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Analysis - Interpreting NPS / CSAT / CES
The main questions of a survey are what we call metric questions. We offer three metrics:
- Net Promoter Score (NPS)
- Customer Satisfaction Score (CSAT)
- Customer Effort Score (CES)
Depending on the questions you added in your survey, you will find the analysis of one or more metric questions in the analysis part of the platform. In this article, we will explain how you should interpret the analysis of the different metric questions.
IN THIS ARTICLE
1. How to get there
Option 1
On the homepage, click directly on the analysis icon of the touchpoint for which you want to see the analysis.
Option 2
Step 1: Click on Analysis in the left navigation menu
Step 2: Choose the touchpoint for which you want to see the analysis
2. Interpreting the numbers
When you land on the analysis page, you will see that each question you added in your touchpoint will get its own tab. Each metric question gets a tab to show the results of the metric question itself and a text analysis (ISAAC) tab which shows the result of the open text question linked to the metric. Learn more about the ISAAC analysis and how to interpret it in this article.
2a. Net Promoter Score (NPS)
i. What is NPS?
The Net Promoter Score is a useful method to measure customer satisfaction and loyalty and shows the overall perception of the respondents about your company. Therefore, it's a metric that is mainly used in relational surveys, not after a specific transaction, for which CSAT and CES are more useful. To learn more about the Net Promoter Score, we recommend reading this blog post.
Our survey system uses two questions:
- The metric question itself: a 0-10 scale question that asks respondents how likely they are to recommend your company to a friend or colleague.
- An open question which allows the customer to freely describe why s/he attributed his mark.
Respondents are put into three categories based on how they answer the first question: detractors, passives and promoters.
- Detractors: respondents who gave a score between 0 and 6.
- Passives: respondents who gave a score of 7 or 8.
- Promoters: respondents who gave a score of 9 or 10.
The Net Promoter Score is calculated by substracting the percentage of detractors from the percentage of promoters. Therefore, it should not be seen as a percentage, but rather as an absolute number lying between -100 and +100.
ii. NPS visualizations
With the date picker on top of the page, you can choose for which period you want to see the NPS.
The general overview of the NPS will show you:
- the NPS (% promoters - % detractors)
- % detractors (respondents who gave a score between 0 and 6)
- % passives (respondents who gave a score between 7 and 8)
- % promoters (respondents who gave a score between 9 and 10)
In the repartition, you can see more details about the exact division of the individual scores. For each individual score, you see the exact number of respondents at the bottom and the percentage on top. In case the numbers are too small, they are not shown, but you can always trigger them on hover.
Last, but certainly not least, you can also see an evolution of your NPS. You can choose whether you want to see this evolution on a daily, weekly or monthly basis. The dots on the line represent the score that is calculated at the end of the chosen interval. For the weekly interval, for example, this is on a Sunday. You can hover your mouse over the dots to see the score and the date of the calculation.
There are two lines in the graph:
- Daily / weekly / monthly average: the average of the scores submitted that day / week / month
- Moving average: the average of the first day of the selected date range until the day / week / month the dot represents
In the example above:
- Weekly average of week 19/12/2022
- average of all people who answered the survey in "week 19/12/2022" = between 19/12/2022 and 25/12/2022
- NPS = 100, with 75 people answering the survey
- Moving average of week 19/12/2022
- average of all people who answered the survey since the first date of the selected date range, in this case 1/12/2022, until the last day of the week 19/12/2022 = 25/12/2022
- NPS = 64,29, with 210 people answering the survey
iii. Interpreting the NPS
Interpreting the NPS is not easy because it depends on a lot of factors. If your touchpoint only has a small number of respondents, for example, the score could be unusually high or unusually low due to the lack of data.
As a general rule of thumb:
If you want to read more about what a good NPS is, we recommend reading this blog article.
2b. Customer Satisfaction Score (CSAT)
i. What is CSAT?
The Customer Satisfaction Score (CSAT) is a score that measures how happy customers are with a business, product or service. The CSAT is mainly used after a customer had an interaction with your company, for example bought something in your shop. If you want to learn more about this metric, we recommend to read this blog article.
Our survey system uses two questions:
- The metric question itself: a 1-5 scale question that asks respondents how satisfied they are with a business, product or service.
- An open question which allows the customer to freely describe why s/he attributed his mark.
Respondents are put into three categories based on how they answer the first question: people who are satisfied, people who were neutral and people who are unsatisfied.
- Satisfied: respondents who gave a score of 4 or 5
- Neutral: respondents who gave a score of 3
- Unsatisfied: respondents who gave a score of 1 or 2
The CSAT itself is equal to the percentage of satisfied customers.
ii. CSAT visualizations
With the date picker on top of the page, you can choose for which period you want to see the CSAT.
The general overview of the CSAT will show you:
- the CSAT (% satisfied customers)
- number and % unsatisfied customers (respondents who gave a score between 1 and 2)
- number and % neutral customers (respondents who gave a score of 3)
- number and % satisfied customers (respondents who gave a score between 4 and 5)
In the repartition, you can see more details about the exact division of the individual scores. For each individual score, you see the exact number of respondents at the bottom and the percentage on top. In case the numbers are too small, they are not shown, but you can always trigger them on hover.
Last, but certainly not least, you can also see an evolution of your CSAT. You can choose whether you want to see this evolution on a daily, weekly or monthly basis. The dots on the line represent the score that is calculated at the end of the chosen interval. For the weekly interval, for example, this is on a Sunday. You can hover your mouse over the dots to see the score and the date of the calculation.
There are two lines in the graph:
- Daily / weekly / monthly average: the average of the scores submitted that day / week / month
- Moving average: the average of the first day of the selected date range until the day / week / month the dot represents
In the example above:
- Weekly average of week 12/12/2022
- average of all people who answered the survey in "week 12/12/2022" = between 12/12/2022 and 18/12/2022
- CSAT = 60,16, with 246 people answering the survey
- Moving average of week 12/12/2022
- average of all people who answered the survey since the first date of the selected date range, in this case 1/12/2022, until the last day of the week 12/12/2022 = 18/12/2022
- CSAT = 73.51, with 672 people answering the survey
iii. Interpreting the CSAT
Basically, CSAT is the percentage of satisfied customers. However, the distribution of the scores can be more interesting than the score itself
Although you have a good score, it can be interesting to take a look at the lowest scores that are dragging your score down. The customers who give the lowest scores are the customers that are important to look into.
CSAT only measures short term happiness. The metric is commonly used to survey customers shortly after an interaction with a company, such as after a customer has contacted customer support. This type of survey is a great way to close the loop on a customer interaction and to make sure that you have met your customers’ expectations. This opportunity for the customer to give a quick thumbs-up or thumbs-down on their last experience with your brand, helps you to quickly quantify short-term happiness across the total of recent customer exchanges.
2c. Customer Effort Score (CES)
i. What is CES?
The Customer Effort Score (CES) is a score that measures customer effort in particular interactions. In other words, it measures the simplicity of an experience with a company. CES is extensively used to measure the quality of interactions that require input from customers, such as interactions with customer care teams for example. To learn more about the CES, we recommend reading this blog article.
Our survey system uses two questions:
- The metric question itself: a 1-7 scale question that asks respondents how hard it was for them to perform a certain action.
- An open question which allows the customer to freely describe why s/he attributed his mark.
Respondents are put into two categories based on how they answer the first question: people who agree and people who disagree.
- Agree: respondents who gave a score between 5 and 7
- Disagree: respondents who gave a score between 1 and 4
The Customer Effort Score is calculated by calculating the average of all scores. Therefore, if the score is 5 or higher, people tend to agree that it was easy to handle the issue.
ii. CES visualizations
With the date picker on top of the page, you can choose for which period you want to see the CES.
The general overview of the CES will show you:
- the CES (average of all scores)
- number and % disagree (respondents who gave a score between 1 and 4)
- number and % agree (respondents who gave a score between 5 and 7)
In the repartition, you can see more details about the exact division of the individual scores. For each individual score, you see the exact number of respondents at the bottom and the percentage on top. In case the numbers are too small, they are not shown, but you can always trigger them on hover.
Last, but certainly not least, you can also see an evolution of your CES. You can choose whether you want to see this evolution on a daily, weekly or monthly basis. The dots on the line represent the score that is calculated at the end of the chosen interval. For the weekly interval, for example, this is on a Sunday. You can hover your mouse over the dots to see the score and the date of the calculation.
There are two lines in the graph:
- Daily / weekly / monthly average: the average of the scores submitted that day / week / month
- Moving average: the average of the first day of the selected date range until the day / week / month the dot represents
In the example above:
- Weekly average of week 5/12/2022
- average of all people who answered the survey in "week 5/12/2022" = between 5/12/2022 and 11/12/2022
- CES = 5,22, with 18 people answering the survey
- Moving average of week 5/12/2022
- Average of all people who answered the survey since the first date of the selected date range, in this case 1/12/2022, until the last day of the week 5/12/2022 = 11/12/2022
- CES = 5.38, with 26 people answering the survey
iii. Interpreting the CES
Basically, CES is calculated as an average. However, the distribution of the scores can be more interesting than the score itself.
Although you have a good score, it can be interesting to take a look at the lowest scores that are dragging your average down. The customers who give the lowest scores are the customers that are important to look into.
According to a study conducted by the Corporate Executive Board Company (CEB), moving customers from 1 to 5 increases their loyalty by 22%, while moving customers from 5 to 7 increased their loyalty by only 2%.
3. NPS, CSAT and CES for specific customer groups
Filtering on participant attributes (metadata) can be very beneficial in determining how satisfied (CSAT), eager to recommend your company (NPS), or how simple a procedure was for a certain customer segment, as well as how they feel about your staff, products, etc. Comparing different groups to one another can also be interesting which is why we added smart filtering to the platform to simplify this process. To learn everything about smart filtering and comparing groups, read this article.