Net Promoter Score NPS
SurveyMars now supports Net Promoter Score (NPS) survey .It is an index used to research the likelihood of users recommending a brand/product/service to others. It helps understand users' willingness to actively recommend a brand/product/service and is a common loyalty indicator.
What is NPS
Net Promoter Score (NPS) is a research method used to measure customer loyalty by asking customers how likely they are to recommend your brand/product/service to others. The data collection is simple - you only need to design a survey question asking respondents to rate their likelihood of recommendation on a scale of 0 to 10 points, where 0 represents the lowest likelihood and 10 represents the highest likelihood.
After collecting the data, scores are automatically classified into three groups:
- Detractors: Scores between 0-6 points. These users are unlikely to recommend and may even discourage others from using your product/service.
- Passives: Scores between 7-8 points. These users are satisfied but not enthusiastic enough to actively recommend.
- Promoters: Scores above 8 points (9-10). These users are highly satisfied and likely to recommend your product/service to others.
The NPS value measures the degree of recommendation. The formula is: NPS Value = Promoters% - Detractors%, which is the percentage of promoters minus the percentage of detractors. The result ranges from -100% to +100%.
Creating an NPS Question
1. Navigate to your survey design page and select "NPS" question type to add to your survey.
2. Enter your NPS question. For example: "How likely are you to recommend [Product/Service Name] to a friend or colleague? (Rate from 0 to 10 points)"
3. Configure the scale settings. Ensure the scale ranges from 0 to 10, where 0 represents "Not at all likely" and 10 represents "Extremely likely".
4. (Optional) Add follow-up questions based on the score:
- For scores ≤6: Add a question asking for reasons for low scores
- For scores 7-8: Add a question asking for reasons for moderate scores
- For scores 9-10: Add a question asking for reasons for high scores
5. (Optional) Adjust any additional settings for the question:
Making Survey Questions Required/Optional
6. Click Finish to save your NPS question.
7.Share your survey and collect data.
NPS Analysis
1. Navigate to the analysis section of your survey.
2. Click "Analysis Results" from the analysis options.
Understanding NPS Results
The NPS value is calculated automatically using the formula: NPS Value = Promoters% - Detractors%
You can analyze the distribution of scores and identify patterns. For example:
- If scores are concentrated in the 8-10 range, it indicates strong user loyalty
- If there are many scores in the 0-6 range, it suggests areas for improvement
- If scores are evenly distributed, it may indicate mixed user sentiment
Interpreting NPS Values
There is no fixed standard for what constitutes a high NPS value. Typically, 50% is considered a relatively high value. However, interpretation depends on your industry and comparison baseline.
NPS Value Ranges:
- Negative NPS (-100% to -1%): Indicates that detractors outnumber promoters, suggesting significant dissatisfaction among users. This requires immediate attention.
- Low NPS (0% to 30%): Indicates more promoters than detractors, but overall loyalty is relatively low. There is room for improvement.
- Moderate NPS (31% to 50%): Indicates good customer loyalty. Promoters significantly outnumber detractors.
- High NPS (51% to 100%): Indicates excellent customer loyalty. A large majority of users are promoters.
Tracking NPS Over Time
Researchers can collect NPS data multiple times and compare NPS values and changes in the three types of users to comprehensively measure changes in user loyalty.
1. Collect NPS data at regular intervals (e.g., quarterly, semi-annually, or annually).
2. Compare NPS values across different time periods to identify trends.
3. Analyze changes in the distribution of Detractors, Passives, and Promoters to understand what drives loyalty changes.
4. Use the insights to measure the effectiveness of improvements and identify areas that need attention.
Case Study Example
Background: The marketing department wants to study brand loyalty. NPS data was collected three times: at the beginning of the year, mid-year, and end of the year, with 116 samples collected each time.
Data Collection: Each survey asked respondents: "How likely are you to recommend our brand to a friend or colleague? (Rate from 0 to 10 points)"
Score Distribution Table
The following table shows the percentage distribution of scores (0-10) across the three surveys:
| Score | Survey 1 (%) | Survey 2 (%) | Survey 3 (%) |
|---|---|---|---|
| 0 | 0.9 | 0.0 | 0.0 |
| 1 | 1.7 | 0.0 | 0.0 |
| 2 | 0.9 | 0.9 | 0.0 |
| 3 | 0.9 | 0.0 | 0.0 |
| 4 | 2.6 | 1.7 | 0.9 |
| 5 | 8.6 | 12.1 | 3.4 |
| 6 | 12.1 | 10.3 | 5.2 |
| 7 | 15.5 | 17.2 | 10.3 |
| 8 | 19.0 | 20.7 | 15.5 |
| 9 | 17.2 | 15.5 | 25.0 |
| 10 | 20.7 | 21.6 | 39.7 |
Category Distribution and NPS Values
The following table shows the distribution of Detractors, Passives, and Promoters, along with the calculated NPS values:
| Category | Survey 1 | Survey 2 | Survey 3 |
|---|---|---|---|
| Detractors (0-6) | 27 (23.3%) | 28 (24.1%) | 11 (9.5%) |
| Passives (7-8) | 40 (34.5%) | 44 (37.9%) | 30 (25.9%) |
| Promoters (9-10) | 44 (37.9%) | 43 (37.1%) | 75 (64.7%) |
| NPS Value | 14.6% | 13.0% | 55.2% |
| Total Respondents | 116 | 116 | 116 |
NPS Trend Comparison
Results Analysis:
- First survey (beginning of year): NPS value was 14.6%, indicating that promoters (37.9%) exceeded detractors (23.3%) by about 14.6%, with relatively low overall user loyalty. Some respondents chose scores of 1, 2, or 3, suggesting some users had negative feelings about the product. Scores were concentrated in the 5-10 range, with 8-10 points being more common.
- Second survey (mid-year): NPS value was 13.0%, remaining similar to the first survey, showing no significant improvement. Notably, the percentage of Detractors (24.1%) was slightly higher than the first survey, and the percentage of respondents scoring 5 points (12.1%) was relatively high. The distribution remained similar to the first survey.
- Third survey (end of year): NPS value increased significantly to 55.2%, showing a dramatic improvement in user loyalty. Promoters increased from 37.9% to 64.7%, while Detractors decreased from 23.3% to 9.5%. This indicates that improvements made throughout the year were highly effective. Scores of 9-10 points became dominant, with 39.7% of respondents giving a perfect score of 10.
Key Insights: By collecting NPS data multiple times, the company was able to track changes in user loyalty and measure the effectiveness of their improvements. The significant increase from 14.6% to 55.2% demonstrates the value of continuous monitoring and improvement. The dramatic reduction in Detractors (from 23.3% to 9.5%) and increase in Promoters (from 37.9% to 64.7%) shows that the improvements resonated well with users.
FAQ
Q1: What score range should I use for NPS data collection?
A: NPS raw data scores must be between 0 and 10 (including 0 and 10). If your data is not in this range, use data encoding to convert the numbers before analyzing NPS. This is a critical requirement for accurate NPS calculation.
Q2: What is considered a good NPS value?
A: There is no fixed standard, but typically 50% is considered a relatively high value. However, interpretation depends on your industry and comparison baseline. It's best to compare your NPS against industry benchmarks and track changes over time.
Q3: How should I interpret negative NPS values?
A: A negative NPS value indicates that detractors outnumber promoters, which suggests significant dissatisfaction among users. This requires immediate attention to improve product/service quality. Focus on understanding the reasons for low scores and addressing the most critical issues.
Q5: How often should I collect NPS data?
A: It's recommended to collect NPS data regularly (e.g., quarterly, semi-annually, or annually) to track changes in user loyalty over time. This helps measure the effectiveness of improvements and identify trends. The frequency depends on your business cycle and how quickly you can implement changes.
Q6: Why are Passives (scores 7-8) not included in the NPS calculation?
A: Passives are not included in the NPS formula because they represent neutral sentiment - they are satisfied but not enthusiastic enough to actively recommend. The NPS formula focuses on the difference between Promoters (who actively recommend) and Detractors (who may discourage others), which provides a clearer measure of customer loyalty.
Q7: Can I compare NPS values across different products or services?
A: Yes, you can compare NPS values across different products, services, or time periods. However, ensure that the data collection methods and question wording are consistent to make valid comparisons. Also consider industry-specific factors that may affect NPS values.
Important Notes
- NPS raw data scores must be between 0 and 10 (including 0 and 10).
- NPS values range from -100% to +100%. A positive value indicates more promoters than detractors, while a negative value indicates the opposite.
- Collecting NPS data multiple times allows you to track changes in user loyalty and measure improvement effectiveness. Regular monitoring helps identify trends and measure the impact of changes.
- Typically, an NPS value of 50% or higher is considered relatively high, but interpretation depends on industry benchmarks. Compare your NPS against competitors and industry standards.
- The classification process (Detractors, Passives, Promoters) is handled automatically by the system. Scores 0-6 are Detractors, 7-8 are Passives, and 9-10 are Promoters.
- Passives are not included in the NPS calculation formula, but they are important to monitor as they represent potential for conversion to Promoters.
