Examples Of Survey Questions

Market researchers are called upon to provide fresh, current information about a target market and/or product. For example, a study might be conducted to find out if people are planning to upgrade their cell phone in the next year, and what kind of phones they are looking to buy.

Naturally, you will decide on a data collection method and send out surveys or conduct focus groups. In this instance, a combination of online survey and in-person focus groups might be chosen. It is a good idea to supplement these methods with some external research.

This will add weight to whatever is discovered through the online survey and focus groups. For example, if 70% of online web survey respondents and 84% of focus group participants say they plan on upgrading to a smartphone like the iPhone or Blackberry, that makes a strong statement in favor of smartphones. You can supplement this finding with market information on smartphone sales. If the research shows steady increases in sales of smartphones, that strengthens the market research finding. However, if it shows declining sales, it provides additional insight. It might even indicate a need to broaden the target group for the survey – perhaps they are early adopters and very technology conscious.

If you do use external research to supplement or add insight into your findings, be sure to use reputable sources and cite them correctly.

I’ve previously emphasized how important it is to consider survey reporting not only after you’ve collected data, but at the beginning and throughout a survey project.  Another central tenet of good survey reporting is tailoring your report or presentation to your audience.

The formatting of your market research reports and presentations can vary dramatically depending upon who is going to receive them.  Even the content will differ based on the audience(s) who will read the report or view the presentation.  Here are two big questions to ask yourself about your audience, so you can tailor your reporting tasks accordingly:

1) Is this a lay or technical group of people? 
The more professional your audience is, the more technical you want to be when describing the results.  For example, if you are sending survey results back to respondents, you probably don’t need to go into statistical and methodological detail.  If you are presenting to market research colleagues, on the other hand, you would go into fairly deep detail regarding topics such as statistical significance, margin of error/confidence level, as well as include prior research citations and an abstract of your project.

2) Am I presenting this to senior officials and/or executive decision-makers?
Usually, the higher-up the ladder your audience is, the less time you spend on detail.  So if your answer to the above question is "yes," I like to use a five-minute rule: if someone had to make major business decisions based on your survey results, what could you present in five minutes that would help them make good strategic decisions?  What would be the “take-home” message (i.e., two or three data-driven recommendations based on your results)?

Although surveys are usually single point-in-time snapshots, it’s good to draw basic conclusions unless it would be inappropriate to do so... after all, you’ve likely spent considerable time and effort for the survey project to generate useful insights!

Sometimes we forget we can't be everything to everyone all the time. It's just not possible. It wouldn't make sense for a shoe designer to start creating hard hats just because a customer wrote on a comment card in response to a retail survey that she wished the designer also made hard hats because the her husband worked in construction. It seems obvious to most people, going into the hard hat market would be a bad call on the shoe designer's part. So why don't organizations have the same clarity when it comes to their business?

It can be hard to say no to customers, particularly when they have good ideas. But just because an idea is a good one, it doesn't necessarily mean it's right for your business model. Take the example many organizations have to face in their life time: where do they belong? Is it in the high end of the market, the mid-market or the bottom feeders? Most people when you ask them don't want to admit to being a bottom feeder, but there's a market need there that can be very profitable. The organization that can fulfill that need is very rarely, if ever, the same organization that can fill the need at the high end of the market. This just points out, again, that we can't ever be everything to everyone. I remember my marketing classes in college always told us you could only be two of the three things: good, fast or cheap. You can never be all three. Good and fast is expensive; fast and cheap is inferior; good and cheap is slow. It's because we can't be everything to everyone.

So how do you figure out what you should be? Your organization's mission should be a start, but missions can change and transform over time. One place you can start is to ask your employees, survey staff to see what they think the organization is and where they should be going. Employees have stellar ideas, but this may sound like a trick question so make sure to follow these tips for employee opinion surveys.

You should also ask for customer feedback. Your customers will help point you in the direction you should be heading. Sure you'll have the one off cases like with the shoe designer who's customer wants her to create hard hats for construction works, but chances are, no one else will respond that way on her customer questionnaire. And then, at the end of the day, you should be armed with the information you need to support your decision. As you're reading through survey comments, you'll notice that everyone doesn't want you to be everything.

With the emergence of widespread internet usage and powerful online survey software, the web has become the survey method of choice for many project managers and market research professionals.  Utilizing an online web survey design allows for levels of efficiency unheard of in traditional mail questionnaire projects, but it also poses new challenges for business survey researchers.  One of the questions that is asked often is, Is my customer feedback sample and/or survey data skewed because I used an online survey?

The answer could be either no, yes, or maybe, depending upon your specific research issues and target demographics.  The demographic that use the internet (and newer technologies in general) the most are younger people.  Those who are new to online technologies, or those who are not tech-savvy, might be intimidated or confused by a web survey form or an email survey invitation from an unknown sender, which can decrease your rates of nonresponse.  Also, you can run into the issue of coverage error for those who do not have internet access, which is more common among lower-income and less-educated individuals.

But overall, the reliability and validity of online survey results can be on par with or better than other modes, especially if you know your target audience well, including their rates of internet usage.  According to a September 2009 survey from the Pew Internet & American Life Project, 77% of all adults - and 93% of those ages 18-29 - use the internet “at least occasionally.”  Less than half of those aged 65 and older use the internet or send and receive email, however.

So while there are drawbacks to online questionnaire designs of which you should be mindful (as there are with any survey modes, such as interviewer bias, etc.), the efficiency and reduced costs are more than enough rationale for most to employ online data collection techniques, either exclusively or as part of a multi-mode survey design.  Knowing and understanding your target audience is the best way to be sure that your chosen mode will produce quality data.

Randomizing your online survey form or your answer options within a survey questionnaire, means that the listed items are not asked in the same order for each survey respondent.

So, participant A may see their question in this manner:


While participant B may see the question in this order:


With the advent of electronic surveys, this feature can now be done in an easy and cost-effective manner!

For many survey questions, rotating the order in which answer choices are viewed by your participants will minimize potential within-item bias. Say for example, customer service survey respondents tend to remember (and choose) the last option they read from a list, or conversely, the first option they read from a list, rotating the order of the options means that each option is read last as often as all the other options available. Ensuring that any potential bias is spread out across the options.

By randomizing your answer options for certain questions, you can be more confident that your results aren't over-estimating the number or frequency of participants who prefer dogs, to say, ferrets.

Read more about this topic to learn important tips on when you shouldn't use randomization of your answer options.

Quota sampling is frequently used in survey designs, and especially in market research projects.  This technique is a form of "convenience sampling," where respondents are chosen not at random, but because they are available or easier to reach.  A probability-based sampling design is not employed, due to decisions made by the researcher based upon various reasons: the population frame cannot be known, contact information for respondents is unavailable, or even because the time, effort and costs are simply too high for the budget.

Quota sampling is a way that you can gather completed questionnaires, producing adequate amounts of data, from people with different demographic attributes.  Often, market researchers want to ensure they get roughly equal amounts of data from males and females, may be interested only in a specific age range (i.e., their target market/demographic), or would like to know if preferences differ by other characteristics such as ethnicity and income level.

So where does the “quota” come into play?  Well, just as in stratified sampling, the population is divided into mutually exclusive subgroubs, often based on demographic characteristics.  The researcher sets a quota for each subgroup (100 females and 100 males, for example), collects data until the quotas are met, then stops data collection and begins data analysis.  The reason that quota sampling is not a probability-based sampling technique, thereby limiting your ability to generalize, is because respondents are not selected at random.  Quota sampling does go a step further than simply selecting whomever is available without regard to any criteria, and that's why it is used so often.

When conducting market research, either through survey forms or another mode, the method of sending a survey pre-notification letter can be a tempting one.

For some time now survey methodologists have been conducting studies of pre-notification letters to determine if they have any affect, either positively or negatively, on survey response rates. An overall analysis of these various independent studies revealed an increase in response rate of approximately 8% when compared against studies where no pre-notification letter was sent.

No one can say for sure exactly why pre-notice survey letters seem to assist in increasing the number of survey responses, but perhaps they help to establish the legitimacy of a survey, contributing to a respondent's feeling of trust and the credibility of the organization conducting the research. Another possibility is that a pre-notice letter builds expectation of arriving mail (be it electronic, paper, or in-person). A third possibility is that a potential respondent is less likely to disregard the survey when it arrives if they are aware it is arriving shortly.

Although survey pre-notification letters are an excellent (but sometimes expensive) way to increase response rates, they are seldom used in marketing research surveys. Each researcher needs to weigh the additional cost of sending out a pre-notice to potential respondents against the probability of a lower response rate.

It's worthwhile to take your population's survey sample size into consideration when coming to this decision. When your sample sizes are small, each individual response affects your survey results even more. Increasing those responses through utilizing a pre-notice letter may counterbalance the increased cost of sending them out to your participants.

In today’s competitive world, most of us find ourselves asking, What more do I get out of our online survey management software besides the obvious?

Well here’s one extraordinary feature you get along with the Cvent Web Surveys tool: A Robust Address Book. The Cvent Address Book is where you can store all you contacts; you can manually add new contacts if you need to update your records with just a handful of contacts or you can use our 4 Step Import Wizard to add bulk contacts in one go.

You can also export contacts out of the survey software if you need to update your personal database. For example, you want to be able to update contacts in your CRM system that attended your conference and completed your post-event survey so sales can follow up appropriately with attendees. Using the Cvent Address Book you can also merge duplicate contacts, create contact groups to help manage the Address Book more efficiently, or edit existing contacts to keep your records up to date.

Wait! There is more. In the Cvent Web Surveys application, you can not only run different reports to pull up information based on your address book, but also run reports to pull up information from your address book. Here is a list of some of our Address Book Reports:


If you are interested in knowing more about the benefits you can enjoy with Cvent Web Surveys, go ahead and sign up for a free trial account!

While designing a web surveys is fairly simple, make sure you are aware of common online survey pitfalls so you can avoid them:

• Plan the correct date and time to send survey invitation emails and consider your target audience. If your survey sample is office workers, it would be best to send it out during the work week when they will be at a computer most of each day. Do a little research on what the best day is – while it is widely known that Fridays, Saturdays and Sundays are not optimal, there is always new information on this topic. Don’t forget to consider the time zone of recipients too – if you are sending something that will land at 7 p.m. their time, it will likely be buried or forgotten by morning.

• Create your questions carefully. In an online web survey, the respondents are obviously on their own. You can’t clarify things for them. Make sure the questions are clear and easy to understand.

• Keep the open-ended questions to a minimum or you will be poring through the answers for hours. Respondents tend to be more forthcoming with electronic surveys, and this is a positive thing. But just because you can get all those open-ended responses, you may not really want them. Always be thinking ahead to how you will analyze survey data and present findings.

• Entice the respondents to take the survey. Many times online surveys fail to offer enough incentive. Even though online surveys are more convenient, the respondents are still volunteering their time and should be rewarded.

As is the case with any research method, there are advantages and disadvantages to using an online web survey to collect data about customers, employees or the public-at-large.  For example, online surveys offer you the ability to gather vast amounts of data from many respondents at the same time, get your data back in an electronic form, see real-time results and automate analysis/reporting tasks... and you can do all of this affordably.  You can even use a relatively small research survey sample to accurately estimate the opinions of your larger population (for survey research in general).

But in some cases, it is best to use a “mixed-methods” approach to your research project.  This means you combine the online survey method with another kind of investigation, such as interviews or focus groups, in order to produce more well-rounded data and conclusions.  Here are some examples of when a mixed-methods approach is likely better than an online survey form by itself:

We all know the holidays are getting closer, which means office pot lucks are about to become all the rage. What will you be bringing? How is your office going to make sure that not everyone plans to bring the same thing? How do you determine the winner of this year's Tastiest Dish Awards?

Competitions involving food are definitely a favorite around this time of year. However, if you have a big office, it can be a pain to collect everyone's votes. As I mentioned at Halloween, building polls to quickly identify the winner of your office Halloween Costume contest can be applied to the Best Dish Award too. Simply log into your web site voting poll software, make a poll to gather employee opinions on who should win this year's Best Dish Awards. Have different categories, such as best presentation, tastiest appetizer, most unique recipe? Add in images of the dishes to help jog people's memories and create one web poll using your poll maker.

Don't think that an online poll survey software tool can only play it's part at the end of the pot luck event, you can send a pre-event survey to find out who plans to bring what. If too many people are planning to bring dessert, a typical favorite, the online poll generator can easily run a survey report to identify categories with too many volunteers. You can easily create a survey contact group to email those volunteers and ask them if they can bring something else.

Holidays are a time to celebrate with family and friends, and eat delicious food. Unfortunately, we often make such office traditions a little more painful than they need to be by forgetting we can use a polling system or survey software tool we already have. Since Cvent Web Surveys doesn't limit the number of responses you can have, it wouldn't make sense to suffer through paper ballots when it can be done for you! Ready to create a poll for your next staff opinion survey? Get started with a free trial.

What are your other sample employee opinion survey examples?

A few weeks ago, I did a series of posts about the effect colors can have on individuals and how you should keep them in mind when designing a web survey. Today, I came across a survey form that reminded me again of the importance of your survey template's color scheme. When you're designing surveys, make sure you pick colors that are easy to read.


Can you read this question from a sample customer questionnaire? Probably. Is it easy to read? Do you want to answer pages and pages of survey questions writen with this color scheme? Probably not. Because it's hard to read, you will probably see a high abandonment rate and then you'll have to deal with speculations about nonresponse bias. To avoid having this issue, make sure to ask people if they find the survey easy to read when they're testing it for you. Believe me, you don't want poor color selection to decrease your response rate.

You can read more about the effects different colors have in these posts:

Last week, we reviewed poorly written survey question items, and what makes them inefficient tools for collecting the data you desire. For our final installment of "Writing Survey Questions the Work," we'll discuss some final points to keep in mind in order to write great questions.

In general when you design a questionnaire, try to write from the respondent's perspective rather than your perspective. Hark back to last weeks post where we discussed writing objectively and from a non-assuming point of view. Writing from neutral viewpoint and keeping far away from internal workplace jargon and slogans that wont be understood by your clients is key.

Having a sample of your survey population and other neutral testers review the wording of your survey is a wonderful way to attain clarity on question items. After spending what may amount to dozens of hours on a survey form project, having an outsider do things like proofread and spell check with a fresh pair of eyes can be well worth the effort!

And as we've talked about in other posts, pre-testing your survey with a segment of your audience is crucial to detecting question item mis-wordings as soon as they occur.

If we have poorly worded question items in our survey, not only will the answers we receive be inaccurate, our data analysis will be inaccurate as well. This could result in poor decisions being made based on data that has either overstated or understated our clients needs for a product or service. 

Staying in tune with the needs of our clients and our target populations starts with skillfully worded survey question items. If your question isn't worded right, your analysis wont be right.

One of the best descriptors attributed to good survey questions is the word specific.  A main goal in designing valid, reliable survey questions is doing everything in your power to make them clear, standardized and unambiguous.  A great way to follow through on that is to make sure your questions are as specific as possible.  The degree of specificity affects how people interpret and respond to your survey questions.  Several examples are listed below to help you analyze your survey questions regarding their level of specificity.

Be clear with demographic questions.  Your objective here should be to use words and categories that your respondents can clearly understand and identify with.  Will you use Census designations for Ethnicity?   Exactly what do you mean by “marital status?”

Define vague concepts, words and phrases.  Your respondents will likely widely differ with regard to their backgrounds, experiences and perceptions.  Words like “justice” and “equality” can mean very different things to people, so it is best to define exactly what you are asking about.

Objective or subjective?  Use verbs that trigger respondents.  Attitude survey questions are usually subjective (i.e., how do you feel about the war?), while behavioral questions are usually objective (i.e., what did you eat for supper last night?).

Always try to attach a time frame to behavioral and recall questions.

For market and product research, identify the actual brand name, and ask how they feel about specific items, not just groups or genres.  For example, don’t use the vague word “furniture” if you’re really interested in how they feel about a table or a chair.

Survey designing software can't look at your questions and tell you if your online survey form will give you the data you want. However, it does make it easier when you're designing a web survey because it takes out the added complications with writing your own code. So make sure next time you're working on an instant survey form, you think about the specificity of your survey questions.

When you plan your online market research study, you still need to remember the standard steps for any market research project, plus some online specific tasks:


The time frame for an online study is, as discussed previously, often shorter because of the immediacy of the results. Keep this in mind but be sure to give yourself enough time to analyze survey responses.

Surveys are an invaluable tool for researching the community attitudes, employee concerns, product needs, customer loyalty and priorities held by different groups or target audiences.  Designing a questionnaire and collecting survey responses from a sample allows us to draw a profile of the group as a whole, and perhaps perform some correlation analysis to understand the source of those feelings.  The online survey findings can then support fact-based organizational decisions or improvement projects to help continually improve the organization over time.

Survey research can be applied to many venues.  Here are just a few practical applications listed below:

An Internal Employee Survey could identify reasons for low employee retention and provide ideas for reducing those costs, such as a better designed benefit program, improved training opportunities, or problems in the way the organization functions.

A Training Survey can identify how a training program has improved the capabilities of some group and how the training program itself can be improved.  

A Product Satisfaction Survey can identify initial customer experiences with a product, providing data to address unforeseen problems and help the next product release.  

A Market Research Survey can identify customers needs when creating these new service and product offerings.  Surveys can be part of Design for Six Sigma activities.  

An Association Survey, which is similar to market research and customer surveys, can show the member benefits most of interest.

However, a survey program is only valuable if it is properly designed and executed.  While performing a survey project seems deceptively simple – it's just a bunch of questions, and survey software tools make electronic surveys quick and cheap – a small mistake in the survey questionnaire design or survey administration can skew or bias the data, leading to erroneous conclusions.  No organization should ever make critical business decisions based on unreliable or invalid data.

Bad data is worse than no data!

I’ve talked extensively in the past about using Facebook for market research. But there are other Web 2.0 sites that you can use effectively as well.

For example, Twitter is growing more and more. You can search on Twitter for keywords or competing products to see how often they are mentioned, and what people are saying. This is a quick and simple method of gathering background info.

There are many sites where people mark things they like or dislike, like digg and del.icio.us. Everything on digg is submitted by users and then ranked by users. After a story has enough “diggs” it is listed on the front page. You can search for your client and see what types of stories are making their way to the site and get an idea of what kind of buzz is surrounding them. Del.icio.us allows users to tag and bookmark their favorite pages, and then allows all users to access rankings. You can find out how many people have bookmarked your client and competitors.

Of course, both these groups are by their nature narrower than most studies require. Results for each page are primarily involving only regular users of the site. You should broaden your search to find other respondents so your data is more accurate.

Web 2.0 sites are great places to find information and do background research. They also tend to be good places to find electronic survey respondents, as users are web savvy and opinionated. But as I mentioned, be sure not to make your respondent range too narrow.

In yesterday's post we looked at how your survey question items, if worded improperly, may be biased, resulting in unusable or incorrect results. Now we know how survey questions shouldn't look, let's delve deeper into why those previous examples were poorly worded, and how with just a few small adjustments you can easily start to hone question items within your survey forms.

When you design internet surveys, how do you write objective questions that won't bias your results one way or the other?

Here are a few main points:


These first few points are a great starting place when you're designing a questionnaire. The final post in this series will look at a few final survey best practice tips for writing great survey questions and the benefits you'll gain from crafting quality items. In the meantime, questions previously stored in our question library already come properly worded and ready for use!

Vocus, a leading provider of on-demand public relations management software, released the results of a recent public relations and marketing survey they conducted. The survey sample was made up of 1,800 marketing and PR professionals. Among Vocus's key findings was the response of 80% respondents that social media would be a key focus for them in 2010. Vocus shared that they believe social media has been a catalyst for the change in the PR industry, where PR is becoming increasingly more important.

How is the PR industry dealing with the fact they're being asked to do more with less? Investing in technology. Sounds like a familiar story, right? Marketers turn to email survey tools to send out email survey invitations instead of having to manually send all email marketing messages through Outlook. Accounting departments use software to help them manage finances instead of the old way of paper, pencils and ledgers. Technology is often used to help professionals manage their work loads, and PR industry is doing the same thing.

Here are some of the other key findings Vocus shared from it's marketing survey:


You can learn more about the survey results by viewing the recording of webinar Vocus hosted yesterday, PR Planning Considerations for 2010.

Just because you find correlation in your data when analyzing survey results does not mean there is causation. I find this is a common mistake in lots of survey reports when someone is new to survey research or conducting data analysis. Take this example:


Some people see this connection as a causation. Customers are satisfied because you contact them frequently to make sure everything is going well. The problem is, it's not a causation. Causation are extremely hard to prove because you cannot control every factor. For example, you may split your territory by industry and your solution suits some industries better than others. Or clients who are really satisfied simply use the product more often so the customer success managers reach out to them more frequently, because they are more likely to have questions. While those who use the product less have less to be satisfied about and may feel they are wasting those budget dollars.

To be able to prove causation, you need to be able to rule out all other possible explanations for the connection. As you can imagine, that's almost impossible to do since we do not control outside factors influencing the survey respondent or even the greater survey sample. Instead, when situations like these occur, we're seeing a correlation between two things. In my customer survey question examples, there's a correlation between how satisfied customers and how often they are contacted.

This principle does not only apply to customer survey research, it also applies to analyzing employee feedback forms, product surveys, market research and any other type of data collection and analysis.