure to ask your questions objectively. This will prevent biases that will cause the research to produce the wrong answers and will allow for continued questioning during your interview. Prejudice occurs when you ask leading questions such as "Don't you agree?", "Would you...?" or "Is it true that...?".
   7. Make sure there is room to ask more in-depth questions. In-depth questions start with 'why', 'how', 'what' and 'who'. In these questions, you will find the 'gold nuggets' that will provide special insights for your research.
   8. Write a closing text explaining what will be done with the survey results.

   Finally, I would like to inform you that remaining objective during the interview is essential. Your own opinion plays no role in this; make sure the interviewee can tell their own story.

   More tips to prepare for your interview? Then please read my blog '15 tips for a good interview'.

Suppose you want to research a target group of as many as 10,000 people. Do you have to interview all 10,000 people to get the right results? Certainly not; only a part of the research population needs to participate in your research to get representative results. Let me explain what representativeness means and when the results are deemed characteristic.

Representativeness means the degree to which the respondents in a sample group are a good reflection of the target group of your research. Therefore, your research is representative, which means that the conclusion of your research is true for 'everyone' in your research population.

A sample

If you have a research population of 10,000 people, you will ultimately need to interview 400 people to arrive at the opinion of the larger group. This does not mean that you only need to approach 400 people. You have to deal with a response rate. This is the percentage of people who participate in your survey. Your response rate depends on the subject you are researching, how easy and fun it is to participate in your research, and what people get in return. I often use a response rate of 30% because I usually research fun subjects, and I am experienced in making it easy to participate in a survey. I also ask the client for a nice gift for the people who participate in the survey. Tips to increase your response rate

Because not everyone will participate in your survey, you will need to have a larger sample group. If you need 400 respondents and assume a response rate of 30%, you will need to interview a sample group of 400/30%=1,333.

When you conduct a survey, you must keep in mind that the smaller the research population is, the larger the number of respondents will be to arrive at the desired representative results. Sometimes, however, respondents' input is more valuable than the number of participants. In this case, you're referring to qualitative research, and it can be more important to focus on the research results than the representativeness in some cases.

If you want to know how many respondents you need for your research population: go to a sample calculator. These will often immediately tell you how many people you need to approach in your sample.

The range of research methods on offer is enormous, so you can sometimes not see the wood for the trees. That's why I give you a handy overview of different research methods in this blog. With some of the research methods, you will find a link to a blog with more information.

In this overview, I characterize quantitative and qualitative research methods. Would you like to know more about these? In my previous blog, 'When to choose: qualitative research or quantitative research,' you will find information about the difference between these two types of research.

Qualitative Research

• Group discussion: Conversation or discussion with several people about one or more topics.
• Individual interview: Structured or unstructured conversation with one person in which you go into detail about one or more topics.
• Literature Review: Research in which you use research, theories, and information already available (e.g., from a library or on the Internet) based on a problem statement.
• Mystery visitor: Research method in which you use experts who behave as customers or visitors and assess the quality of service or organization.

Quantitative research

• Observing: Observing actual behavior and recording responses.
• Questionnaires: Recording data and opinions of groups of people using a pre-prepared questionnaire. You can have this questionnaire completed digitally or in writing by a large group of people.
• Tear tickets: A research method in which you get a large group of people to answer one question quickly. This can, for example, be done by giving the audience a piece of paper with a statement on it before a show. After the show, the audience can indicate whether they agree or disagree with the statement by making a tear in the piece of paper.
• Existing source research: conducting research using existing datasets of quantitative data that other researchers have already collected. You then use the dataset again to answer a new question.
• Informal conversations: During an informal conversation that is already taking place, you will ask a few specific questions. You record the answers afterward and repeat them to multiple respondents. The respondents are not aware that they are participating in a survey.
• Ten-minute interviews: Short interviews to find out about respondents' experiences, opinions, and motivations. It is stated in advance how long the interview will last. You can use a timer.
• Tracking: following respondents (e.g., visitors to a museum or customers in a store) through a distinct area. This can be done through the Wi-Fi or Bluetooth of their own devices, but also with a device that you give to respondents, with which you follow them.
• Logbook: A document (digital or written) in which you have visitors or participants record events and specific data.

A questionnaire is used as a measuring tool to answer your research questions. It is essential that you can use the results of the questionnaire. The quality of the questionnaire determines the quality of the data collected. It is therefore important to carefully formulate the survey questions. Here are a few tips and rules of thumb to help you formulate well-structured questions:

1. Keep the questions simple. Don't use complex language, and consider your audience in your choice of words. For example, "What do you prefer to do in your free time?" is better than "How do you prefer to relax?
2. Provide an unambiguous interpretation. 'I am satisfied with the quality of the exhibition' is an example of how not to do it. What is quality? The type of artwork, interactive elements, crowds, venue, the light?
3. Formulate the question as precisely as possible. Refer to place and time and mention numbers. Try to delineate questions such as "Have you recently..." to a specific period, for example, "Have you in the past six months...".
4. Avoid vague wording and avoid terms like ‘often’ and ‘sometimes’, also in the answer categories. Everyone interprets often and sometimes differently, so it is better to ask for a specific number of times.
5. Avoid duplicate questions. No 'and' or 'or' in the questions. A question like "What did you think of the performance and the actors?" cannot be answered with one answer if the audience thought the performance was a little off, but the actors were excellent.
6. Do not formulate (double) denials in the question. A negation in the question is confusing. For example, 'I am not dissatisfied with what I have seen' or 'I don't like to visit a museum.'
7. Ask short questions.
8. Be careful with examples in the question and suggestive questions. Chances are that the respondent may only think of these examples. This can happen with a question like 'How often do you undertake a cultural activity such as a visit to a museum or a play.' The respondent will be inclined to think that a visit to a festival or a dance performance is not part of the equation.
9. Make sure the question measures up: The question should answer the research question. If you want to know if an exhibition inspired someone, do not ask how long they stayed. It is possible that the length of stay was longer or shorter because the respondent had to wait or had to leave earlier and had no choice.
10. The answer categories to the questions should be mutually exclusive, and it should be clear to the respondents which answer to tick/indicate.
11. Provide the same direction in the response order for scale questions. If at one point you are asked to rate something on a scale from totally disagree to totally agree (increasingly positive) and a few questions later on a scale from very satisfied to very dissatisfied (increasingly negative), there is a chance that people will fill this out incorrectly.
12. For scale questions, try to keep the scale the same for each question. So do not use a scale of 1 to 5 for one question and a scale of 1 to 7 for another. This also makes it easier to analyze.
13. See which scale fits best. A rating scale of 1 to 10 offers a lot of variation but is also more challenging to interpret (for some, a 10 is good, others think a 10 is perfect and therefore don't give it easily). A 2 (good/bad) or 3-point scale (good, average, bad) offers minimal variation and makes it harder to answer a question if it is an opinion (opinions are typically nuanced). An even scale causes a respondent to have to choose; with an odd scale, you offer the opportunity to sit safely in the middle.
14. Also, provide the option of a reasoned non-answer, for instance, by creating an answer option like not applicable or don't know/no opinion.