People use the terms “questionnaire” and “survey” interchangeably, believing they’re the same thing. However, they’re entirely different concepts, although integrated in numerous cases. “How long is a piece of string?” is a much-used (somewhat facetious) question when one wants to point out something immeasurable, but in the case of the Questionnaire vs Survey debate, the latter is definitely a much longer thread than the former.
What is a Questionnaire?
A questionnaire adequately describes itself. How and why? It’s a format containing text or audio lines (i.e., content), each requiring (or implying) a question mark punctuation. Looking at them from a bird’s eye, you see or hear a set of questions or statements that require an answer.
Questions can vary significantly in their presentation and the answer options open to respondents. Three questionnaire structuring directions come to mind:
A. Closed-ended questionnaires:
As the name suggests, a closed-ended questionnaire includes only a limited number of possible options. At its most basic, a dichotomous closed-ended questionnaire offers only a pair of possible answers for each question. For example:
- Yes or No
- True or False
- Agree or Disagree
- Fair or Unfair
This kind of questionnaire narrows the field to uncover a definite opinion or understanding that’s black or white with no shades in between. In other words, it delivers absolutes, leaving no doubts about the respondent’s position. For example:
- Would you recommend Brand X to your friends? YES or NO
- I would repurchase brand X: I AGREE or I DISAGREE
The benefits of a dichotomous questionnaire are that it’s simple (often short and to the point) and easier to engage the respondents. By narrowing down the answer options available in this way, dichotomous questions are great for clarifying opinions or understanding on something, with recipients providing absolute answers – one way or another.
The most significant drawbacks are:
- It does not indicate what’s behind the answer (i.e., the dynamics that created the stated standpoint).
- It leaves zero room for respondents with extreme or middle-road views on the subject (e.g., STRONGLY DISAGREE or STRONGLY AGREE) or those who, if they had the chance, would mark off NEUTRAL or UNDECIDED as their positions.
- It may be limiting and, with that, frustrating. Why? Respondents may want to say more but, without the opportunity, bounce from the questionnaire.
- A query list that’s too long and filled with only dichotomous options is generally tedious, leading to incompletion.
Users of questionnaires understand the pros and cons, thus injecting creativity, leading naturally to innovative extensions of the strictly “yes or no, agree or disagree” probe type. Read more on this below.
B. Hybrid and open-ended questionnaires:
Hybrid questionnaires fall closer to close-ended as described above but offer a little more latitude (i.e., more than two optional responses). The most common ones in this category are:
- Multiple choice questionnaires (e.g., Which of the four answers is closest to your feelings about….)
- Scale questions (e.g., rate yourself on your feelings about the following statement: Both political candidates are so flawed I cannot vote for either. Strongly agree | Agree | Disagree | Strongly Disagree | Not Sure
An open-ended questionnaire is one where anything goes regarding responses. Why? To dig deeper, you must allow the respondent to freewheel. Frequently, a questionnaire with closed-ended, multiple choice, or scale questions will follow up with a question like, “Why did you respond the way you did to the previous question?”
So, taking (b) above as an example, the respondent ticking “Strongly Agree” might say, “I don’t see Candidate X offering policies that will change things, and I don’t believe a word of what Candidate Z tells us he can do.” These are valuable insights into motivations, thoughts, and emotions.
Example: A healthcare questionnaire
When you visit a physician for the first time, they provide a questionnaire with a long list of questions to answer, such as:
- Are you anemic? Y N
- Do you take medications? Y N
- If so, what are they? ……………….
- Have you been hospitalized in the last year? Y N
- How bad are your headaches when you get stressed?
- Rate yourself on a scale from 1 to 10, where 1 is hardly noticeable, 5 is throbbing but mild, and 10 is a full migraine. 1 2 3 4 5 6 7 8 9 10
The above represents the tip of the iceberg a medical questionnaire can bump you into when entering the doctor’s waiting room. The one thing you can be sure of when facing a questionnaire is that the originator wants to find out what you know or think about a topic (in this case, your health), but it could be anything under the sun, such as:
- Your recent brand experience.
- Satisfaction or dissatisfaction with a support agent interaction.
- Your work skills and resume
- Your bucket list of travel destinations.
- The pros and cons of a hospitality event.
- Your views on a political initiative.
- Economic volatility effects on your lifestyle
Indeed, questionnaires are robust tools organizations use to research a broad subject range.
What is a Survey?
Here’s the thing in the Survey vs Questionnaire debate: A standalone questionnaire’s most distinctive characteristic is that it applies to the individual answering the questions and goes no further. Strictly speaking, it’s a survey. Why? You’re surveying the responses of a single person, whereas the traditional definition of a survey covers response data derived from the same questionnaire across multiple respondents. In other words, many surveys may involve a questionnaire presented to people one at a time, but it goes significantly further with strategies that require:
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- Questionnaire design focused on a strategic result beyond that component alone.
- Accumulating the data from several questionnaires on a timeline.
- Feeding it into a data analytics model.
- Curating the output of biases, incomplete fields, and errors.
- Analyzing the results to shed light on the strategic goal.
- Testing accuracy.
- Recycling the process with adjustments.
So, staying with the health example under “What is a questionnaire?” consider the following as an integral part of an online survey program:
- It begins with physicians’ consensus on what they need to know about their patients.
- Using that as a foundation, they structured a questionnaire that puts all participants’ health profiles on the same page.
- Analysts accumulated and collated data (without IDs attached to protect privacy) as the patient-specific data streamed in. Thus, it extended across several (even hundreds or thousands) respondents answering the same questionnaire.
- They fed the data into an AI-enhanced data analytics model to create insights, which can stratify the respondents’ no-ID information by:
- Age, gender, race, occupation, and other demographic criteria.
- Behavioral characteristics like exercise, diet, alcohol consumption, drug habits, and special aid assistance.
- Pre-conditions.
- Insurance coverage.
- The next step involved evaluating the insights delivered by the data output, followed by disseminating valuable information that may help the health of millions.
- Finally, the sponsors reviewed the latest information to determine if:
- It’s wise to delete questions on the original questionnaire or add others.
- Subdivide the primary questionnaire into categories for more in-depth probes.
In short, a survey extends far beyond the questionnaire one-on-one respondent borderline, using the latter as a penetrating tool. However, some surveys have no questionnaire in the equation, such as how many cars pass by a highway marker per hour during peak and non-peak traffic or the polling numbers per day during voting season. Still, most aim to go beyond observation facts by deploying a questionnaire (or more than one) to derive qualitative information.
Modern-day surveys: Survey vs. questionnaire data collection
AI-enhanced technology has changed the face of survey capabilities, taking it far beyond the questionnaire as a signature piece. Software algorithms have the power to scan SM reviews, customer phone-in recordings, interactions with chatbots, customer searches on their mobiles, and other behavioral situations, drawing psychographic conclusions that help define the audience at a deeper level.
Here are the five most popular survey types:
- Online Surveys – An upgrade of “old-school” mail surveys (which still exist, too!) on websites, apps, and social media after requesting the audience to participate by clicking on a questionnaire. Why is this not only a questionnaire? Hundreds of audience members will likely contribute thoughts, feelings, and reactions that energize surveying.
- Chatbot Surveys or Face-to-Face Surveys (with live agents sometimes merging with phone surveys) – A subset of (1) above, except AI enhancement may throw in variable questions depending on participant responses. Again, questionnaires are in the mix but emerge relatively unstructured.
- Focus Group Surveys – Similar to face-to-face surveys except with a group of six to ten people. Selecting a target population representative group is a challenge but professionally surmountable. Still, once past that and with a flexible questionnaire, it invites the group participants to respond openly on a topic under a moderator guiding the conversation.
- Panel Sampling – Observing a selected group of people in a (mainly) blind sampling and asking them (with closed-ended, scaled, hybrid, and open-ended questions) to:
- Identify the brand.
- Select the best and the worst of the bunch based on taste, ease of use, etc.
- Rate the samples on a provided scale.
- Recommend improvements based on personal experience.
- SMS Surveys – Short text questionnaires (usually one close-ended question or two with a “Why did you respond to our question the way you did?”) play right into the survey formula with thousands of respondents.
Choosing the right tool: Survey vs. questionnaire in research
Having read this article so far, I’m sure you conclude we’ve answered this question in several ways. In most survey cases, one cannot create a meaningful model without questionnaires as part and parcel of the model.
So, it’s not a matter of choosing between the two but how to overlay questionnaires on survey configurations to create effective strategic results. A questionnaire format stands alone for situations focusing on an individual (e.g., medical history, as in our example above). For everything else (extending into survey territory), it’s an integration of the two concepts.
Sogolytics’ primary focus is survey design and strategy, embracing everything relevant to questionnaire deployment. The online consultancy has vast experience and resources at your disposal ready to help you tackle the following:
- Selection of questionnaire formats.
- Survey complexities and designing cost-effective strategies.
- Marketplace and workplace situations for both concepts.
Contact us today for an optimal survey/questionnaire strategy that will help you achieve your current and future goals.
FAQs
Q1: What is the difference between a questionnaire and a survey?
A: A questionnaire is only content, whereas surveying involves an extensive process that usually includes questionnaires in the model.
Q2: What are the similarities between a survey and a questionnaire?
A: When the survey is underway, it looks like a questionnaire to respondents. However, there’s no resemblance when reviewing the process behind it and going forward.
Q3: When should I use a Questionnaire vs Survey in research?
A: Questionnaires without survey connection work when the results count for a single person. Surveys rely on anonymous results covering more than one person (i.e., the results are data-centric). In these instances, questionnaires are components but certainly don’t dominate a far more inclusive process.
Q4: What are the advantages of using a questionnaire vs a survey in data collection?
A: The article above focuses on the two concepts as integrative, which means this isn’t a question we can answer convincingly. Most surveys can’t do without questionnaires in the mix, and the only time a questionnaire stands alone is when data-centric objectives are irrelevant.
Q5: How do the goals of a questionnaire differ from those of a survey?
A: Questionnaire without survey connection: When the results count for a single person. Surveys: When the results cover more than one person without IDs attached (i.e., the results are purely data-centric).
Q6: Can a survey include multiple questionnaires?
A: Yes.
