Customer Satisfaction Surveys - How to Analyze Them in 2021

Happy customers spread the word about your brand, and remain loyal to your product or service. In return, they expect seamless and personalized customer experiences.

There’s a lot of pressure on businesses to deliver first-class, and meaningful customer experiences and one way that has proven to be successful in meeting customer needs is listening to the voice of customers (VoC).

Customer satisfaction surveys are one of the most popular and effective ways to listen to the voice of customers. By regularly asking for customer feedback at different stages of the buyer’s journey, you can better understand customer’s challenges and pain points, and make changes to meet their expectations.

Read on to discover why customer satisfaction surveys are an invaluable source of customer feedback. Then, dive into some real-life examples of CSAT survey questions, and learn how to analyze and visualize survey responses:

What Is a Customer Satisfaction Survey?

A customer satisfaction (CSAT) survey is a questionnaire that is used to collect feedback from customers. CSAT responses let companies know what customers think about a brand, their products or services, and their level of customer service.

CSAT surveys usually start by asking customers to rate how satisfied or dissatisfied they are with a company. Then, they follow up with a question about a recent event, like a conversation with a customer service agent: “On a scale of 1-10, how well did we understand your questions and concerns?”. Finally, CSAT surveys often include open-ended questions to allow customers to share their experience in more detail, in their own words.

Happy customers are the key to long-term business success. Positive customer experiences drive loyalty, improve customer retention, and lead to more sales, so keeping tabs on how customers feel should be top of mind.

Once you’ve received your CSAT responses, you’ll need to measure customer satisfaction to find out whether your brand, products, or services are meeting your customers’ expectations. Analyzing data from CSAT surveys can yield valuable insights that help you:

  • Improve products or services, and ensure they are correctly aligned with customer needs.
  • Provide seamless customer experiences that lead to loyal customers and get them talking about your brand.
  • Gain a deeper understanding of the user experience and identify customer pain points. The more you know about your customer’s challenges and motivations, the more proactive and effective you can be when solving their problems.

Keep track of customer satisfaction over time, and compare how brand perception evolves over time.

Types of Customer Satisfaction Surveys

There are different types of surveys that businesses send to customers to understand how they feel at different stages of the customer journey. Often, they require one-word answers or a simple click and send, but there’s also the option to ask open-ended questions. Here are some of the most popular types of customer satisfaction surveys:

1. Customer Satisfaction Score (CSAT)

The purpose of CSAT surveys is to measure if you’re meeting your customers’ expectations. These surveys are sent after different touchpoints along the customer journey, and usually have a high response rate since they’re easy to respond to with a number or emoji.

The Customer Satisfaction Score (CSAT) is an important metric to assess the level of satisfaction related to a single event. While benchmarks vary by industry, you should aim for a satisfaction score of over 80%.

2. Net Promoter Score (NPS)

NPS surveys ask customers how likely they are to recommend a brand or product to their friends or colleagues, on a scale from 0 (absolutely not likely) to 10 (extremely likely). As a result, you’re able to group customers as Promoters (9 - 10), Passives (7-8) or Detractors (0 - 6).

The objective of NPS scores is to assess customer loyalty and overall satisfaction. A large number of Promoters suggests a high level of customer satisfaction.

3. Customer Effort Score (CES)

The Customer Effort Score (CES) aims to measure how much effort it takes for a customer to use your product or solve an issue with your customer support.

The goal of this score is to evaluate customer loyalty, which is determined by the customer experience. You might send a CES survey after closing a support ticket or to ask about a customer’s experience with a new feature.

4. Milestone Surveys

Milestone surveys are sent at specific stages of the buyer’s journey, to give insight into the customer experience. For example, you might send a survey to a new user after completing the onboarding process, to evaluate how it went and if it could be improved.

A popular use of this type of survey is to find out why a customer churned. By sending surveys just after a customer cancels their subscription, for example, it’s likely you’ll get their honest opinion.

Examples of Customer Satisfaction (CSAT) Surveys & Questions

Companies send CSAT surveys to capture their customers’ instant and honest feedback about a recent customer experience. Timing plays a huge part: while you need to ask the right questions, you also need to choose which stages of the customer journey to send surveys.

Here are a few tips on when to send customer satisfaction surveys:

  • After a purchase send a survey asking customers about their buying experience. Did they find the process easy? Did they get stuck at any point? You can even add an open-ended question asking if there’s anything you can do to make the process easier.

  • After a trial period: send a survey to find out if customers liked your product. Did they find it useful? Did it help them achieve their goals? Include an open-ended question like, “Is there anything you would change about this product?”.

  • After every support interaction: send CSAT surveys after a customer support ticket is closed to assess the performance of your customer service team. Did the agent solve the customer’s problem? Ask them to rate the agent’s performance and if there’s anything that could improve their experience.

  • After launching new product features: send a survey to gauge customer reactions and learn if the new features are useful: “What do you think about [feature]?”.

Now, let’s take a look at some real-life examples of CSAT survey questions from successful companies:

1. Airbnb

After an experience with Airbnb, the company invites customers (either hosts or guests) to provide product feedback by sharing “what went well and what could have gone better?”. This open-ended question allows users to give their opinion about the service in their own words.

Example of Airbnb customer satisfaction survey

Open-ended feedback is a great way of discovering potential issues and spotting dissatisfied customers. Airbnb also started using video to collect voice of customer feedback, and gain more insightful qualitative feedback. Whether video feedback catches on or not... only time will tell.

2. YouTube

YouTube uses customer satisfaction surveys to make sure they’re happy with their video recommendations. They ask viewers if they are happy with the videos that are shown to them on the homepage or in their ‘watch next’ feed. Viewers are also able to send feedback to the platform by taking a screenshot and describing the problem:

image5

3. Asana

Project management software Asana regularly asks customers for feedback through in-app surveys. Sending a survey when customers are engaged with an app or platform provides valuable qualitative insights to understand user experience.

Here’s an example of a survey Asana sent asking customers to evaluate their homepage:

Asana customer feedback survey about the platform's homepage

This survey tries to identify how customers are actually using the platform and which problems they are trying to solve. In this case, customer feedback can help them improve their product roadmap, by prioritizing those features that will be more helpful and valuable for their users. Also, qualitative user feedback might shed light on other customer needs that the company might not be aware of.

4. Zapier

When a customer hasn’t been using the app for a while, Zapier sends customers a survey asking them about their activity. Besides including a multiple-choice question, they invite customers to share more details about their experience with the app:

Example of a customer feedback survey sent by Zapier

The purpose of this survey is to identify any bottlenecks or issues that make it difficult for customers to continue using the product. This feedback can provide insights to improve the product and make it more valuable to users. Also, it allows Zapier to identify the main reasons for customer churn, and take action to retain existing customers.

5. Zoom

Zoom encourages users to send ideas, comments, or feature requests. A questionnaire asks them to select a topic and the device they’re using, then explain more about their idea, product issues, etc.

image4

This allows Zoom to handle customer feedback more effectively, by assigning messages to the right teams based on their topic and detecting issues that may occur on certain devices.

How to Analyze CSAT Surveys?

Customer satisfaction surveys can include two types of questions: close-ended and open-ended questions.

Close-ended questions (like multiple-choice, yes/no, or rating-scale questions) provide quantitative data, like the percentage of customers who are satisfied with a brand’s product or service.

Since quantitative survey data is expressed in numbers, it’s easy to analyze using Excel or Google Sheets and visualize in a dashboard.

Most survey tools offer in-built capabilities to analyze quantitative survey data, like NPS or CSAT scores. For example, here’s how SurveyMonkey displays the results of NPS surveys:

Example of SurveyMonkey's dashboard showing results of NPS surveys

Open-ended questions, on the other hand, provide qualitative data or unstructured data. These questions ‒ like, “What can we do to improve your experience?” ‒ elicit responses that offer more insight into customer’s opinions and motivations. Customers explain and describe how they feel (and why) in their own words. This data doesn’t have a predefined format, which makes it harder to process in bulk.

When you have thousands of open-ended survey responses, manually sorting each one is time-consuming and inaccurate. But there’s a far better solution: machine learning software.

Analyze Qualitative Survey Data with Machine Learning

With low-code text analysis tools like MonkeyLearn, it’s easy to implement machine learning to analyze survey data and transform feedback into action.

MonkeyLearn provides out-of-the-box solutions to help you sort survey responses by topic or sentiment, and find relevant keywords or entities in text.

For instance, this pre-trained survey analyzer sorts open-ended responses by the following topics: Customer Support, Features, Pricing, and Ease of Use:

Test with your own text

Results

TagConfidence
Customer Support61.9%

You may also want to identify positive, negative, or neutral opinions in thousands of open-ended survey responses, in which case you’d use this sentiment analyzer to automatically detect emotions in your unstructured data.

Test with your own text

Results

TagConfidence
Negative99.9%

You can also extract the main keywords from each of your open-ended survey responses with the help of this keyword extractor:

Test with your own text

Results

TagValue
KEYWORDelon musk
KEYWORDsecond image
KEYWORDspacesuit
KEYWORDbody look
KEYWORDnew design
KEYWORDphoto
KEYWORDspacex

Pre-trained models are a great way to get started with machine learning tools: they allow you to get started right away with little effort. But sometimes, you’ll require further accuracy, especially if your data contains industry-specific vocabulary.

With MonkeyLearn, you can easily build customized models, and train them with your own data and criteria. Learn how to auto-tag responses from SurveyMonkey using custom models.

Once you’re ready, you can put your models to work by uploading survey data in an Excel or a .CSV file, connecting to your favorite survey tools through the API or via point-and-click integrations.

The output will be an Excel file with your processed data, which you can then transform into compelling visualizations using MonkeyLearn Studio. Organize your survey data and create interactive dashboards to uncover insights, trends, and patterns that you simply couldn’t find in a spreadsheet:

A dashboard created on MonkeyLearn Studio, showing the results of analyzing Zoom reviews.

Conclusion

Customer satisfaction (CSAT) surveys are the cornerstone of your feedback strategy. Analyzing your survey responses provides unique insight into the customer experience and helps you improve every step of the buyer’s journey.

While quantitative survey data is valuable to measure your overall performance, qualitative data offers a much richer perspective of your customer’s motivations and feelings.

Machine learning software like MonkeyLearn can take your survey analysis to the next level, and help you draw insights from open-ended survey responses through intuitive, no-code tools.

Request a demo from one of our experts to learn more about how to customer satisfaction surveys with MonkeyLearn.

Inés Roldós

January 11th, 2021