About Recommendation Score Questions
The Recommendation Score question is based on the Net Promoter Score® (NPS) method. However, Recommendation Score questions, unlike NPS questions, which are based on a 0-10 scale, can be based on different scales. They are an effective way to gauge customer loyalty by asking the ultimate question "How likely is it that you would recommend [company/product/service] to a friend or colleague?"
Respondents are segmented into three groups according to the rating they gave:
Promoters (those who answer 9 – 10) are loyal and will recommend you to their networks. They are your ambassadors and are therefore more likely to remain customers and increase their purchases over time.
Passives (those who answer 7 – 8) are satisfied for now but your company, product, and/or service didn’t leave a lasting or permanent impact. They won’t vouch for you but may mention you within the right context.
Detractors (those who answer 0- 6) are not happy! They will actively spread negative word-of-mouth and tend to be louder (and scarier) than promoters.
The score itself ranges from -100 to 100. It is calculated by taking the percentage of Promoters minus the percentage of Detractors, therefore a positive score means you have more promoters than detractors and vice versa. To increase your NPS, you have to boost the percentage of Promoters by reducing Passives and Detractors.
In reports, Enalyzer automatically calculates the recommendation score, as well as segments respondents into Promoters, Passives, and Detractors in Frequency and Time Series charts.
Add Recommendation Score Questions
To add a Recommendation Score question, all you have to do is:
- Go to your survey, click the add survey element icon (
), and choose question.
- Choose recommendation score, and click next.
- Edit the question text if you need to. You can also change the typography (bold, italic, and underline).
Use the merge field dropdown menu to insert your respondents' background information or their answers to previous questions.
The length of question text is restricted to max. 250 characters.
- It's time to define your scale and you have various options:
- Steps: Select the number of steps for your scale.
- Reverse scale: If you'd like to reverse the scale enable the setting.
- Start from zero: By default, this setting is enabled, disable it if you'd like your scale to start from
- 'Don't know' or 'N/A' option: Enable this setting to include a don't know or N/A option that will be automatically excluded from average calculations in reports.
- When you are satisfied with your question, click next.
- Now you can set up the question settings:
- Open answers: This setting allows respondents to elaborate on their answers.
- Require answer: This setting is enabled by default. Disable it if you don’t want your question to be mandatory.
- Layout (button scale): Select the question's layout and decide how your scale is visually presented to your respondents. Button scale is the default layout but you can change it to a dropdown.
- When you have finalized your question and customized the settings, click add.
Recommendation Score Questions in Response Data Downloads
You can download your survey responses from Enalyzer for several purposes. You can use the file for analysis in other software, share it with your team, or import it to another Enalyzer survey.
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In the response data download, Recommendation Score questions are found in one column. By default, in each respondent's row, each response option in the question will be displayed with the response option value. You are able to edit the format output, you can read about data formats here.
- If you enabled the open answer setting, these will have their own column. The column name will be the number of the question followed by "_Open"
Recommendation Score Questions in Reports
You can visualize the data collected by your Recommendation Score questions in your reports. The available charts for Recommendation Score questions are:
Enalyzer automatically calculates the Recommendation Score, as well as segments respondents into Promoters, Passives, and Detractors in Frequency and Time Series charts.
Reports remove "don't know" and "N/A" options from average calculations for Recommendation Score questions.