Today’s customer, who is spoilt for choice and looking to maximize value for every product or service bought, is hard to please. Organizations today are pulling out all the stops to understand how satisfied the customer is and what can be done to proactively improve customer satisfaction levels. Loss of customers impacts margins and cash flow. To make good the loss, organizations need to spend 5-10 times more to acquire new customers than to retain old customers. In this environment, the efficacy of the measurement metrics used to gain insights into customer satisfaction gains high significance.

With quick shifts in customer loyalties, companies need to consistently and objectively collect customer feedback for the services rendered and continuously innovate to upgrade service delivery levels. However, before you chose any methodology, keep these questions in mind:

  • What are you trying to measure: Service delivery as compared to a standard, customer retention, the pace of customer resolution?
  • What kind of business you are in: B2B transactions, customer query resolution, retail?
  • How much time can your customer genuinely dedicate to respond to your questions: Less than a minute, less than five minutes, over a few days?
  • How good is the analytical capability of your team to churn maximum information out of the available data: Basic level skills, business level analytical skills, detailed structure involving resources of Black Belt level?
  • How frequently can you ask for feedback: Immediately after the service delivery, once a day, yearly?

To find best fit of Need versus Approach for deciding the measuring metric, you can pick from the following methodologies:

Customer Satisfaction (CSAT): A Widely Followed Methodology

Up to 80 Percent of customer service organizations use Customer Satisfaction (CSAT) to gauge customer experience with the organization. A CSAT survey is multi-dimensional and covers all customer touch points. A higher CSAT score represents a clear state of improvement and the rate of change in customer perceptions for the services offered. It is much easier to pinpoint the reason for customer dissatisfaction through a CSAT survey than by any other method of customer loyalty measurement. CSAT surveys are widely practiced in the industry and your scores provide a good comparative baseline vis-à-vis your competitors.

A widely used framework is the RATER model for measuring customer satisfaction or Servqual, developed in the 1980s by Valarie A. Zeithaml, A. Parasuraman and Leonard L. Berry. CSAT surveys typically utilize the five-point scale ranging from 1 being 'highly dissatisfied' to 5 being 'very satisfied'.

However, there is a basic error in CSAT. It assumes that satisfied customers are loyal customers. Research by Dixon, Freeman and Toman, as reported in Harvard Business Review in July 2010, showed that 20 percent of satisfied customers intended to leave the company and 28 percent of dissatisfied customers intended to stay. Low levels of satisfaction indicate that customers are not confident in the basic viability of your offerings. Good to excellent satisfaction scores simply mean you are competent and as such remain a contender for future business. Low satisfaction leads to attrition but high satisfaction does not lead to retention.

In contact center operations that focus on CSAT measurements, the natural focus is on enriching customer experience and exceeding customer expectations but this generally leads to confusion, wasted time and high costs.

Generally, the way companies focus on low CSAT scores and react to improve things are knee-jerk, quick fix improvements that hurt the organization in the long run. This metric is best used when the focus is on customer churn rather than on customer retention. This approach is best used in a B2B kind of stable environment with longer frequency time. Here a satisfied client over a period of time is most likely to be retained for the future when business volumes are high. Also, the statistical rigor and skill required for data handling is high, since the activity takes place once or twice in a year and information retrieved out of this data can be used to decide the future course of action for the business in the medium- and long-term.

DSAT Scores: High Risks of Error of Judgment

A DSAT score is nothing but the inverse of CSAT where the customer is judged on the scale of dissatisfaction with the service provided. This not being a scale in wide practice leads to confusion in the customer's mind and considerably raises the risk of error of judgment. The output is on the same lines as CSAT and does not provide any better picture on customer pain areas.

Net Promoter Score (NPS): Simple, Easy Way to Measure Customer Loyalty

Net Promoter Score is a customer loyalty metric developed by Fred Reichheld, Bain & Company and Satmetrix. The primary advantages of this method are its simplicity, effective utilization and ease of interpretation of the metric. The judgment of an organization's health in meeting customer expectations and the gaps therein can be derived from one single metric of measurement. NPS performance leaders outgrow their competitors in most industries, by an average of 2.5 times. The key differentiator of NPS is the focus on the practical actionable output of the score as compared to statistical focus of a CSAT study. This provides a quick reference guide for an average employee. The focus is to quantify the potential 'promoters and detractors' for a company and calculate with easy areas in organizational health that need more attention.

However, in 2008 Hayes declared that there was no scientific evidence that the 'likelihood to recommend' question is a better predictor of business growth compared to other customer loyalty questions (for example, questions for judging overall satisfaction).

Also, the validity of NPS scale cut-off points across industries and cultures has also been questioned. In a contact center environment exceeding customer expectations or creating delighters have a marginal impact on customer loyalty as compared to simply meeting the customer's demands.

People who contact a call center are either the detractors or potential detractors. Customer expectation revolves around quick resolution of the issue the customer faces. The likelihood of a customer being loyal to a company is highly dependent on how quickly and easily the issue gets resolved.

An NPS metric provides a high level overview of changing customer preferences vis-à-vis the company's offering. It fails to pinpoint the actionable areas for an organization. The NPS score is ideal where the scope of innovation and creating differentiators is high. The customer needs to be constantly excited and engaged with 'what next'. By tracking the NPS score, a company can understand any change that the customer expects from the organization. This approach calls for weekly data collection. Though it means an additional burden of analytical work, the data allows for easy analytics, resulting in a quick purview of the current state of customer expectations.

Customer Effort Score: Tracking Customer Satisfaction with Call Types

The effort of reaching out repeatedly to get a query resolved through non-responsive contact channels often result in bitter experiences for a customer. Long waits to get through a contact center, navigating through various IVR options and having to repeat the information already provided to the agents cause customer dissatisfaction that creates detractors.

Researchers have now showcased a metric named Customer Effort Score (CES) as a more effective methodology to measure customer loyalty. Scoring is done on a five-point scale where one represents 'Very Low Effort' and five represents 'Very High Effort'. The focus of CES is not only to reduce customer dissatisfaction but also to focus on eliminating the reasons why a customer has to contact the call center. This metric goes beyond First-Call-Resolution where the effort is to just resolve a particular query.

It also prepares an agent to give an objective and clear resolution to the customer, and not a tentative response. Research has shown that this has a high impact on the repeat call percentage for a call center. Also, by doing simple improvements like simplifying the help section of the Website or removing jargons from it reduces the contact center call flow and results in higher customer loyalty.

This methodology judges the customer's experience with an organization from the type of calls and quality of solutions suggested to improve the frontline processes. This not only leads to a more agile, customer-focused and proactive organization but also reduces the cost and effort required to manage and respond to customer dissatisfaction. With a focus on the effort the customer puts in to get a problem solved, CES makes a better measurement metric to gauge customer experience.

The sooner an issue gets resolved, the more likely that a customer will perceive the information provided in the contact center to be authentic and trustworthy, and hence consider service delivery to be effective repeatedly. With high data collection frequency, the low analytical skill requirement makes it an ideal measurement metric for customer contact center kind of operations.

The different methodologies have relevance for various business situations and needs. But in terms of delivering more value to clients in business outsourcing operations, the best combination is to use CES for gauging end customer response and CSAT for understanding the satisfaction level of the client of the service delivery model.

Comparative Chart for Three Methodologies
Focus Area CSAT Framework NPS Framework CES Framework
Delivery Framework To gauge the customer experience as compared to a standard delivery goal To gauge customer retention ability of an organization To gauge customer effort put in to get resolution for an issue faced
Scale Used Likert Scale (rating from 1 to 5) Numerical Scale (rating from 0 to 10) Numerical Scale (rating from 1 to 5)
Questionnaire Type Detailed questionnaire with multiple questions covering all major customer touch points (No. of questions vary from 10 to 40) Single question-based survey but sometimes tagged along with complementary questions (No. of questions vary from 1 to 5) Single question-based survey but sometimes tagged along with complementary questions (No. of questions vary from 1 to 8)
Analytical Focus Statistical rigor Ease of use of metric Ease of use of metric
Key Advantage Ability to differentiate customer experience at various touch points Ability to showcase gap in service offerings vis-à-vis customer expectations Ability to estimate customer effort and identify root cause for customer pain areas
Key Disadvantage Poor in gauging customer loyalty Fixed cutoffs for customer categories not valid across industries and cultures Inability to measure aspects of customer experience other than customer service and other direct interactions
When to Use To understand churn of customers To measure customer experience at company level To captures customer impressions at transactional level

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