# A tighter grip on your returns process with these smart metrics

You've probably calculated your shop's return rate before. This handy metric provides insight into the proportion of all sales that are returned by customers.

Using metrics such as the return rate is an ideal way to tidy up the jumble of orders and returns. They make numbers clear and easy to compare over different periods, products and customers.

## What's a metric?

A metric is a quantitative measurement of a certain activity. Within the e-commerce world, an endless amount of metrics can be calculated, such as the performance of an online store, the conversion percentages, the number of abandoned shopping carts and the known return rate.

Metrics often go together with KPIs (Key Performance Indicators). KPIs are indicators of a company's planned success or progress. For example, by drawing up the next KPI, the metric used (the return rate) becomes even more useful:

"By 1 January 2022, the return rate must have dropped by 10%."

## 6 metrics for making the returns process measurable

Although most people probably think directly of the return rate in the returns process, there are many more useful metrics to calculate that can help optimize the returns process.

The following six metrics are easy to calculate and offer insights that almost every online store can use:

### 1. Return rate

In this article we cover some smart but "lesser known" metrics, only we still can't leave out the return rate from the list. After all, it gives a good *overall* picture of the number of products returned compared to the number of products sold over a given period.

The return rate is easily calculated by **dividing ****the ****number of returned orders in a given period by the total number of orders in the same period of time.**

The value is especially useful for comparing multiple time periods. If, for example, you calculate the return rate every month and see that it is continuously increasing slightly, then this probably means further research is needed. In this case, you will have to look in to possible improvements within the returns process and/or the sales process.

Unfortunately the return rate has one disadvantage: the metric is very general. Keep in mind that a return does not necessarily have to be something negative. Some returns result in exchange actions, sometimes even with a higher value than the initial purchase. Such details are unfortunately not taken into account in using return rates.

### 2. Exchange rate

To solve the above problem, several metrics can be calculated that give extra insight in the way a return takes place.

An example is the *exchange rate*. It is calculated by **dividing the number of items exchanged over a given period by the number of items returned during the same period. **

A high exchange rate can mean several things. First of all, an exchange is better than a request for a refund. A higher exchange rate can therefore be a good sign. However, when it relates to a specific product, in most cases this indicates a problem. For example, this could mean the sizes are not right and customers often order the wrong size.

### 3. Refund rate

If you didn’t manage to convert a return into an exchange, the customer will probably ask for a refund on a return.

A high *refund rate* usually means that a product was disappointing. For example, it was damaged, of poor quality, did not look like the picture, or simply did not meet expectations.

Many refunds on a specific product is therefore often a reason for online stores to reconsider the sale of this product or look for ways to sell it in a different way.

The refund rate is calculated by **dividing the number of refunded orders in a given period of time by the total number of orders in that period of time. **

### 4. Retention rate

The goal of returns process optimization is simple: keeping the number of satisfied customers and the amount of turnover as high as possible.

Many online stores therefore choose to give a special offer to customers when registering a return. This could be a credit with which a new product can be purchased immediately, even before the initial product has been returned to the online store.

A nice way to calculate to what extent such actions work is to calculate the *retention rate*.

You calculate the retention rate by **dividing all return requests that result in a new sale by the total number of returned orders in the same period.**

Is the retention rate going up? This means that more customers choose to make a purchase instead of requesting a refund.

### 5. Perfect order rate

A common reason for return is the occurance of an error during the ordering process. This could be a delay in shipping or a defect in the shipped product.

The more errors, the greater the chance of having dissatisfied customers and returns.

In order to measure how many errors occur within a certain period of time, it can be useful to *calculate the perfect order rate*. This metric shows to what extent the ordering process is flawless. Does this rate go up? Then it's probably time for an improvement.

The perfect order rate is calculated by **dividing the number of order errors by the total number of orders over the same period of time. **

### 6. The No Fault Found Rate

Not all returned products can be sold again at the initial price. Is the product damaged or can you see that it has been unpacked before? This raises the chance that the new customer will not like his or her order.

Many returned products are therefore sold, donated or disposed of at a discount. Unfortunately, this often results in a loss for the seller.

The *no fault found rate* indicates the extent to which returned items are received back in perfect condition, allowing them to be sold again for the new price.

The no fault found rate is calculated by **dividing the number of flawlessly received returns over a given period of time by the total number of returns received over the same period of time. **

Is it noticeable that the number of flawless shipments is going down? Then, for example, we can try to improve the packaging or add special instructions for the customer.

## The data dashboard

The above mentioned metrics may seem difficult to keep track of, but fortunately that is not the case. More and more online stores are using smart return software. With this software, returns are registered by the customer directly online, after which all details regarding the shipment are displayed in a data dashboard. This data includes return numbers, the number of exchange actions, the number of customers that take advantage of special offers such as credits, and any errors that occurred during orders or returns. In other words: it contains all the data you need to calculate the above metrics. And on top of that, in most cases the dashboard can calculate the metrics for you.

## Interested?

Are you interested in using handy return software with a complete data dashboard? Or would you like to brainstorm about the use of the above mentioned metrics? Then Returnista is the right place for you.

Returns are no longer a pain point with the Returnista software. Increase customer satisfaction and reduce your costs with the help of an attractive returns portal and a complete data dashboard. Do you want a nice portal in the style of your online store, just like Decathlon, Loavies and ASOS? Ask for a demo on our website.