Customer Satisfaction Research

As I've mentioned plenty of times before, a critical step in the survey research process is taking the time to analyze data (check out these tips on how to analyze survey data) and presenting your survey findings. If you're like most people, the thought of having to create a survey report makes you cringe - perhaps even hide out under your desk until you think everyone has forgotten about the survey research project. Shame on you if you're under your desk! Why did you even bother spending all that time on the market research or employee questionnaire or customer satisfaction marketing survey in the first place if you didn't want to share the findings?

I do understand, despite my sarcasm. Creating a survey report can be daunting. After all, where do you even start? In past posts, I've mentioned how great Cvent presentations and reports are for post data collection survey analysis and report creation. It's awesome that our online survey software can do a lot of the heavy lifting with the graphical representation of your survey, but you still need to structure the report and provide recommendations.

After you finish analyzing survey results, here's a quick guide to what should be included in your survey report:


Even with these survey tips for creating survey reports, you may still not have the extra time to allocate to building reports and presentations. If this is your situation, let our Survey Professional Services Group help. Our talented team created countless custom, professional reports for our clients to share with their management teams and decision makers. Contact us to learn more about our Professional Services.

Yesterday I was out to dinner with a friend, and we started talking about retail surveys. She was expressing her frustration with the survey questionnaire design for her company's retail surveys. Apparently, they always score low on this one question:

Most people don't come into her store looking for pants, so the sales associates don't harass customers asking if they need the fits explained. Makes sense. Then why is their online survey asking for customer feedback from all consumers regardless of their primary purpose in visiting the store?

Oh, wait! There's the problem. The survey writer neglected to ask survey respondents why they came to the store. Because of this omission, the survey question in question (Were pant fits explained?) isn't presenting very valuable survey data. The clear solution would be to add a new question and use some form of survey question logic (perhaps branch logic might be ideal here) to only ask those people who were shopping for pants if the pant fits were explained to them. Ideally, when you're testing your survey, you should think through the question flow and catch situations like these.

Another minor point about this question, what about those customers who were asked if they'd like the pant fits explained and declined? How are they going to answer this question to give you accurate data? Even if you would answer "Yes" because it was offered, not all online survey respondents will. This would be a more useful question, after being paired with a screener question, if it asked if a sales associated offered to explain the pant fits.

This same concept applies to hotel surveys, customer satisfaction research, website surveys, etc. The reason why a guest stays at a hotel (business or leisure travel) matters. What someone was looking for when they visited your website (trying to purchase X vs. looking for information about Y), makes a difference. If they are looking for information about Y it does not make sense to ask them if they found information on Z.

It's pretty frustrating when it comes time begin your survey results analysis using either the survey reports built into your online survey software, excel or another survey analysis tool and you find your survey has a high partial response rate. You spent a lot of time writing survey questions then building the survey in your survey tool. You thought about your survey methodology (including your survey analysis methods) and determined sample sizes using a sample size calculator, because you wanted to ensure you had a representative sample. However, survey best practices tell you that you should not use partial responses in your survey analysis. It seems unfair after all your time working on the survey project that you should have to throw out partial responses and fall short of your estimated sample size.

This is one of the reasons you need to test your survey to a small segment of your email list prior to fully launching your survey. A small test would allow you to catch this problem early. I typically see survey abandonment stem from an online questionnaire being too long, the topic of the questions are too personal or the respondent knows little about the topic.

You know how frustrating it is for you to see a high abandonment rate? It's equally frustrating to an online survey respondent to begin to completing a customer survey, website market research or web usability survey and find out it's long. Particularly because most survey invitations promise a short survey.

Solution? Ask survey respondents the most important questions on the first page (keep it to just a few, I would try to stay under five. Think about a comment card at a restaurant, would your questions fit on a comment card?) Then ask if they have time to give additional feedback. I've seen this method used on a number of customer satisfaction marketing surveys, but the same customer satisfaction survey methodology could be applied to employee questionnaires, product feedback forms and website surveys as well. Each question in your survey should have a purpose and contribute towards meeting your survey project's goal, but some may rank higher on your "need to know" scale. Offering respondents an out will not eliminate survey abandonment but it should reduce it without forcing you to throw out that respondent.

Do you know how satisfied customers are? Do you know commonalities satisfied customers share? What about dissatisfied customers? If not, you're missing out on valuable information that could help identify how your organization can boost revenue. All you need is to conduct some customer satisfaction research. If it could help boost revenue why wouldn't you be interested in measuring customer satisfaction?

One way to begin to classify customers in customer satisfaction survey research is to ask a series of Net Promoter survey questions about overall satisfaction, likelihood to repurchase and likelihood to recommend. As I've mentioned in past posts, many online survey tips recommend placing overall satisfaction questions before more specific questions. This applies here as well. Asking about repurchase likelihood and chances of making recommendations should be placed where ever they fit best within your questionnaire.

Here's the important part: the survey analysis. After getting back your questionnaire responses and you begin the survey results analysis and calculate customer satisfaction scores, look at how you can divide up customers. Typically, customer survey best practices say there are four distinct customer satisfaction categories:


This should just be one step in your survey research analysis process. From here, one of the things you should look for is commonalities between each group. Does everyone in the dissatisfied column have something in common you can fix? Does everyone in the secure group do something the bottom two groups do not, maybe you could better share these benefits or features.

There are always a lot of questions about customer satisfaction survey methodology. Like with all survey research projects, the first step is to clearly define the goals of your customer satisfaction marketing survey. One of the goals when measuring customer satisfaction should be to increase customer satisfaction in ways that will maximize the value of long term customer relationships. I often see people developing customer satisfaction surveys that fail to collect data to help organizations do this. Instead, their satisfaction questionnaires simply categorize clients into a satisfied or dissatisfied pile based on the response to one overall satisfaction question.

In the past, I've heard people compare measuring customer satisfaction to measuring an individual's level of intelligence. I think it's a good example for understanding why one overall satisfaction is not a reliable means of gauging satisfaction among customers. If you are asked to take a test intended to gauge how smart you are and you open the test booklet to find a single question:

Chances are, you wouldn't think it was a good gauge of your intelligence - in fact, it wouldn't even tell the researcher how observant you are as a person. That's because how intelligent someone is cannot be reduced to a single question, intelligence is multidimensional. The same is true for measuring customer satisfaction, you cannot get a true understanding of how satisfied a client is or isn't by asking a single question.

What does this mean to you when starting your next questionnaire builder? If you select a quantitative research method, like surveying, be sure to include a series of questions aimed at gaining an understanding of customer satisfaction levels. Keep in mind your goals and how you could increase satisfaction in ways that will transfer into actionable items for the organization. When analyzing the survey data, don't just lump customers into satisfied and dissatisfied categories. You should be assigning degrees of satisfaction based on the responses.

Conducting customer satisfaction research or customer opinion surveys in countries who do not speak English? It's a no brainer to make sure you're translating your survey to the native language. Our online survey technology make's it easy to build online surveys in either English, French or Spanish. However, we don't pretend to be an online translator. I strongly recommend looking into a translating service if you're not fluent.
Customer survey best practices for translating surveys is to translate into the language you want to build your survey and then translate back to your native language. Seems like a lot more work, but it helps ensure the translation is done correctly. When you're using your survey results to help create marketing strategies for international products, making sure you're getting the right data back is essential. This translation best practice doesn't only apply to customer surveys, but any type of marketing piece from printed advertisements to power point presentations to other types of market research.

Sometimes, all the tips for creating and designing survey invitations are just not enough of a push in the right direction to get you started sending email survey invitations. I like to be able to look at examples when starting a new type of project - particularly when business decisions hang on your survey results.

Last week, I was invited to take customer satisfaction marketing survey on my credit card experiences. The email survey invitation so closely follows these tips for sending survey invitations, I wanted to share the example:


This survey invitation email get's to the point quickly, introducing the electronic online survey, telling me how long I should expect to spend on the questionnaire and offering an incentive that is unlikely to cause people to skew the results just to get the market research survey report.