Customer Satisfaction Surveys: Time to shift gears?

A few days ago, I visited one of the leading chains of super markets to buy groceries for the week ahead. The billing queue was long and I was gazing at various brands of chocolates neatly stacked on the shelves on either side. Just then, a store personnel approached me with a printed form. You guessed it; she wanted me to take the customer feedback survey.  I agreed to take up the survey (Yes, she was charming, but that was just not the only reason for me to take the survey).  Being in the profession of propagating data driven decision making, I decided to make a contribution to much needed data. I also wanted to contribute for a larger cause. Read on to know!

Customer Satisfaction Surveys
Image courtesy of tiramisustudio at

Customer centricity and revenue; what is the connection?

Over the past decade, we have witnessed many firms realigning their businesses to focus on customer centricity. Firms have opened up new communication channels and are reaching out to customers via their preferred channels – with right offers at the right time.

Can firms leverage customer satisfaction information to predict future revenues? Can they tell with confidence that an X percent increase in customer satisfaction can boost firm’s revenues by Y percent?  What would be the return on Investment (Bottom line growth) on customer satisfaction improvement efforts?  How will the Life time value of the customer and cost per customer acquisition change?

C-Sat Surveys of yesterday, not enough today

C-SAT (Customer Satisfaction) surveys are widely used today to understand the pulse of the customer. A typical C-SAT survey consists of a question on overall satisfaction/willingness to recommend  product or service and several other questions which contribute to overall satisfaction / likeliness to recommend. In addition to this there are a couple of open ended questions to capture customer’s views and thoughts. Survey analytics conducted on the responses helps understand the drivers that contribute to overall satisfaction and also mine insights from customer feedback on open ended questions. It also enables tracking of the trends in customer satisfaction and expectations over time.

Is this enough?

Enter the Concept of Net Promoter Score

“Net Promoter Score” is a customer loyalty metric introduced by Reichheld in his 2003 Harvard Business Review article “One Number You Need to grow”. NPS score ranges from -100 to +100.

Let us take an example to understand how net promoter score is measured. NPS is based on a direct question: How likely are you to recommend our company/product/service to a friend or colleague? The scoring for this answer is most often based on a 0 to 10 scale.

Respondents who give a score of (9, 10) are flagged as promoters and those who give a score ranging from 0-6 are flagged as detractors. NPS is measure of  the difference in percentage terms between the Promoters and Detractors.

NPS can be as low as −100 (which means that everybody is a detractor) or as high as +100 (which means that everybody is a promoter). An NPS that is positive (i.e., higher than zero) is felt to be good, and an NPS of +50 is considered excellent.

The Missing Link between Satisfaction (NPS) and Revenue

There are several ways to relate NPS and revenue; we will see couple of them below

Method 1: Find Correlation between NPS score and revenue and predict revenue

In this method, we need to track the NPS score trend and correlate it with revenue figures.  Use the correlation factor to predict future revenues.  This is a very simple and straightforward approach.

Net Promoter Score (NPS) - graph1
Illustrative Graph Showing Correlation between NPS and Revenue by Time

Correlation Factor = 0.864367

Method 2:  ARPU by NPS Segment

  1. Find Average Revenue per user for each NPS bucket.
  2. Find the proportion of customers in each NPS segment and track trend
  3. Quantify the net revenue impact by multiplying the corresponding ARPU with the net percentage of customers added / removed from each segment
Net Promoter Score - graph2
Illustrative Graph Showing distribution of Promoters, Neutrals, Detractors and ARPU by each bucket
Net promoter score - table1-2013
Year 2013 – Respondent and ARPU distribution


Consider a situation where 5 % of customers moved from neutral to Promoters Band.

Net Promoter Score - table2-2014
Year 2014 – Respondents and ARPU distribution

The new revenue would be

Revenue = (55% of customer base *65 )+ (15% of customer base *40)+(30% of customer base *15)

Using the above methods firms can predict future revenues by measuring customer satisfaction and loyalty levels. They can accurately predict the revenue impact for every 1% increase in NPS score and easily provision funds for increasing customer satisfaction. Depending on the industry nature and competition, firms can also accurately estimate the dollar investment needs for increasing NPS score by 1 %

Does this explain why we see such a large number of customer surveys floating around us? Just by participating in the survey, did I also help the retailer to boost his revenue?

What do you think? I would love to hear from you.

This blog is written by Neeraj Krishnamoorthy, Analytics Consultant at BRIDGEi2i

About BRIDGEi2i: BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. Our analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. To know more visit

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The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.