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5 Things eCommerce Stores Can Learn From Their Customer Service Metrics

To improve the quality of the customer experience in eCommerce, businesses should invest in customer service software and train support agents. They should also measure the satisfaction of their customers and determine how effective their team is. 

Metrics in customer service help to understand customer preferences, purchasing patterns, support feedback, satisfaction rate, etc. In this article, we’ll discuss the 5 things eCommerce businesses can learn from their customer service metrics. 

Why track and analyze customer service metrics?

track and analyze customer service metrics

Customer service metrics are performance indicators that help to analyze the effectiveness of a store’s customer service team. The common ones include average response times, customer churn rate, customer satisfaction rate, and so forth. They help to discover those areas of improvement and provide indicators on how to optimize the customer experience. 

Some customer support metrics can help businesses understand the reasons why prospects aren’t buying, why customers aren’t making repeat purchases, and why they’re getting little to no referrals from current customers. This helps to identify problems early and fix them before it’s too late. The happier customers are, the better their reviews are.

Top 5 customer service metrics to track 

It’s not enough to implement great sales and marketing strategies. You should seek to understand how customers perceive them and their impact on business. These metrics allow you to know how good a support team is, what customers think about a business, and how easy it is to engage with a brand. Below are 5 important metrics that can help eCommerce stores learn more about their business. 

Average revenue per account (ARPA)

The ARPA metric measures the revenue generated by each customer. It can help stores determine products that have high or low revenues. It can also provide insight on who the high-value customers are and their product preferences. 

Such insights can help promote personalized upsells and cross-sells to customers. B2B and eCommerce businesses can use ARPA to calculate the revenue gotten from each user or customer over a specific period. 

The formula for ARPA is: Total Revenue / Number of Users 

From there, choose a particular period (either month or year) and calculate using the exact numbers for that period. 

Customer Effort Score (CES)

The CES metric is used to measure the ease at which a customer gets a question answered, a problem resolved, a request fulfilled, or a product shipped or returned. In the Six Pillars of Customer Experience, customer effort is a strong predictor of loyalty. The less effort a customer uses to engage with a brand, the more loyal they get. 

Online stores should understand the customer’s experience when trying to place an order or initiate any form of transaction. With customer service apps, eCommerce businesses can put CES surveys on specific contact points within their website, app or support channels. It indicates how convenient it is for customers to perform any purchase action or make use of your product. 

The formula for CES is: (sum of the CES survey scores / total number of respondents). 

Ideally, a business would ask a question like, “How easy was it for you to use the product or how much effort was needed?”. From there, use the scores and respondents to calculate a CES.

Cross-and upsell conversion rate

Although their major tasks are to reply to customer queries and resolve customer support tickets, the support team can also sell to customers. You just have to train them on how to upsell and cross-sell relevant products or services. 

The upsell rate would help to determine the percentage of customers who bought a higher-end product or service package after being encouraged. While the cross-sell rate shows the percentage of those who purchased related products or services after it was suggested to them. 

Online retailers would need to know how many times cross- and upselling to customers resulted in a successful sale. Such insights can indicate which products are better to cross-sell and upsell and what type of customer is likely to buy them.

The formula for cross-sell rate: (Total number of customers who purchased the cross-sell product / number of times it was suggested) × 100. 

The formula for up-sell rate: (Total number of customers who purchased the upsell product / number of times it was suggested) × 100. 

Repurchase rate

The repurchase rate measures how many buyers return to purchase from you again. It allows businesses to determine the factors that are stopping customers from buying another product or service. For example, 76% of customers would switch to another brand after one bad service experience. 

This is different from the customer retention rate which measures how many customers a company retains in a specific period regardless of whether they purchase again or not. The repurchase rate tells you the percentage of customers who make another purchase after the first one. 

To calculate the Repurchase rate: (Total customers with more than one purchase / total number of customers) 

Make sure to select a particular period and use the required numbers to calculate the repurchase rates.  

Time to Value (TTV) rate

The TTV rate measures the time it takes for customers to derive value from your product or service. A shorter TTV shows that customers can use a product without many issues. The shorter the TTV, the happier customers are.

When customers can achieve their goals much faster, they are more likely to stick with your brand. Online stores need to know the areas where customers can be struggling. From there, create help articles or make sure that agents are available. 

To calculate the TTV rate, define what value means to a customer who’s using your product or service. Next, determine the start point e.g. time of purchase, first onboarding email, etc. Then, pick the endpoint e.g. when the customer has achieved their first outcome. 

The formula for the TTV rate is: the time when the expected value was achieved; the time when the customer started. 


Customer support metrics can be used to measure how efficient the eCommerce customer support staff is. But they can also help to understand what’s driving customers to patronize a brand. Note that customer service apps can make internal processes better and automate mundane tasks. 

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