What is Net Promoter Score (NPS)
Net Promoter Score (NPS) is a customer loyalty and satisfaction measurement based on the likelihood of customers recommending your product or service to others. The score is calculated by asking customers:
“On a scale of 0 – 10, how likely are you to recommend to a friend?”
How is the score calculated?
The responses to the above question are collated into the following categories:
- Promoters (scores of 9 or 10) – these are happy customers who are highly likely to recommend you to others and speak highly of your products or services.
- Passive (scores of 7 or 8) – these customers aren’t highly satisfied and are at risk of switching to a competitor.
- Detractors (scores between 0 – 6) – these customers are unsatisfied and likely to take their business elsewhere. They are also likely to dissuade potential new customers.
Once you have classified your customers into one of these groups, you can then calculate your company’s Net Promoter Score using the per cent of promoters and detractors, as shown below. Passives aren’t used to calculate the score.
For example, if you conducted the survey and 70% of the respondents rated 9 or 10, and 10% rated you 1 – 6, your score would be 60. This is a commendable score, meaning the customer majority are promoters.
(70% – 10%) x 100 = 60.
The 3 top advantages to tracking NPS
- Provides invaluable insights into the health of your customer base
- Effectively measures customer loyalty and satisfaction
- Reduces customer churn rate
By using NPS and expanding these scores into open conversations with your customers you can improve your business, products, services and improve your satisfaction score.
How can Machine Learning be used to increase client satisfaction?
Machine learning can be used to learn customer behaviours and not only predict scores where there may be missing data, but also predict scores over the entire relationship with your customers. Estimating NPS shows you trends and changes in customer loyalty and provides an opportunity to improve your customer experience and address any negative issues.
How Amdaris uses Machine Learning to rank in the Top 25% of our industry for NPS
At Amdaris our machine learning tool automatically learns our client’s behaviours and uses them to predict NPS scores across our client base. Running continuously, it regularly predicts and updates scores across all of our projects.
This makes sure we remain in the top 25% of our industry for delivering customer satisfaction.
You can view our full NPS case study to learn more about how we use it at Amdaris.
If you would like to speak to someone to find out more about out about Machine Learning, please get in touch. Call +44(0)117 935 3444 or contact us using the form below.
You can also read more in our Azure Databricks blog series.