For most SaaS businesses, a product satisfaction survey can be the heart of a user research process.
But what type of surveys are best for your goals? And how should you ask your questions to ensure that you’re collecting the right data?
In this article, we’ll go over different survey types and examples, as well as provide some ready-to-use templates you can use right away with Userpilot.
Let’s start by defining what a product satisfaction survey is.
A product satisfaction survey, as the name suggests, is a type of survey that measures your customer’s overall satisfaction with a product or service.
It’s an essential part of any customer feedback program, as it allows your product team to engage in active communication with your user base, make the right improvements to your app, and finally close the feedback loop.
Now, the best type of survey will always depend on your goals and the type of data you’re looking for.
So let’s go over five different satisfaction survey types.
NPS surveys ask users to rate their likelihood of recommending your product to a friend on a scale of 0-10. Where users who scored 9-10 are considered “promoters,” and users who selected 0-6 are considered “detractors.”
By measuring your Net Promoter Score (NPS), you can find out how a specific interaction affects customer loyalty or keep track of loyalty levels over time.
The Customer Satisfaction score (CSAT) measures the customer’s experience with a specific product, feature, or team interaction.
Conversely, CSAT surveys tend to trigger after a specific touchpoint or milestone, such as finishing the primary onboarding or contacting a customer service representative. This way, you watch over the satisfaction levels across the customer journey and spot stages where users are experiencing friction.
Customer Effort Score (CES) measures the perceived effort of an interaction.
As such, CES surveys ask users to rate from 1 to 5 how easy it is to use your product. And they allow you to identify friction points inside your product that you wouldn’t be able to notice otherwise.
For example, triggering a CES survey after account renewals can help you spot friction in your payment process and avoid involuntary churn.
Product evaluation surveys are oriented to gauge how users feel about product performance at multiple touchpoints. It allows you to measure what aspects of your app are most valued so you can understand what you’re doing right and what you should improve.
For example, if you notice that most users value ease of use over your features, perhaps you should focus on adding new functionalities that are intuitive and serve to streamline your user’s workflow.
PMF surveys ask customers how disappointed they would be if they could no longer use your product. And if at least 40% of your respondents say they will be very disappointed, then you have achieved product-market fit.
You can also use PMF surveys for specific features and, for example, see if you need to sunset a feature.
Choosing a type of survey isn’t all, you also need to write a question that:
So let’s go over eight types of survey questions and get some examples:
The rating-scale survey questions are mapped in a numeric scale that ranges from 1 to 5 or from 1 to 10. In this type of survey, respondents need to rate their level of agreement or satisfaction with a statement with a number, making it good for more quantitative analysis (especially NPS surveys or alternatives).
Here are three examples of rating-scale questions:
Likert-scale questions are a subset of ordinal questions, and they’re mostly used to measure opinions or feelings about a statement or your product.
It typically includes five answers ranging from the most negative to the most positive (with a neutral option in the middle), for example:
They can be used on many surveys, either for general research or targeted CSAT surveys. Here are some questions to go very well with it:
Multiple-choice questions, as the name suggests, present respondents with three or more predetermined answers that can’t be quantified. In SaaS, they’re commonly used to gather product feedback or to research respondents’ behaviors, demographics, or persona types.
Here are some good questions that fit this model:
An ordinal scale question asks users to rate their experience and sentiments on a scale of five, seven, or ten items that have no quantifiable distance from one another.
As the name suggests, the answers are placed in a specific order (worst to best). But unlike the rating scale, a rate of four stars isn’t twice as valuable as two stars (that’s why the Likert scale is also ordinal).
As a way to measure user sentiment, SaaS can use this scale to measure CES and find opportunities to improve the user experience. Here are five common questions you can use:
Open-ended survey questions allow users to describe something in their own words without any limitations, making them great for collecting qualitative feedback.
In SaaS, open-ended questions help you understand the reasons behind certain behaviors from users. Or even receive very useful feedback about your onboarding process you wouldn’t be able to get otherwise.
Here are five great examples of open-ended survey questions for user experience:
In SaaS, it is very useful to pair quantitative questions with open-ended questions (a.k.a follow-up questions). The goal of follow-up questions is to gather both quantitative and qualitative feedback to get data that you can act on.
NPS follow-up questions are a common example, as they help you understand the reasons behind certain responses from survey takers. However, they’re also used in CSAT and CES surveys, as well as any other score-based questions.
Here are four good follow-up question examples:
Product usage questions are specifically oriented toward how the user engages with your app.
It’s very helpful to SaaS businesses, as it can give you insights that can help you improve customer retention.
The survey format of your product questions can vary drastically, so you can use any of the following five questions as it fits your needs:
As we explored earlier, PMF surveys ask users this very specific question: “How would you feel if you could no longer use our product/feature?”
The format of this survey is a Likert scale reduced to only three options, making it an easier experience for respondents and giving you more clarity over the data.
However, there are more question types you can use to measure product-market fit. And they include:
With the basics covered, all you need now is a good tool that can allow you to build and use survey templates.
Here, we’ll go to Userpilot’s user sentiment tool to build some useful survey templates for product satisfaction.
The onboarding process can make or break a customer’s first impression of your product.
That’s why you need to take the opportunity to ask about their onboarding experience and how satisfied they feel with it. So with the customer satisfaction survey template below, you can gather data that can help you understand how efficient your onboarding is using an ordinal-scale response.
The following template is a CES survey that uses the Likert scale to add both negative and positive responses. This way, users can explicitly express if they didn’t like their experience.
With this template, you’ll get more accurate responses if you trigger this survey when the user has used your product and their experience is still fresh. Plus, it’s a smart idea to pair it with a follow-up question, so users who rated negatively can explain their reasons.
This CSAT survey template targets users’ expectations. And since user expectations can be very unclear, this survey allows respondents to give them a number.
For more accuracy, send this question to users when their first impressions and sentiments are still clear. Maybe after they reached activation, or after their first month with you, etc.
This NPS survey template is great for measuring customer loyalty with a rating-scale question.
A big part of your customer’s value is their likelihood to expand word-of-mouth, so this survey template is great to quantify it and keep track of it. Plus, there’s no need to send it at specific times. Just make sure to trigger it to users who have enough experience with your product.
This template follows the regular format of a PMF survey, asking users about how they’d feel if they could no longer use a product or feature.
Here, the multiple-choice format makes it more specific and gives less distance between the responses. So neutral users can express they’d be “somewhat disappointed” if they aren’t too active but still have some positive regard toward the product.
At last, the template below includes an open-ended question where users can freely describe their experience with your product.
This customer experience survey can be used for general UX research, and it gives room to users to surprise you with insights you’d never expected.
Having known the different types of surveys, questions, and templates available, how should you use them to make sure you’re getting valuable data?
Here are four best practices for creating customer satisfaction surveys.
The reason why you’re interested in satisfaction surveys is probably too vague. “Understand my users” or “Build a better product” are not goals.
Be more specific. The more details you have in mind, the easier it is to know what type of survey and data you should get.
Try following a goal-setting framework such as SMART goals. SMART stands for specific, measurable, achievable, relevant, and time-bound, which can easily direct your surveying tactics.
For example, if your goal is to “Increase the usage of X feature by 40% by the end of Q3”. You can decide to trigger CES surveys to recent users and include a follow-up question where they can indicate what makes X feature hard to use.
Deciding the right type of survey for your goal is great, but you also need to make sure that your survey questions are:
So think about the type of data you need in order to progress, and write survey questions specifically for that. It will make data more actionable and credible than any general template.
On the other hand, there are things you can’t know until a user points them out with detailed responses.
That’s what open-ended questions are for. Sometimes, it’s not enough to know how many users find your product hard to use if they don’t tell you why.
This way, you can get surprised and identify problems (or opportunities) that you’d have never guessed on your own.
When to send a survey is almost as important as what survey to send.
It doesn’t matter how carefully you target your surveys. If you send surveys over email at midnight on Saturday, there’s no way you’ll get a response.
The better method (for product satisfaction surveys, specifically) is to set in-app surveys to trigger after the user has performed a specific action or achieved a milestone. For example, sending a satisfaction survey after a customer has interacted with the customer service team.
This won’t only increase response rates but also provide more accurate responses as their experience is still fresh at that moment.
Once you’ve collected a decent amount of data, how should you look around the data to find those “actionable insights” people talk about?
Well, here are three survey analytics practices we love to use to analyze responses.
Before ever coming to any conclusion, the first step to analyzing your data is to glance over your survey’s performance.
Good survey-building tools have a built-in analytics dashboard where you can easily spot changes and patterns (especially for score-based surveys like the NPS dashboard below). Allowing you to find a potential insight that might direct your next strategy.
What’s cool about surveys is that you can tag responses and identify common keywords across promoters or detractors. This way, you can identify recurring themes that correlate with scores and either double down on what’s working or fix what’s causing people to become detractors.
And it’s not limited to NPS or CSAT surveys, you can also tag exit survey responses to find churn reasons, for example.
Another way to find valuable insights is to segment users based on their customer journey stages and look into their response patterns.
First, you need to collect customer journey data by tracking your users’ interactions and touchpoints with your product.
Then, you can analyze their survey responses within the context of their journey stage.
For example, maybe a new user isn’t satisfied with your app because they skipped the onboarding checklist (thus, you could send them an email to encourage them to use it). Or perhaps your advanced users feel “stuck” because your secondary onboarding is weak (then you could trigger in-app tooltips for feature discovery).
No matter what it is, you can only find out by making correlations.
Sure, you’re able to create and send surveys without subscribing to yet another tool.
You can also try other survey-making tools like SurveyMonkey.
But Userpilot is specifically designed with product managers and customer success teams in mind. It offers everything you need to measure user sentiment, create product satisfaction surveys without coding, and trigger them at the right time. It includes:
The right product satisfaction survey can potentially unlock SaaS growth. And with all the templates and ideas we covered, all you need to do is take action.
So choose a tool, design your in-app surveys, and start gathering customer satisfaction feedback so you can stop guessing how users perceive your product.
And given that you’ll need software, why not try a Userpilot demo to see how easily you can trigger surveys inside your app?