Sending surveys allows you to keep a pulse on customer satisfaction. When you know how customers feel about your brand you can make strategic decisions to increase customer loyalty, retention, and – in the long run – drive more sales.
The most common customer surveys are Customer Satisfaction (CSAT) and Net Promoter Score (NPS).
While they both contain a simple close-ended question to help businesses determine their satisfaction scores, as well as an open-ended question to understand the reasons behind each score, each survey focuses on a different aspect of customer happiness.
Let’s take a look at the key differences between CSAT and NPS surveys:
Customer Satisfaction Score (CSAT) is a metric that expresses a customer’s level of satisfaction with a brand, its product or services, or a particular interaction during the buyer’s journey.
The purpose of CSAT surveys is to measure customer happiness after each meaningful touchpoint, like completing a transaction, or prior to an important milestone, like renewing a subscription.
A CSAT survey usually asks customers to rank a recent experience on a scale of 1 to 5, in which 1 is Very Unsatisfied and 5 is Very Satisfied. The average response score is the CSAT score:
CSAT surveys often include open-ended questions, which provide further details of the customer experience. When you analyze both quantitative and qualitative survey data, you can identify what drives your CSAT score up or down, and pinpoint which aspects of your business need improvement.
There are also CES (customer effort score) surveys, which we’ll briefly mention here.
They’re a type of customer satisfaction (CSAT) survey, and measure how easy it is for customers to use a product or service or resolve a problem – usually on a scale from “very difficult” to “very easy.”
CES surveys are similar to CSAT surveys, in that they are sent following recent interactions so, for the purpose of this post, we’ll bucket them under CSAT surveys.
Net Promoter Score (NPS) indicates whether or not customers will recommend your brand, product, or service to friends or colleagues. NPS surveys ask customers to express their referral intention on a scale of 0 to 10 and, based on their responses, customers will fall into one of three groups:
To calculate your business’ NPS score, subtract the percentage of Detractors from the percentage of Promoters.
Customer satisfaction (CSAT) surveys measure short-term happiness following a recent interaction with your brand, while Net Promoter Score (NPS) surveys focus on the overall brand experience to gauge satisfaction and customer loyalty.
Let’s take a look at the main differences between CSAT and NPS in more detail:
Send CSAT surveys right after meaningful touchpoints or milestones. For example:
Send NPS surveys to close the feedback loop after a customer goes through the entire buyer’s journey. It may be useful to choose neutral touchpoints, so that customers don’t link their answer to their most recent interaction. For example:
Finally, make sure to send NPS surveys regularly (for example, the same month every year) so you can keep track of the results and analyze brand happiness and loyalty over time.
CSAT surveys allow you to analyze interactions or experiences at a micro level, while NPS provides you with macro level insights.
However, combining both types of surveys can give you a more precise overview of the customer experience, and often businesses will use both surveys to measure customer satisfaction.
No matter which survey you use (NPS or CSAT), always include open-ended questions.
Metrics can give you a sense of how well or bad you are doing (compared to previous surveys or against industry benchmarks), but they don’t explain the reasons behind customer scores.
Qualitative data, on the contrary, can help you understand exactly what makes customers happy or unhappy, and therefore, identify what you need to improve to provide a better customer experience.
AI tools like MonkeyLearn can make it very easy for you to analyze qualitative survey data.
Through intuitive, low-code tools powered by machine learning, you can classify large amounts of survey responses by topic or sentiment, or find relevant keywords for each piece of feedback.
Imagine you included this open-ended question in your latest NPS survey: ‘How can we improve your experience?’.
With a ready-to-use survey analyzer, you can automatically tag each survey response by topic, using categories like Customer Support, Ease of Use, Pricing, or Features.
CSAT and NPS surveys are two powerful tools to measure customer satisfaction and lead the way towards better customer experiences. They provide an overview of how your business is doing, and which areas you need to improve.
However, to really understand how you need to improve aspects of your business, you also need to analyze the qualitative data found in the open-ended responses.
This qualitative data can reveal where you are falling short and offer you detailed insights into what your customers need.
MonkeyLearn provides a suite of intuitive AI tools to help you make sense of qualitative survey data and gain real-time, actionable insights.
Reach out for a demo to learn more about how to power up your CSAT and NPS survey analysis with AI tools.
January 21st, 2021