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Customer Loyalty Analytics: Ways To Measure Customer Loyalty

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Customer Loyalty Analytics: Ways To Measure Customer Loyalty

Customer loyalty analytics is metric through which businesses and eCommerce can keep track of customer loyalty towards the brand. And something that can be tracked, can be improved upon.

Loyal customers are the way to keep any business sustainable. And by tracking the right metrics, you can learn how to grow the number of your loyal customers.

In this guide, I’ll be sharing with your what is customer loyalty and will be sharing the customer loyalty analytics that you must track.

Without taking any more of your time, let’s get started.

What Is Customer Loyalty?

Customer loyalty is the emotional relationship between the customers and the brand. The connection between the customer and your brand grows through engagement, repetitive purchases, and a positive customer experience.

It is one of the most critical factors in growing a brand. Loyal customers have a 306% higher lifetime value and 60% of them recommends the brand to their friend and family.

If we talk about profitability, it is seen that a 5% increase in the number of loyal customers, results in a 25% increase in profit.

Customer loyalty analytics are ways and metrics through which you can measure the number of loyal customers and determine how loyal they are. Customer loyalty analytics also helps track your progress in increasing the customer loyal customers your brand has.

Customer Loyalty Analytics That You Must Track

Customer Retention Rate

Customer Retention Rate (CRR) is one of the most commonly used Customer Loyalty Analytics. It is a metric that shows the percentage of existing, who remain customers even after a given period.

It is a very important loyalty metric that tells us that our existing customers are still our customers. The higher your CRR is, the more loyal customers to have.

You can calculate the customer retention rate with the following formula:

(Customers at the end of the period) - (New customers acquired)/(Customers at the start of the period) X 100 = CRR

For example, if they started a month with 100 customers, gained 20 more but lost 10 by the end of the month, your CRR will be:

(110 - 20)/100 = 0.9

0.9 X 100 = 90%

The average customer retention rate for eCommerce brands is 30%, but having above 25% is still positive.

Return Purchase Rate

Return Purchase Rate (RPR) is the percentage of customers who come back to make another purchase. It is powerful customer loyalty analytics that helps us keep track of the rate of customers who place a repeat order.

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Unlike Customer Retention Rate where we remove the new customers from the equation, RPR is a metric that focuses on all the customers.

Hence, gives us a better understanding of how many of the customers are coming back, and actually making a purchase.

You can calculate the return purchase rate with the following formula:

(Number of repeat customers) / (Number of total customers) X 100 = RPR

For example, if you have a total of 100 customers, out of which 60 are repeat customers, the RPR will be:

60/100 = 0.6

0.6 X 100 = 60%

The average eCommerce Return Purchase Rate is 28.9%.

Customer Satisfaction Score

The Customer Satisfaction Score is a direct measurement of how satisfied your customers are with the product and the whole experience of making a purchase.

The important word of the following customer loyalty analytics is the “direct”. It is a score that is measured by requesting a quick answer from the customers that they put in.

You have to ask your customers “How satisfied are you with your experience?” You’ll ask your customers to rate their experience between 1-5 or 1-10.

Because the survey is coming directly from customers, it gives us a good understanding of how satisfied your customers are.

Once you collect a good amount of surveys, here’s a formula to calculate the Customer Satisfaction Score of your eCommerce:

(Number of positive responses) / (Total number of responses) X 100 = CSAT

For example, if you receive 100 responses out of which 75 are positive, the CSAT is:

75/100 = 0.75

0.75 X 100 = 75%

The average Customer Satisfaction Score is 74.4%.

Net Promoter Score

Net Promoter Score is a powerful metric for customer loyalty analytics as it is a score that tells us how likely are the customers to refer us to their friends and family.

And just like the Customer Satisfaction Score, the data is directly collected through the survey.

Here, you have to ask your customers “How likely are you to refer us to your friends and family on a score of 0-10?”

Here, we can segment the audience into 3 groups:

  • Detractors (0-6) - These are the group of people who are satisfied and are likely to switch to your competitors.
  • Passives (7-8) - These are the group of people who are satisfied but not loyal. They may switch to your competitors if they get a better price or experience.
  • Promoters (9-10) - This is a group of people who is most satisfied with your brand and its experience. These are people who will likely refer your brand to their friends and family.

Once you collect your responses, here’s a formula to calculate the Net Promoter Score of your eCommerce:

(Number of Promoters) - (Number of Detractors)/Total number of responses X 100 = NPS

For example, if you received 100 responses out of which 70 were promoters and 15 were detractors, the NPS is:

70-15/100 = 0.55

0.55X100 = 55%

The average net promoter score is 32% and more.

Customer Effort Score

A Customer Effort Score is a loyalty metric that helps in measuring how hard was it for the customer to complete an action. In the case of eCommerce, it could be the purchase or signing up for a newsletter.

While with other Customer loyalty Analytics, the goal is to keep the score high, here the goal should be to reduce the efforts.

This is a direct survey so, you can ask your customers questions like “How hard was it to place an order with us on a scale of 0-10”

Once you collect your responses, here’s a formula to calculate the Customer Effort Score:

(Sum of all ratings) / (Total number of responses) = CES

For example, if you received 100 responses and the sum of all the ratings is 70 the CES will be:

700/100 = 7

Bonus Read

Learning about Customer loyalty analytics is one of the most progressive ways to know which loyal metrics to track. This makes it easy to keep track of the best customer experience, higher sales, and more organic customer acquisition.

With the above Customer loyalty analytics, I am sure you’ll be able to track and grow your customer loyalty starting from today.

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