4 Key ‘Must-Measure, Can’t Leave’ Customer Experience (CX) Metrics

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In a world of analytics, most organizations have enough data, metrics and dashboards to deal with. When it comes to customer experience (CX), unfortunately, many organizations don’t always measure and report the right metrics. For example, in a 2018 NPS & CX Benchmark report, One-third of organizations don’t measure Customer Churn or Retention. This is indeed an irony because organizations spend enormous amount of resources in marketing and sales and finally they don’t track how many of those acquired customers have been retained or what let them to attrite.

Immaterial of how big your organization is, and which sector you belong to, here are 4 top line Customer Experience metrics that you should be tracking. Consider these as bear minimum that should be measured. But I would caution against going overboard on Customer Experience Measurement. A survey pointed out that some organizations measure as much as 200 odd metrics relating to Customer Experience. That’s overwhelming, isn’t it!
What are CX Top Line Metrics?

Top Line Metrics are those which are lag measures or outcome indicators. They keep us tied to our long term vision. These metrics don’t improve by themselves. To show an improvement on these metrics, we need to improve other independent or lead CX metrics.

I’m going to restrict the scope of this resource paper to top line Customer Experience Metrics and CX lead measures to be dealt separately.

The most important top line Customer Experience Metrics that you should measure are:

  • NPS
  • CLV/CAC
  • Customer Churn
  • CES


We’ll talk about each briefly now.

NPS (Net Promoter Score)

Probably, there is no explanation needed as NPS has gained enormous popularity in the last decade or so. Over 70% of fortune 1000 companies use NPS to measure their brand loyalty.

The advantage of NPS is its simplicity (single question format) to assess the customer’s intention to recommend the product/service to trusted ones, such as family and friends. The uniqueness of the question lies in its 11 points survey scale (0 to 10) with 0 to 6 as detractor, 7 & 8 as passive and 9 & 10 as promoter.

Net promoter Score is the difference between proportion of promoters and proportion of detractors. A detailed understanding of NPS scores, its merits and demerits is not covered here.

Data of sector wise NPS scores are tracked by Satmetrix and CX & NPS Benchmark Reports.

The next metric we’ll talk about is a ratio.

CLV/CAC (Customer Lifetime value/Cost of Acquisition of Customer)

CLV is Customer Lifetime Value and CAC is Cost of Acquisition of Customer. What we are interested here is the ratio of CLV to CAC.

What is CLV?

Customer Lifetime Value (CLV) aka Lifetime Customer Value (LCV) is the net financial value (or economic value) associated to the relationship between customer and the organization.

CLV is a very good metric to let us know how much money we are making from a customer. When averaged out, we can generalize it for the entire customer base. If we don’t make enough money from the relationships we have with our customers, then we may seize to be in business sooner or later.

Calculating the net financial value or the net contribution (profit) from an ongoing relationship with the customer will involve the contribution we have made in the past and estimating the future contributions. Thus, CLV is an estimated metric.

There are several ways in which CLV can be computed, the details of this covered in a separate resource paper.

In its simplest form, CLV is the average sum of contribution made by customers till they churn or retire.

Thus CLV takes into consideration the ‘average contribution from customer per period’ and ‘the expected number of periods the customer stays with the company’.

For example, if the average customer revenue for a telecom company like Vodafone-Idea, Jio or Airtel is Rs.1000 per month and if the cost of offering the service is Rs.800, then their Average customer contribution is Rs.200 per month. If an average customer stays with an operator for 12 months before churning out, then CLV is Rs.2400 (200 x 12).

This calculation takes into consideration, the customer retention rate (or customer churn rate) & average contribution per customer.

We all know the future value of cash flows is less than its present value. So, this formula can be adjusted or improved to include this aspect.

As CLV puts an economic value to customer relationship, it is very good metric for the following:

  • Evaluate if our delivery model is viable
  • Consider how we can refine our customer service, so as to increase CLV
  • Sensitize employees about economic value and inculcate ownership in them
  • Evaluate individual customers as against average CLV, to know whose relationship is more valuable to us. This can also help in customer segmentation


Unfortunately, in India, Customer Lifetime Value (CLV) is still a metric owned by Marketing and Customer Experience (CX) professionals are yet to embrace it.

What is CAC?

Customer Lifetime Value (CLV) alone may help us to some extent in refining our operations & service delivery model, but CX (Customer Experience) starts right from marketing. Hence we need a metric that considers the end to end impact. That can only be achieved by considering CAC, that is, Cost of Acquisition of Customers.

CAC is the average cost of acquiring a customer that includes marketing and sales expenses. It also includes offers and discounts.

CLV/CAC

The ratio of CLV to CAC is very useful to evaluate the entire business model and its viability. When the cost of acquisition is greater than the CLV, the answer is straightforward – Business model isn’t viable. For a sound business, as a rule of thumb, the CLV is 3 to 4 times CAC.

There are many factors which drive this, but Customer Experience (CX) professionals can play a significant role in optimizing this ratio using levers of Customer Experience (CX).

Further, tracking the trend of CLV & CLV/CAC ratio will help Customer Experience (CX) professionals to assess the impact of Customer Experience (CX) initiatives implemented in the organization. Many organizations in India, lack robust ways to evaluate the ROI of Customer Experience (CX) initiatives or projects and this metric can go a long way in doing that.

Customer Retention or Customer Churn

As it seems, Customer Churn is a popular metric in Customer Experience Management. Most Customer Experience (CX) professionals talk about it. But as per NPS & CX benchmark report 2018, only one-third of companies track Customer Retention Rate.

In simple words, Customer Churn is the proportion or % of customers who have left or discontinued using the organization’s services as against the total base of active customers.

Customer Retention is just the inverse of Customer Churn Rate. (1/Customer Churn Rate)

Apparently this looks straight forward, but in reality, there are many scenarios such as non-recurring business models, businesses with lock-in periods & without lock-in periods, pure subscription models, etc. Hence calculating Customer Churn has been very tricky. In fact, that is one of the reasons for organizations to not calculate Customer Churn. There is a separate resource paper on “How to calculate Customer Churn Rate?”

There are no universal benchmarks for Customer Churn Rates, but there is data available by sectors. However, there is no such data available for India centric businesses.

I have found that base-lining historic churn rates is a better way to assess the efficacy of Customer Experience (CX) initiatives. So, lack of data for bench marking across industry shouldn’t be of any concern.

Customer Churn Rate is a very good metric to know effectiveness of Customer Experience Strategy.

A variation of Customer Churn Rate is the Revenue Churn Rate.

Revenue Churn Rate

Revenue Churn Rate reveals how much revenue was lost in a given period. This is a very useful economic indicator of customer loyalty in subscription based business models.

In simple words, if $ 10 K is recurring revenue of last month and if that has reduced to $ 9 K this month, then, there is a revenue churn of $ 1K. In other words, the Revenue Churn rate is 10% [=(10-9)/10]. We should take into consideration the installed base of customers and shouldn’t add new acquisitions to current month. The simplest version of this formula ignores customers who have upgraded. However, the refinement to this formula is not covered here and will be dealt with separately.

Revenue Churn Rate is as good as Customer Churn Rate for subscription business, except that downgrades would impact Revenue Churn Rate but not the Customer Churn Rate.

CES (Customer Effort Score)

Customer Effort Score is not a very popular metric in India. Even globally, only 15% of organizations use this metric. I would say that it is one of the most under-utilized metrics by Customer Experience Management fraternity.



Did you know that CES has higher statistical correlation to both repurchase and increased spending rates than Net Promoter Score (NPS). That means, it is a better metric to predictive repurchase and spending behaviours than NPS. In today’s scenario, customers are genuinely busy and anything that can make their life easy is a natural choice.

For example, all of us would prefer using a web or kiosk check in facility rather than stand in check-in queue in the airports. Thus reducing the customer’s effort and helping the customer ‘Get the Job Done’ can drastically increase brand consideration and preference.

CES (Customer Effort Score) is measured through a single question like NPS but with a 5 point scale. Another big advantage of Customer Effort Score (CES) is that the same question can be posed after every interaction or transaction as it makes sense to find out if the customer found it effortless to transact.

Thus these are 4 most important top line Customer Experience metrics (CX metrics) that every organization should track.

Of course, there are so many other metrics such as Service Levels, Turn Around Times, Complaints %, etc that can be tracked. All these are lead measures, which can help in improving the performance of the 4 lag measures or outcome measures.

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