The option to return goods free of charge or for a small fee is a significant service for online shoppers. Return options deliver a feeling of “security” for consumers that increases their likelihood of ordering. This increase in potential orders is what most inspires retailers to offer easy returns, but doing so is also simply “good manners.”
However, the reality is that the return ratio is a very significant issue for every online retailer; returns generate high expenses – in terms of personnel, logistics and revenue.
The number of returns varies depending on the product segment. The fashion and apparel sector struggles with particularly high figures – here the proportion of returns is between 25% and 50%. In comparison, “only” 10% of items are returned on average in the furniture industry . Knowing these figures, online retailers should update processes to keep the cost factor of returns as low as possible. In many industries, great efforts are being made in this regard. To start, many retailers are working to identify the reasons consumers return goods, and the corresponding return ratio. These vary from retailer to retailer and from product segment to product segment. However, there are also overarching factors that are worth taking a closer look at.
Does the price influence the return ratio?
In a number of dynamic pricing projects, I have been asked: What impact does price optimization via AI have on the return ratio? People who ask this question are often concerned that the return ratio could increase because AI raises the price level of items. The thinking behind this question is that if an item costs a lot, it may be evaluated more carefully and will be returned if it is not perfect.
In practice, however, the following questions arise:
- Do prices generally rise when they are calculated by an AI? No. Prices that are optimized on the basis of current demand do not generally rise.
- Isn’t it true that ordering a lot and returning some items occurs more often when items are inexpensive? Maybe shoppers are more likely to order a large selection of products when prices are low – with the intention of keeping only the best items and returning the rest.
In order to take a closer look at the influence of dynamic prices on the return ratio, we, alongside our customers, considered our own behavior as online shoppers and found the following:
In many cases, we make our purchase decision before placing an order. This means that we have already accepted the price of a product once we order it. Afterwards, when the product has arrived, other factors decide whether we return it or not. For example, whether the product fits or looks/functions as it was described.
Price influences the purchase decision – but not the return ratio
In the end, it’s first of all clear that price influences the purchase decision. There are numerous studies that confirm this behavior. For example, a survey by Statista shows that price is the factor with the greatest influence on the purchase decision (22%) in online shops. Other factors, such as customer reviews (17%), product images (16%) or product descriptions (16%) are secondary.
But besides of the purchase decision – does price also influence the return ration? Here also a number of studies paint a clear picture: whether the ordered item fits or not is the deciding factor for a return in 58.2% of cases. Customers also frequently return goods if they are defective (41.3%), poorly finished (28.9%) or look different from the description (26.4%).
In a nutshell: Once the customer has made a purchase decision, it is only in rare cases that the price decides whether or not to return the goods.
I was able to confirm this connection in a project I completed with a dynamic pricing customer. The basis for this was a 3-month A/B test, which proved that the return ratio remained balanced and stable in both groups. The use of the dynamic pricing software had no effect on the return ratio.
Nevertheless, a mature dynamic pricing solution should offer possibilities to adjust price calculation very strategically according to the return ratio. Feel free to contact me if you want to know more!