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InsightSofa Satisfaction Index (ISI)

A unified methodology for evaluating Customer Experience across different metrics.
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What is the InsightSofa Satisfaction Index (ISI)?

The InsightSofa Satisfaction Index (ISI) is not a metric for collecting feedback, but for evaluating feedback. If you use multiple metrics to determine customer/employee experience (such as NPS, CES, and CSAT), you’ll want to see one overall score that speaks to your overall customer satisfaction as well.
The InsightSofa Satisfaction Index (ISI) can combine the NPS, CES and CSAT methodologies into one number, providing you with a simple and easy to understand indicator of the overall customer or employee experience.
isi index scale
On a scale of 0 to 10, the ISI Index tells you where your company stands in the overall customer or employee experience in terms of ease of use of your products and services, overall satisfaction and customer (employee) loyalty.
The InsightSofa Satisfaction Index (ISI) is most telling when a company measures using all known customer and employee experience metrics (NPS, CES, and CSAT). If a metric is missing, the ISI index still works. It just doesn’t include as broad a view.
The ISI Index therefore shows:
isi index positive

Strongly customer-oriented organization:

Customers are your supporters. They find it very easy to use your products and services, are satisfied with them and are willing to recommend you to their friends.

isi index neutral

Moderately customer-oriented organization:

Customers are happy with your company, but find the ease of use a problem, are not completely satisfied or do not recommend your company as much as they could.

isi index negative

Weakly customer-oriented organization:

Companies with this index have more dissatisfied customers than satisfied ones. They have problems using the products or services and do not recommend the company to their friends.

Thus, the resulting InsightSofa Satisfaction Index (ISI) is calculated as the ratio of supporters and positive customers to the ratio of detractors and negative customers from different methodologies. Finally converted to a scale of 0 to 10.
isi index formula
The resulting ISI Index is then rounded to one decimal place.
There is a correlation between the InsightSofa Satisfaction Index (ISI) and company turnover, although this correlation can be variable depending on the specific conditions, the methodologies chosen to measure customer experience and the context of the company.
A lower ISI value indicates lower customer satisfaction, a higher level of effort that customers have to make to use your products and an overall lower level of recommendation of your company to their friends.
If a firm has a low ISI index, customers are more likely to turn to competitors or not to make repeat purchases from that firm. This can lead to a reduction in the company’s turnover.
On the other hand, a higher ISI value indicates that customers have an easy and comfortable experience when interacting with the company, are happy to recommend it, and overall satisfaction is at a high level. These factors positively influence customer satisfaction and loyalty. They are more likely to remain loyal and make repeat purchases from the company. This helps to increase the company’s turnover.
Benefits:

Simple display:

The ISI index results in a single number, showing a comprehensive view of the customer/employee experience. It’s easy to work with and easy to track trends.

A comprehensive view of the experience:

The ISI index incorporates all the most important methodologies (NPS, CES, CSAT). The resulting company index is therefore the most comprehensive view ever.

Identification of areas for improvement:

By sharing questions in InsightSofa, you can see an overall summary of the factors customers most want to improve, thanks to the ISI Index. This is across all methodologies.

Disadvantages:

It only works with multiple methodologies:

If you use only one measurement methodology for the entire company, then the ISI Index cannot be used.

Lack of context:

Each methodology in itself provides relevant data for the collection for which it is intended. The ISI index generalises the data.

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