Customer Satisfaction (CSAT) – What It Is, Pros & Cons, and How to Measure It
Companies have long recognized the need for customer feedback, but the focus on customer satisfaction, while always a priority, shifted into high gear during the pandemic. Consumers’ trust and loyalty were put to the test, and many brands responded with flexible return policies, pricing and change policies.
Customer satisfaction is a metric that matters: Most Americans have decided not to make a purchase because of a poor customer service experience, and it takes 12 positive customer experiences to make up for one negative one. Research by Microsoft found that 90% of people say customer service is important to their choice of and loyalty to a brand.
What is the CSAT Score?
Customer Satisfaction Score (CSAT) reflects how satisfied a customer is with a particular interaction or overall experience. Measured as a percentage – the higher the better – it functions across industries as a key metric reflecting customer service, product quality and the customer experience. In addition, more than one-third of organizations use CSAT to measure their digital customer experience improvement, according to the CMSWire State of Digital Customer Experience 2021 survey.
The Traditional Method of Calculating CSAT: Surveys
For businesses that do not have a full CX or analytics program, CSAT is often measured through customer feedback in the form of a survey question or questions that ask respondents to rate their satisfaction. Businesses use varying methods; some use a ten-point scale to correlate responses to their overall Net Promoter Score (NPS), while others use a five-point scale. One commonly used question is as follows:
Rate your overall satisfaction with the [goods/service] you received:
1. Very unsatisfied
5. Very satisfied
To calculate a CSAT score from the responses, you typically use the two highest values – in the example above, 4 (satisfied) and 5 (very satisfied). The two highest values on feedback surveys have been shown to be the most accurate predictor of customer retention.
Then, you perform a simple calculation:
Number of satisfied customers (those who selected 4 and 5) / Number of survey responses x 100 = % of satisfied customers.
The Pros and Cons of Using Surveys to Calculate CSAT
The CSAT score can give you insight into your customers, their experience with your business, and areas that need improvement, but it’s not an infallible metric – there are pros and cons associated with it.
Pros of using CSAT:
- It’s short, intuitive and simple.
- The rating scale can vary based on the context, giving you the flexibility to use what works best for your audience (e.g. stars, emojis or numeric rating scales).
- You often have high response rates because there are few questions.
Cons of using CSAT:
- The vast majority of customers do not fill out surveys, increasing the likelihood that results are not accurate.
- It has a potential for cultural bias: People in individualistic countries (e.g., the United States, Germany, Ireland, South Africa and Australia) choose the more extreme ratings more frequently than those in collectivistic countries (e.g., China, Korea, Japan and Mexico).
- There can be ambiguity in what a good or a bad score is because of wide-ranging benchmark data across industries and companies.
- It reflects short-term sentiment.
The Modern Method of Calculating CSAT: Using AI Sentiment and Omnichannel Contact Center Interactions
Getting a true measurement of your customers’ satisfaction with your organization requires a big-picture understanding – one that can be far more powerful when survey data is incorporated into omnichannel analytics. Linking all survey data alongside additional predictive metrics in contact center interactions such as sentiment or churn risk allows evaluators to use workflows to narrow down priority customer interactions. By narrowing the focus, supervisors can review a smaller sample of specific recorded calls or chat text to gain a clearer understanding of:
- The volume of at-risk interactions occurring across all customers, not just a sample.
- Whether a customer’s issue is due to broken processes, agent behaviors or product issues – among others.
- Whether the issue requires remediation with the customer or additional agent coaching.
With a more in-depth understanding of customers across all channels of communication, the additional insights gathered empower all roles in the organization to take clear action to improve CSAT. Traditional scoring methods only provide an output – without AI omnichannel analytics to look deeper into the data, there is no way to take action to improve the score over time.
How to Use the CSAT Metric
Measuring CSAT is just part of the equation; what you do with the information and insights you gather is just as important. Here’s how to use CSAT for maximum impact:
- Analyze trends and understand customer expectations: Identify both happy and unhappy customers and pinpoint the factors influencing CSAT. This can help you plan and inform priorities not only for the contact center but also product development and marketing as well.
- Assess CSAT at multiple touchpoints along the customer journey: CSAT is simply a snapshot of satisfaction at a moment in time, so measuring it at different touchpoints can help you uncover pain points you may not have uncovered with a single survey.
- Close the loop: If you receive a complaint or uncover an issue with the product or service a customer has received, respond promptly and try to resolve it.
- Leverage open-text fields: Open text enables you to get more detail and depth, potentially uncovering unexpected insights.
- Share results: Help teams understand where in the customer journey satisfaction levels are highest (and lowest) and how you compare to industry benchmarks. You can also use CSAT to identify opportunities for coaching and improvement.
While CSAT is not the only metric to consider when measuring service quality, it still remains a valuable one – it can tell you a lot about your customers' feelings toward your brand. NICE can help you measure and improve CSAT as well as other metrics that are important markers of service quality, customer loyalty and customer engagement, in an easy and simple way. Enlighten AI leverages sophisticated, purpose-built behavior models that empower contact center agents to understand in real time how their behaviors affect CSAT, while Customer Engagement Analytics lets organizations take interaction data from any source at any customer touchpoint and weave it into an end-to-end customer journey complete with metrics and insights that help organizations understand and better serve customers.