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Customer Satisfaction score, also known as CSAT, is a key performance indicator used by organizations to identify customer satisfaction levels after a specific interaction, or in regard to their overall experience with the company. CSAT can prove to be a strong indicator of short-term customer loyalty and customer retention, and helps organizations understand customer sentiment and expectations.
The data you require to calculate your CSAT score can be obtained through CSAT surveys. CSAT surveys usually take the form of single question surveys that ask a variation of the following question:
“How satisfied are you with your experience with us today?”
This question is followed by a five-point Likert scale, with the following categories:
Once you’ve obtained the responses to your CSAT survey, you can use the following formula to calculate your CSAT score:
CSAT (%) =( Number of satisfied customers*Number of Survey Responses) x 100
*Number of satisfied customers = the number of respondents that selected a score of 4 (satisfied) and 5 (very satisfied) in the survey.
The higher a company’s CSAT score, the better. However, there is no particular benchmark that defines a good CSAT score across all industries. This is because what is considered “good” will vary significantly by the type of industry you are a part of.
The industry benchmark for a CSAT score will dictate whether your CSAT score is good or not. For example, according to the American Customer Satisfaction Index (ACSI), the CSAT benchmark for the American airline industry is 75%. Therefore, if an American Airline has a CSAT score of above 75%, they have a good CSAT score. However, if their CSAT score is significantly below 75%, they have a bad CSAT score.
The American hospitality industry has a benchmark of 69%. Hence, while a score of 70% may be considered good for an American hospital, the same score would be considered bad for an American Airline.
Net Promoter Score®, or NPS® , is a metric that is used to measure long-term customer loyalty. It does so by asking customers how likely they are to recommend your product or service to others. Similar to CSAT, NPS® surveys also usually take the form of single question surveys.
Unlike CSAT, which is expressed on a scale of 0-100, NPS® scores are expressed on a scale of -100 to 100. A negative score indicates that the company has more detractors than promoters, and a positive score indicates the opposite.
Which to measure: CSAT or NPS® ?
CSAT and NPS® serve different purposes. CSAT measures user satisfaction and short-term customer loyalty, whereas NPS® is a measure of long-term customer loyalty.
Therefore, when choosing which one to measure, it is important to first clearly define what you are trying to measure. CSAT would be more suited to your needs if you are trying to understand how your customers feel about a specific product, service, or interaction. However, if you want to measure customer loyalty based on their feelings toward the entire customer journey, then NPS® is the better option.
Some of the most widely used customer satisfaction metrics are:
CSAT scores can vary significantly by industry, however, a score above 75% is typically considered good across most industry types.
Once you’ve received your CSAT survey responses, the following formula can be used to calculate your CSAT score, which is expressed as a percentage:
CSAT (%) = (No. positive responses / Total no. responses) * 100
A few reasons why Voxco is your best bet to conduct your CSAT survey:
With Voxco’s centralised survey authoring, you can create surveys and send them across multiple channels without the need for reprogramming for every medium. As you can connect with customers over a wide variety of channels, you can maximise your survey response rate.
With Voxco, you have access to existing templates created by our team of professionals. This includes a CSAT survey template, which you can easily customise to your needs and deploy across channels.
Voxco’s powerful and dynamic dashboards efficiently analyse survey responses for you and present visual stories of the data collected. This makes it easier for you to identify trends and patterns, and to extract actionable insights from the data.