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Measuring customer loyalty: How loyal are your customers?

We know that loyal and engaged customers are among the best brand representatives in the company and act as ambassadors for your company in their social circles. But how can you measure customer loyalty and find out how loyal your customers really are?
By the way, you can find the most important key figures on this topic in our article "Measuring customer loyalty".
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Measuring customer loyalty: The basics

A common mistake is that loyalty is only measured in terms of sales. However, there are more efficient ways to measure customer loyalty. The ultimate measure of loyalty is the share of purchases in the respective category. In the grocery store, it is the share of the refrigerator. In the clothing industry, it is the share of the closet. And in the restaurant industry, as John Martin - President and CEO of Taco Bell - says, it's the "share of the stomach".

Unfortunately, such information is rarely available at the individual customer level. However, there are alternative measurements: Harvard Business Review has categorized them into three main categories.

1. The intention to purchase again

In the customer relationship, it is always possible to ask customers about their future intentions to repurchase a particular product or service. Although their answers are merely indications of future behavior and do not constitute assurances, they provide valuable insights into future purchasing behavior.

Companies can capture this information by measuring customer satisfaction. This makes it possible to use intentions and satisfaction for analytical purposes.

In industries with long repurchase cycles, the fact that repurchase intent can be measured at any point in the customer relationship is particularly valuable.

Last but not least, the intention to repurchase is a strong indicator of future buying behavior.

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2. Primary behavior

Depending on the industry, companies often have access to information about various transactions at the customer level and can measure five categories that show actual repurchase behavior:

  • Recency

  • frequency

  • Amount

  • Retention

  • Longevity

Although these are important measures of actual behavior, they only give an overview of the overall percentage and are most useful as an indicator of change over time.

They can also sometimes send the wrong message. For example, the credit card industry uses willingness to pay the annual fee as a retention measure. They found that willingness increased, but 'share of wallet', which would be the ultimate loyalty measure, actually decreased.

In this example, recency, frequency and volume of purchase would have been much better measures of loyalty.

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3. Secondary behavior

Customer recommendations, endorsements and word of mouth are particularly important forms of consumer behavior for a company. In most product and service categories, word of mouth is one of the most important factors in attracting new customers.

It is often easier for a customer to respond to the question of whether they would recommend the product or service to others than to the question of whether they intend to buy the product or service again.

Such loyalty indicators obtained through customer surveys are often ignored because they are soft measures of behavior that are difficult to link to subsequent purchasing behavior.

However, since secondary behavior significantly leverages the positive experiences of an individual customer, it is very important to understand what types of experiences generate such behavior.

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Conclusion - Measuring customer loyalty

Customer loyalty should never be underestimated!

In order to be successful with customer loyalty, it is necessary to be able to measure customer loyalty. There are various options available to you for this. Which one is right for your company depends on various factors such as purchasing behavior, industry and competition.

It is best to look at all the different options and select 2-3 that are relevant to you. This will prevent you from losing sight of the essentials due to all the data.

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