Find your respondents

After putting time and effort into creating a great survey, we find surveyors asking, “where do I find people to…

After putting time and effort into creating a great survey, we find surveyors asking, “where do I find people to take my survey?”

Today, there are multiple ways to reach your respondents, however, this doesn’t mean they’re all applicable to your survey. For example, your customer service feedback survey should be sent to customers that interact with your customer support. Therefore, the best way to reach them will most likely be sending a follow-up email after customer support has solved their query. That’s why you should start by identifying your target audience and then figuring out the best collection method(s) to reach them.

But don’t worry, we’re not leaving you alone on this one. Here are some collection methods we recommend:

If you have an existing list of contacts that have agreed to receive emails from you, e.g. newsletter list, then you can send your survey to them. Email as a collection method is often used for employee and customer surveys and it’s a great way to add existing background variables, such as department and industry, for a better report.
Social media
You can share your survey to Twitter, Facebook, LinkedIn, Google+, or any other social platform that your audience uses. As a bonus, Enalyzer allows you to add social media icons to your survey so your respondents can share your survey with their networks. To weed out respondents outside of your targeting audience, add screening questions to your survey. For example, if your survey seeks to find out attitudes about trust in politicians among voters, make sure that your respondents are 18 years old by adding a question: “How old are you?” If the respondent is 17 or younger, set up a condition so that the respondent is directed to an end page thanking them for their willingness to participate in your survey but unfortunately, they don’t fit the adequate target group.
Sometimes you have to go to where your respondents are, for example, if you’re conducting a survey about your hair salon and its facilities, it might be a good idea to ask people as they’re leaving. Set up a tablet in your store to make it easier for your respondents.
Panel companies can match your survey with online respondents for a fee. There are plenty of online survey panel companies out there, all you have to do is find one that specializes in what you’re looking for, describe your project to them and they’ll find a solution that fits your needs. If you’re interested in this, you’re welcome to contact one of our consultants and hear more. They can do the whole survey for you or you can create your own survey and they will match you with the right panel.

Collection methods are not mutually exclusive, which means you can, and should, combine the necessary methods that will help you reach your target audience. Whatever you decide, remember that it all starts with your target audience.

→ Create a free account and try it yourself!

4 things to consider when targeting respondents

Now that you have your survey and design all lined up, it’s time to invite respondents to your survey. This…

Now that you have your survey and design all lined up, it’s time to invite respondents to your survey. This may seem like the easiest step in research, how hard can gathering data be? Let me burst your bubble and tell you, this is one of the most important aspects of survey research and can determine the fate of the entire research endeavor. No pressure.

You need to make sure that you target the right respondents so that they accurately represent what you wish to look into. But, how do you ensure accurate targeting without introducing a source of bias to your research? Bias is the concurring evil of all research, so here are 4 things to consider:

1. The what and the who: research interest and population size

When determining who should answer your survey and how they get a hold of your survey, you first need to figure out what your research interest is. It doesn’t make sense to survey all students at the University of Oxford if you’re trying to figure out how satisfied students are with the dorms at the university. For this, you need to define your population, which is the entirety of your research subjects. For this example, the population is the number of students living in the University of Oxford’s dorms. However, it’s often impossible to survey an entire population due to time and cost issues. Luckily, most of the time, surveying the entire population isn’t necessary. Drawing inferences from samples often get you pretty close to the actual population, just be mindful of the inherent uncertainty they carry.

2. Random sampling

In order to achieve a result that comes as close to the truth as possible, you need to carefully sample your respondents. A sample frame is a list containing the entire population, from which a random sample is drawn. Continuing with the above example, this would be a list of all students living in the dorms, from which random names are selected to participate in the survey. You need to make sure that each student has the same chance of being selected so that you can minimize the sampling error (the natural deviation between sample and population). This is called probability sampling.

3. Sample size

We know you’ve been waiting for this one. The answer to the question; how many respondents do I need? Well… that depends on many factors but don’t worry we have a formula for you.

Let’s not get ahead of ourselves and take this one step at a time. You have to set the maximum error you’re willing to accept in your survey. When doing this, you should be aware of the following two parameters: margin of error and confidence level.

The margin of error is the interval within which you expect to find the value from the population you’re measuring. For instance, let’s say you wish to determine how large the proportion of the 10.000 students in the dorm are exchange students. If we assume that 1.000 are exchange students (10% of the population) with 5% margin of error, it really means it is about 500 (5%) and 1500 (15%).

The confidence level expresses how confident you feel about the value you look for within the margin of error. For example, in the previous case, if you choose a 95% confidence level, we could say the percentage of students in the dorm that are exchange students in 95% of the cases, is between 5% and 15%. In other words, if we repeat the survey 100 times, the proportion we’re looking for would be within the interval 95% of the cases and it would be out the interval in the remaining 5% of the cases.

The margin of error, confidence level, and sample size are always linked and co-dependent. Modifying any of these values will change the others:

  • Minimizing the margin of error will require a bigger sample size.
  • Increasing the confidence level will require a bigger sample size.

So, once you’ve decided on the margin of error and the confidence level you can use the formula to determine your sample size!

Pro tip: As a reference, the margin of error in political polls is usually 3%.

n: sample size to be calculated
N: size of the population (e.g. 1 000 students)
Z: refers to the confidence level and is derived from a statistical distribution

  • Confidence level 90% -> Z=1,645
  • Confidence level 95% -> Z=1,96
  • Confidence level 99% -> Z=2,575
e: maximum margin of error I tolerate (e.g. 5%)
p: proportion we expect to find. As a general rule, if we don’t have any information about the value we expect to find, we use p=50% .

4. Non-response and response bias

Once you’ve determined your ideal sample size, add a couple extra! Why, you ask? Because there will most likely be some who don’t want to answer your survey. To counter the effects of people not responding, you may want to increase your sample size by the expected non-response rate. So, why should you care?

This has got to do with two more biases related to your respondents that may influence your data. A response bias is mainly on the side of the respondent, who doesn’t understand the question or is lying while answering the question. You can counter this by making sure your questions are properly phrased and that respondents trust that their answers are anonymous and/or confidential.

Quiz Better

Quizzes are meant to test a person’s knowledge in a quick way and they can be formal or informal. The…

Quizzes are meant to test a person’s knowledge in a quick way and they can be formal or informal. The internet is full of entertainment quizzes that question people’s knowledge of pop culture or political awareness. Quizzes, however, can also be used in formal settings, e.g. pop quizzes in US schools. Quiz results are often graded and shared with the respondent a while after they’ve taken the quiz.

But what if your respondents could see the results when they reach the end of your quiz? This will transform your quiz into an interactive experience and can serve as an incentive for people to answer and reshare your quiz.


→ Check it out!

To say goodbye to 2016 and hello to 2017, we launched a New Year’s quiz where we tested people’s knowledge of some of the things that occurred in 2016.

As soon as respondents finished the quiz, they were redirected to a report showing the correct answers and how people had answered. This allowed respondents to test their own knowledge and measure it against others.

A quiz like this can be made more interactive by, for example, adding some demographic questions such as age. This will allow you to compare results based on respondents’ age and inciting a bit of competition.

→ Create a free account and try it yourself!

Fun fact

The word ‘quiz’ is only 250 years old, give or take, and it has had several meanings. In 1782  Fanny Burney used the word to refer to ‘an odd or eccentric person’. Also, around 1790, ‘quiz’ was the name for a toy. Today’s use of them term refers to ‘a test of knowledge’, this meaning emerged in the mid-19th century and the origin is hard to account for.

Making better estimates: how to deal with sample uncertainty

Every measurement is subject to some uncertainty but sometimes researchers tend to forget this. A common mistake researchers usually make…

Every measurement is subject to some uncertainty but sometimes researchers tend to forget this. A common mistake researchers usually make when interpreting results is ignoring the uncertainty of samples, which leads to decisions based on wrong data interpretations. To make sure we’re all on the same page, let’s start with the basics.

What are samples and what do we use them for?

Market researchers and analysts are usually interested in obtaining knowledge from a certain population, e.g. all employees in an organization. Getting data from the entire population would be ideal, however, this might be impossible to obtain for various reasons, the most common ones being time and money. Instead, researchers use a sample of that specific population. The common approach is to run statistics on the specific sample and use the results as “estimates” for the entire population.

Now that we got that covered, let’s move on to an example

Pure Digital is a marketing agency and they have a customer base of 10.000 customers. They want their customers to rate their satisfaction of the marketing services Pure Digital provides. To do so, they create a one question survey and send it to a subset of 300 customers on a yearly basis.

→ Check it out 

Based on the data collected from these 300 customers, Pure Digital calculates an average satisfaction score for each year:

Here’s where the common mistake happens. Researchers and analysts tend to look at the above and conclude that customer satisfaction is deteriorating. But is it? No, it’s not.

The problem

This conclusion is based on the assumption that 3.8 in the sample represents 3.8 in the total population (and in the previous years, the same is true for the average satisfaction of 4.2). This is not correct! If a different sample had been taken, the average satisfaction might have been the same or entirely different. In the above example, Pure Digital got, entirely by chance, some more or less dissatisfied customers into the sample that influenced the average rating. Thus, concluding that the satisfaction score, based on the sample, is a good indication of how satisfied the 300 customers are. What the market researcher didn’t do, is take into account the inherent uncertainty with regard to the satisfaction scores.

The consequences

If you don’t consider this uncertainty, you might end up overreacting or under-reacting. For example, let’s assume that all 10.000 customers are satisfied on average at 4.2 (while the sample tells us 3.8). What would the conclusion then be? Well, here, we mistakenly conclude that our company is not performing successfully when in fact we are doing well. However, if all customers have an average satisfaction level of 3.6 (and the sample still says 3.8) then we might think that we’re not doing as bad as we actually are.

In short, if we assume that a statistic such as an average from a sample is the same in the total population, we make mistakes. Mistakes that can potentially be costly and time-consuming.

The solution

In statistics, the average of a sample would be referred to as a point estimate. A point estimate by itself might be a good start but it doesn’t provide any information about how “good” this estimate is – it doesn’t take into account the uncertainty.

To get an idea of the error that we might have because we have a sample and not the total population, we can use confidence intervals, aka, range estimates. Contrary to point estimates, a range estimate provides a whole range of potential population estimates that are likely to be true.

The correct interpretation of data

For the example above, instead of assuming that the 3.8 average of the sample can be generalized to the total population, Pure Digital should compute the confidence interval and base their decision-making on a statement that says “we can be 95% confident that the true population average ranges between 3.8 and 4.2.

We started with a simple point estimate (satisfaction of all customers is 3.8) to a range estimate (it is quite likely – 95% – that satisfaction ranges between 3.8 and 4.2). The difference here is vital because it directly affects decisions. In this case, we could conclude that the difference between 4.2 and the quite likely 4.0 of this year is not big enough for Pure Digital to engage into redesigning the marketing services they offer.

In conclusion, by taking random samples and computing range estimates instead of point estimates, we acknowledge that our estimate of the population is to some degree uncertain and we are better equipped to avoid costly under- or overreactions.

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How did the polls get it wrong?

November 9th, 2016 will go down in history as the day the United States of America elected Mr. Donald J….

November 9th, 2016 will go down in history as the day the United States of America elected Mr. Donald J. Trump, which, needless to say, came as a surprise to many people, especially pollsters. During the past weeks, there has been quite a few finger pointing towards the polls. Many are wondering, how did the polls get this so wrong?

We decided to have a little chat with our Head of Research, Henrik Nielsen, so he could shed light on this matter.

This is not the first time polls have gotten it wrong, right?

Have you ever heard of the Shy Tory Factor? It refers to the British general elections of 1992 and 2015, when the Conservative Party, aka the Tories, significantly proved the polls wrong. In both elections, polls didn’t take into account conservative voters that hid their support for the Conservative Party.

Last year, Danish parliament election polls also got it wrong, none of them predicted the rise of The Danish People’s Party. Just this summer, we were all witnesses to Brexit even though all the polls predicted a win for remain.

Does this mean that we’re going to stop using polls to predict elections, among other things?

Many political experts, who got this election completely wrong, have already started to proclaim that this marks the end of polling and are calling polls a wild goose chase. We should take this with a grain of salt since they are trying to protect their own brand as political experts. In other words, no, this is not the end of polling. Polls attract readers, viewers, and clicks, which in turn brings in advertising money and as Liza Minelli says, money makes the world go around.

It’s not the end of polling but should it be?

Polls are not a wild goose chase, even though many are calling them that. Polls are useful and render excellent data; however, pollsters need to start re-examining the methods used in polling. Just like in 1992 Britain, before the 2016 US election, experts already started dismissing “shy trump” supporters. They based this dismissal on pre-election polls – ironic, right?

Back to your original question, pollsters need to increase their efforts and revise the way they do things and the rest of us need to remember that, even if the evidence says otherwise, polling carries uncertainty.

What should pollsters do in the future?

The French presidential election is coming up in the spring of 2017, so all of us, especially pollsters, need to look out for the “Shy Trump” phenomenon. As I said before, looking at polls is not a wild goose chase but, as in all aspects of life, polls have to be done according to the 7 P’s – Proper Preparation and Planning Prevents Piss Poor Performance.

The future of polling requires that pollsters find a way to handle the “Shy Trump” phenomenon. I will be following, and suggest everyone does, the polls on the French presidential election and see if the pollsters are able to figure out a way to handle the “Shy Trump” phenomenon or whether Marie Le Pen and the National Front will get a much better result than the polls predict…

The poll we conducted about the US election showed that 83.1% would’ve voted for Hillary Clinton, did we also get it wrong?

Ha! First things first, our poll is not representative, that being said it did show something interesting. It suggested that the majority of respondents would rather enjoy a beer in the company of Mr. Trump than Mrs. Clinton.

This question serves as a proxy for the winner of the election since it turned out to be a better forecast of the US election result than 99% of polls used the media coverage.


Are you saying Enalyzer saw it coming?

No, not at all but it’s still funny. Also, wouldn’t you rather admit to a beer than to a vote for the US presidency?

Did anyone see it coming?

Yes, there was, in fact, one poll that foresaw the victory of Mr. Donald Trump, however, this poll was written off as nonsense by the majority of the high esteemed panel of political experts, you know, those experts who got it all wrong.

6+ ways to enalyze

1. Improve customer relationships Whether it’s friends or customers, relationships are important and they need work and attention, but who…

1. Improve customer relationships
Whether it’s friends or customers, relationships are important and they need work and attention, but who said it has to be hard? That’s a rhetorical question since apparently everyone thinks it’s hard. Well, we don’t think so and that’s why our experts created the customer loyalty template. It’ll help you understand your customers’ experience with your organization and allow you to identify where you need to work harder and where you’re succeeding.

2. Ask customers why they left
Nobody likes rejection but it happens. We understand the urge to grab a glass of wine and sulk the day away after losing a customer. As appealing as that sounds, we have a more productive option; ask the customer why they left. Use their feedback to make improvements for your current and future customers. You can quickly get started with our customer exit template and when you’re done, reward yourself with a glass of wine.

3. Take care of employees
As employers, you want to make sure your employees are happy, motivated and engaged but let’s face it, people would rather share pictures of their recent trip to Bali with the world than their honest opinion with their bosses. So, what can you do? We already talked about this, but the gist is that we recommend anonymous surveys to gather honest employee feedback. You can use our employee engagement template, it’ll only take a few clicks!


4. Listen to work newbies
Starting a new job can be scary and daunting, maybe even slightly awkward. That’s why employers should do whatever they can to ensure new employees are properly and professionally welcomed to the organization. However, have you considered the fact that we all have blind spots and you could be overlooking something? Instead of wondering what it could be, you can ask the new employees! We recommend our employee entry templates that focus on the first 30 and the first 100 days of the new job.

5. Plan your next party
All work and no play makes for a boring life, isn’t that how the line goes? It’s important to blow off some steam once in a while. With that in mind, we refuse the idea that party planning should feel like work, which led us to create two templates for you; event planning and summer party. Combine them or use them individually, they’ll cover RSVP, dietary preferences, who brings what, and loads more.

6. Put hypotheses to the test
Surveys are a great way to test hypotheses about attitudes and behaviors in regards to anything; education, markets, politics, you name it! When used correctly, online surveys can be a powerful tool for academic research. You might not need them since research is topic specific, nevertheless, our experts did the reading for you and created several survey templates based on academic articles on branding, service quality, product design and more!

+ Don’t limit yourself
The Enalyzer research team has created more templates just for you and no matter the template you choose, you can use it as is or customize it to fit your needs. We also invite you to create your own survey from scratch and believe it or not, you can share your survey as a template to your friends!

Happy enalyzing!

Employee feedback, should it be anonymous?

Well, that’s a loaded question for a Monday. But sure, let me grab some coffee and let’s get right into…

Well, that’s a loaded question for a Monday. But sure, let me grab some coffee and let’s get right into it!

Ok, so before we start, we need to recognize that employee feedback is vital for personal and professional growth. Think about it, your employees spend a lot of time on the job, according to Happiness at Work it’s about 90,000 hours… that’s a lot of hours. Understanding how they are doing and making sure to provide an environment where they can thrive ensures they grow as people and they engage in company goals and objectives.

With that settled, it is now important for you to identify what systems and solutions to use in order to collect employee feedback. There are different methods, such as suggestion boxes, feedback coaches, and surveys. You want to look for a combination of methods that are understood and accepted by your employees since this will get you as much feedback as possible, but most importantly you need a system that ensures honest feedback.

Which brings us to your original question… should employee feedback be anonymous?

We live in an age of sharing, which means people are comfortable with sharing pictures of their pets, opinions on movies and selfies upon selfies. Some people might even call this oversharing but at Enalyzer we don’t judge – you do you! Nevertheless, for some reason which most of us can relate to, being open and honest with your boss still feels risky, which is why anonymity is important.

There are many that disagree and believe that fostering a culture of honesty and openness is the best way to go since you can ask employees to expand on answers, reach solutions together and award employees for constructive feedback. This is all true, but the most popular and effective tool to gather employee feedback is surveys, and realistically speaking, you will not get honest answers (or any at all) if you can’t guarantee anonymity.

Anonymous surveys can help you get started in creating a culture of honesty and they are a powerful tool when used properly. Employees will share their true thoughts and suggestions when they don’t fear retaliation, and by constantly acting upon the feedback you receive they will feel heard. Yes, it’s one of those win-win situations we all love.

Anonymity with Enalyzer

We are big advocates of anonymous employee surveys (if you couldn’t already tell), so we’ve designed a tool that ensures complete anonymity. As with many other tools, you can make your survey anonymous which means personal information on the respondents won’t be gathered or stored, but anonymous surveys are more than that.

Your respondents need to be confident that your survey will be conducted and processed in a manner that guarantees their absolute anonymity and this can be tricky with online surveys. Why is that? Well, sharing a report based on a survey with a low level of responses can compromise your respondents’ anonymity – but we took care of that.


With Enalyzer you can apply an anonymity level to your reports and charts, which will hide data until that level is reached. So, if you set your level to 5, all those your share your charts and reports with will not be able to see the responses until more than 5 respondents have answered the survey.


Wanna check it out? Create a free account!

It’s all about first impressions: the importance of survey design

It takes people 1/10th of a second to form an opinion about a person, and surveys are no different. Always…

It takes people 1/10th of a second to form an opinion about a person, and surveys are no different. Always keep in mind that surveys speak in two languages; words and visuals. So, your survey’s first impression relies on these two complementing each other.

Images, colors, and fonts

We are sure you already know this, but we’ll say it again – colors, fonts, and images are important! Plenty of studies (shout out to Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method by Don Dillman, Jolene Smyth, and Leah Melani) show that these incite feelings and attitudes on people, which means you shouldn’t overlook the impact these can have on your respondents.


You can find endless research on colors, fonts, and images and we encourage you to do so, however, today we’re taking it a step further. We want to focus on matching your survey’s visuals to its content.

Avoid bias by conveying the same message through visuals and words

Make sure your visuals and text are saying the same thing. If you have chosen a casual and informal tone in order to target a certain segment of respondents but your visuals are strict and rigid, you’re creating cognitive dissonance and influencing your respondents’ performance.

For example, if you conduct a survey on attitudes towards different social media platforms and you use Facebook’s color scheme, you will end up with invalid data


Your survey is part of your brand

Every and any interaction that customers have with your brand is defined as a touch point, and it can have a positive or negative effect. Your survey is a touch point, it’s part of your brand, that’s why your survey design should align with your brand identity and be consistent.

We live in an online world, which means customers experience brands throughout a variety of channels and it’s important to keep their experience consistent. So, if your website and social media are branded then your survey should reflect your company’s brand presence as well.

Engage your audience through visuals

You have chosen a specific tone and words to address a specific audience, however, have you chosen the right visuals? For example, let’s say you’re conducting a survey about homeschooling and include images of classrooms, however, your target audience is homeschooled children, then these images are not going to resonate with them, they might even hit the wrong note. Make sure your visuals align with your content and brand, as well as speak directly to your target audience.


Ultimately, you can jeopardize your data by overlooking your survey’s visual design. Remember, it is the first thing your respondents will notice and you don’t want to lose them before they even read the content of your survey. Visual design done well can increase response rates and minimize bias, however, when done poorly it can have the opposite effect.

Enalyzer provides multiple survey design templates, which can serve as a great starting point for your survey design – the possibilities are endless.

Pareto principle in survey analysis and reports

  The Pareto Principle, aka the 80/20 rule, is named after Italian economist Vilfredo Pareto (the dude in the picture)…


The Pareto Principle, aka the 80/20 rule, is named after Italian economist Vilfredo Pareto (the dude in the picture) who in 1906 found that 80% of the land in Italy was owned by 20% of its people. Ok, but why is it called a principle? Well, he carried out surveys in other countries and found that the 80/20 distribution occurs frequently. Nowadays in business, this principle is a common rule of thumb, for example, in general, 20% of customers represent 80% of sales, 20% of time spent produces 80% of results… you get the gist.


If you apply the Pareto principle to a bar chart, the result will be values plotted in decreasing order of occurrence, organized from left to right. As a result, the chart clearly illustrates which factors have the greatest impact and what problems need the most attention, making them extremely useful in a variety of situations.

When to use the Pareto principle in a chart?

  • When analyzing survey frequency data.
  • When there are many items, and you want to focus on the most significant one.
  • When analyzing broad issues by looking at their specific components.
  • When sharing your survey data with others.

The Pareto principle is without a doubt a necessary tool for you to know better. That’s why we’ve made it very simple for you to create your own. Want to learn how? Click here.

What is being enalyzed?

We have taken the temperature of our enalyzers to see what kind of templates are being used the most and…

We have taken the temperature of our enalyzers to see what kind of templates are being used the most and the results are in!

The top three most used expert templates are:

  1. Customer satisfaction
  2. Course evaluation
  3. Social capital

This shows just how diverse our enalyzers’ survey needs are. Whether it’s to figure out how customers perceive you, if your course met participants’ expectations, or the level of social capital within your organization, Enalyzer’s templates can assist you in figuring out what you, or your organization, is good at and, most importantly, point out what can be improved.

You can check out our different template options and get an idea of how they can help you get the intel you need. All templates are made by the Enalyzer team and are fully customizable so you can use them as inspiration and tailor them to fit your specific needs.

3 tips to avoid survey fatigue

When collecting data from an audience, you need to be respectful of their time and you want to make sure…

When collecting data from an audience, you need to be respectful of their time and you want to make sure your survey keeps the respondents engaged from “hello” to “thank you”. A key aspect of keeping your respondents engaged is avoiding survey fatigue.

Survey fatigue can be divided into two different types, both of which can have a profound effect on your survey’s response rate, as well as the quality of the data collected.

The first type of survey fatigue starts before your survey even begins and stems from the increased amount of surveys currently being circulated. People are constantly being asked for feedback, whether it be by the local grocery store or their workplace, and are simply tired of answering surveys. This type of survey fatigue is the hardest to battle as this is not really dependent on your specific survey, but an overload of surveys in general.

The second type of survey fatigue is related to the fatigue your respondents may feel when actually taking a survey. This type of fatigue happens if your survey is too long, complicated, or confusing and may lead to the respondents rushing through or exiting the survey prematurely- leaving you with a lack of quality data. 

Though the above might sound bleak, don’t fret! We have comprised a set of tips for how you can avoid your respondents getting survey fatigue.

Don’t drown your audience in surveys
Don’t send more surveys than absolutely needed. This way the chances are higher that your target audience will respond to the survey, as opposed to if they have already received four surveys from you this month. If your organization is dependent on sending out a lot of surveys, try to keep track of when different departments are sending out surveys, so the same people are not answering surveys from multiple departments at the same time.

Communicate the survey’s value clearly
If the respondents know how their responses will be used and what the aim of the survey is, they are more inclined to stick through the survey. So make sure to communicate this clearly. When designing your survey reflect on and efficiently communicate the following to your respondents:

  • Why should they take your survey?
  • What will the answers be used for?
  • How time-consuming is the survey?

Always think of your respondents
Though the survey might ultimately be beneficial for the respondents themselves, through for example improved work or customer experience, while taking the survey they are doing you a ‘favor’ by sacrificing their time. This is not something that should be taken lightly, so make sure that their time isn’t wasted which can be done by:

  • Using behavior and conditions to make your survey as ‘respondent-friendly’ as possible. This way you won’t confuse your respondents with irrelevant questions.
  • Asking the right questions and not asking too many of them. Keep it simple and only ask the questions you absolutely need to. Short and sweet is the way to go. Put your survey to a ‘nice to know vs. need to know’ test. If questions in your survey are ‘nice to know’ rather than ‘need to know’, drop them. This will give you better quality data and a higher response rate ensuring that you get the information that you ‘need to know’.
  • Get creative. A good looking survey is inherently more pleasant to answer so put some effort into your survey design. If you need inspiration check out our blog post on flawless survey designs.

Meet the team: Enalyzer Support

We are lucky to have a diverse, international, and highly professional support team, that is always ready to go out…

We are lucky to have a diverse, international, and highly professional support team, that is always ready to go out of their way to help our customers and it shows. They react quickly to problems, making sure that 75% of tickets submitted to our Help Center are answered within an hour or less, and it keeps getting better.

Plus, the Enalyzer Support rating has never been short of impressive. Check it our for yourselves.

Enalyzer support satisfaction score

That’s why today, we’re happy to shed the spotlight on some of our key supporters, so you can learn a little bit about the people at the other end of the line, and what kind of work they do.

So, what is a typical day at Enalyzer Support?

“It’s normally busy, not only do we answer our customer’s calls and emails, but we also constantly work together with all the other departments to ensure that every customer contacting Enalyzer gets the correct information and gets in contact with the right Enalyzer, for example, our consultants.”
– Mille, Norway

What do you like about working in support?

“I like to teach our customers more about Enalyzer and tips on how to enalyze better, or as we say become an Enalyzer Pro. It is such a good feeling when you can maneuver and figure the tool out by yourself, and I always aim at giving our customers this opportunity, by teaching them. I want them to get a better understanding of the tool, not just get a quick, but satisfying answer to their query. I want to also enhance their overall understanding when they contact us so that next time they might understand the tool better and figure out things by themselves.”
-Marita, Norway

“Hearing a customer’s relief and happiness after talking to us, especially if they have spent a lot of time and effort trying to solve the problem themselves is my favorite part of my job. It never gets old.”
– Mille, Norway

What kind of queries do you usually get in support?

“We are focusing our support towards helping the customers get a full understanding of our tool. This means that we can answer general questions about Enalyzer and what the tool can do for the customers, but also guide them in specific questions or problems that they have encountered within Enalyzer. Apart from that, we can help the customers with questions regarding their accounts.”
-Fredrik, Sweden

“More concretely, I find that the functions customer most often ask about are related to downloading their raw data file in order to see the data of each individual respondent, as well as tips on report filters to get the best out of their insights”
– Ibi, Denmark

What is your favorite story about an interaction with a customer?

“I can’t think of a favorite story, but there has been plenty of occasions where you can save the customer a lot of time by giving them small tips and tricks. That is always associated with a lot of excitement.
For example, best practice tips in relation to conditions and jumps in the survey, avoiding unnecessary questions to ensure a higher response rate, and the variety of possibilities in reporting by using filters and data series.”
– Marita, Norway

“I had a customer who was launching a survey globally. We started a good chat and she talked about the workload she had because of this massive survey. However, everything ended up with a big laugh and a happy customer after I showed her how easy it was to translate the survey. She had initially thought that she had to create a survey per language that she was launching (which were many, many languages), but was quite happy when she realized that she only had to create one and translate it!”
– Fredrik, Sweden

What advice would you give to new supporters?

“I think that the best advice to give to a new supporter would be that it gets easy after a while. Since we talk directly to our customers it can sometimes get nerve-racking and it’s a lot of information, in the beginning, however after a while, you do a lot of it on autopilot.”
– Mille, Norway

And finally, as a new addition to the team, can you share some of your experiences?

“Being new in support is both challenging and rewarding. We talked to many different customers every day, each of them having individual and specific questions. This can sometimes get overwhelming as we supporters need to efficiently handle and adapt to each customer request in a really short period of time. However, the gratitude and appreciation that customers have after getting guidance from us, makes the whole process really gratifying.”
– Cristina, Spain

Aren’t they great? We think so, but we know we’re biased, that’s why we’ve compiled some testimonials from our customers. So if you won’t take our word for it, keep reading.

Mathilde Thomsen returned our call and we got the best help. High praise for Mathilde, who was quickly able to understand our challenges.
– Mia Nørby, Region Nordjylland

I think your support is great! I always get fast answers and my problems solved.
– Malgorzata Ligowska-Marzeta, Danish Health Authority

Fast and extremely friendly support, this is really good!
– Ketil Heyerdahl, Norsk Journalistlag

I have only called Enalyzer Support a couple of times and I have always received quick and prompt help and answers to my questions. Super nice – good customer service
– Malou Jessen, KMD

Our support team handles queries from all around the world and are equipped to assist you with any questions you may have about Enalyzer or overall survey and report queries.

You can get in touch with them at

Are you focusing on customer satisfaction? You should.

Advertising is based on one thing, happiness. And you know what happiness is? Happiness is the smell of a new…

Advertising is based on one thing, happiness. And you know what happiness is? Happiness is the smell of a new car. It’s freedom from fear. It’s a billboard on the side of the road that screams reassurance that whatever you are doing is okay. You are okay.
– Don Draper, Mad Men.

We have been saying it for years, but Don Draper had a better quote, it’s all about making the customer happy. According to Salesforce’s 2016 State of Marketing report, “marketing has entered the age of the customer.” Customer satisfaction has been a top metric of marketing success for two years in a row, and this year it has reached the very top, becoming the most important metric according to 35% of the surveyed marketers, and surpassing revenue growth (33%) and customer acquisition (24%). Yeah, let that sink in.

The report found that marketers are now going for the holistic approach to customer experience. High performing marketing teams are implementing customer experience initiatives across their businesses (58%), compared to 8% of underperformers. This requires building bridges and collaborating across business units (marketing, sales, IT, leadership, and service), which high performers are 17.1 times better at doing than underperformers.

In line with the holistic view of customer experience, the report shows that 65% of high performing marketing teams have adopted a customer journey strategy, and 88% of them found it to be critical to their success. This is due to customers having more information, choices, and power than ever before, as Salesforce puts it, causing them to expect quality customer experience across every touch point.

With Enalyzer, you can create a free account today and be on your way towards understanding your customers’ complete experience by using our customer satisfaction survey template – use it as inspiration or create one of your own. Or if you want to take it to the next level, try our PRO plan and get access to our NPS® survey template. Plus, with our real-time reporting possibilities, you can watch as your customers’ answers start ticking in!

We are glad to hear that marketers are prioritizing customer experience more and more every year, since we have always believed that understanding your customers’ experiences is crucial to your success. Whether this is through your own surveys, on-going feedback recollection or Net Promoter Score®, make sure you start getting familiar with your customers and their experience.

7 golden rules for survey question writing

What is a good question? A good question, is a question that asks the right thing in the right way….

What is a good question? A good question, is a question that asks the right thing in the right way.

Last week we talked about asking the right things by transforming your objectives into survey questions. Today, we will look at how to ask the questions the right way, to ensure higher response rates and better data.

For this purpose, we have comprised a list of 7 golden rules for survey question writing:

  • Clear questions are the best questions
    If your question is not clear, your answer won’t be either. So keep it simple, to make sure that your respondents understand what you’re asking.
    A question should only include a single idea, including several questions will confuse respondents and it will be impossible for you to interpret their answers.  Let’s try this in practice:

    If a respondent answers “satisfied” to this question, how will you know what it means? Is the respondent satisfied with the teacher or the catering? Or maybe the respondent was “very satisfied” with the teacher and “unsatisfied” with the catering? See, it’s confusing!
    A simple mistake as this, creates invalid feedback on the teacher and catering during the course, making it impossible to come up with solutions. These types of double-barreled questions can often be spotted by the use of the word ‘and’, signaling the connection of two different focuses: “… the course teacher AND the catering”.  In other words, by applying the one-idea-per-question rule, you won’t confuse your respondents and collect sound data.

  • Avoid hypothetical questions
    When you ask hypothetical questions, it often results in unreliable data caused by respondents not being able to understand your hypothetical scenario. The question “Imagine that you’re buying a new car, what kind of financing will you prefer?” is virtually impossible for someone that has never considered buying a car, or doesn’t have the knowledge of the different financing options, to answer. Instead, it would be better to ask someone who has recently bought a car how they financed the purchase.
  • It’s all about the context
    In some cases, questions and their answers will only give insights if understood in a certain context established by other questions. For example, if asking about a respondent’s attitude towards Buddhism, can you adequately interpret this without finding out about their attitudes towards religion in general, or other religious groups? In such a case, contextual questions are your friend since they ensure that you’re getting the full picture and the valid information you need.
  • Your response options have to be all-inclusive
    Make sure that your response options allow respondents to answer your question. Let’s look at an example:


    Here, a respondent who has worked at Enalyzer for over a year but less than 2, can’t adequately answer the question. This will inherently have an effect on your data’s validity, plus he/she is now feeling left out and no one wants that. In this case, you need to make sure that your response options fit all possible answers. For the above example, one could add an extra response option, ‘1-2 years’ or extend one of the other options to include this time span.
  • Find the balance between being too specific and too broad
    When writing survey questions, you need to keep your survey’s goals and objectives in mind at all times in order to make sure that your questions allow for the answers you need. So, it might be necessary to reflect on the correlation between being more specific or sufficiently general and the possible answers you can get.
    General questions can sometimes lead to information that is difficult to interpret. For example, let’s say that you’re a business owner that is interested in knowing what customers think about your service. To find this out you could ask “how well do you like my services?” rated on a scale ranging from “not at all” to “extremely well”, but what would a possible response to this mean? What exactly does it mean that someone likes your services? Instead, you could ask more specific questions such as “would you recommend my services to others?” or “would you use my services again?”.
    In other instances, you may need to evaluate whether your question is sufficiently general in order to make sure that the answers you are getting accurately reflects the respondent’s attitude towards the topic of choice. For example, if you ask someone how they have thrived at their workplace for the last week, you could get a very different answer than if you asked them how they have thrived there the past year. Perhaps, the respondent had a bad week, but this doesn’t necessarily reflect their sentiments at their workplace in general.
  • Keep them relevant
    When making a survey always keep in mind that you’re ‘borrowing’ time from your respondents that they could have otherwise used on something else. Therefore, it is important not to waste this time by asking irrelevant questions. Avoid this by going through all of your questions before sending your survey, making sure that you actually need to ask the question and whether you need to ask it at the level of detail you currently have. For example, if you’re asking a question about your respondents income, do you need to know the exact number, or would your reporting needs be satisfied by income ranges?
  • Make them neutral
    Survey questions and response options should be neutrally formulated so that you don’t lead respondents to a particular response. Also, respondents should be able to answer questions both positively and negatively. Here is an example:

    In this example, the response poles, disagree and strongly agree, are not balanced and there are more positively loaded options than negative ones. This should be avoided as it can sway the respondents’ replies and no one likes a manipulator!

Meet the new Enalyzer brand

What is Enalyzer? A noun. So, what is Enalyzing? It’s a verb that describes the process of knowing better by connecting,…

What is Enalyzer? A noun. So, what is Enalyzing? It’s a verb that describes the process of knowing better by connecting, collecting, analyzing, reporting and conveying information through a simple and intuitive application that makes advanced reporting feel like play and look like business.


The new Enalyzer brand is made up of various elements coming together to tell the story of Enalyzing.


The essence of Enalyzing is depicted by our new logo. The logo takes on the form of the Greek letter sigma, which in our profession is used as a symbol for calculations and statistics.
A dot, representing focus, is a clear reference to the idea of connecting processes. The dot is the connecting point which creates a visually interesting combination of lines emphasizing the visual reference to connections and connecting.


It’s flexibility as an icon enables it to morph into numerous other symbols that, in different contexts, can symbolize almost everything but still be recognized as an Enalyzer graphic.

The font and colors

Just as our logo, we needed fonts and colors that depicted our new brand. Stemming from our Nordic roots, we were inspired by our weather and the Aurora Borealis. There is nothing like a Danish summer, however most of the time we are met with a grey and cloudy sky, and it might not sound appealing but we found the beauty in the cold neutral tones. We combined that with the captivating and enticing colors of the Aurora Borealis, and we got a stylish, yet neutral color palette.


Now that we had the colors, we needed the font to match. We chose Gotham, not only for its visual appeal but also for its personality, which goes hand in hand with our own. Gotham is described as having an inherited honest tone that’s assertive but never imposing, friendly but never folksy, confident but never aloof.


Our new brand represents who we are and lays the foundation for the road ahead. We’re glad to have you on board.