3 ways to reduce product returns by analyzing and influencing shopping behavior
Fashion E-commerce has always had a high rate of product returns. For many fashion retailers, up to half of everything they sell comes back to them, inducing high handling costs¹. On the other hand, even slight optimizations in the return rate can significantly increase profitability. According to the founder and former CEO of ASOS, one of the biggest fashion online retailer in Europe, a 1% drop in return rate can increase firms’ bottom line by more than 30%².
As a side product of the intelligent nudge targeting with the behamics AI engine, we analyzed online shoppers’ return behavior in depth based on large-scale purchase data of one of the biggest German fashion retailers. We found some counterintuitive causes for returns, leading to implications to optimize the return rate.
Factors That Impact Product Return Rate—And Factors That Surprisingly Do Not
Our analysis of more than 1,000,000 online transactions between September 2019 and May 2020 shows that the quantity of an order does not necessarily mean a higher return rate. Here’s some quick facts:
1. Number of unique products of the same category ordered does increase the return rate: Orders with more than three products of one category have a return rate that is five percentage points higher than average.
2. Number of unique colours and categories ordered can reduce the return rate. Orders with items from at least three different categories or in at least three different unique colours decrease the return rate by up to 3 percentage points.
Ordering loads of items leads to more returns in the first place. However, these results indicate that a more differentiated view can be useful because there are order constellations that can help retailers optimize their revenue and return rate.
Looking For A Common Thread in Your Fashion Retail Product Returns? Inspiration and complementarity matter
Ordering different unique colours and/or categories can lead to less returns. But why is this?
What we found in the data is that people order for choice and want to select their preferred colour at home. In most cases they end up keeping at least one colour and do not send back all items. Furthermore, the results show many orders with customers keeping even more than one colour whereas keeping more than one size is very unusual. Apparently, customers became inspired by the choice of different colours and liked more than one colour.
Orders with items from different categories were complementary items in many cases, e.g., a jeans and a matching t-shirt. In this case, again, the probability is high that the customer will keep at least half of the order or even more. This is in contrast with a comparable order with the same item in different sizes, where the customer usually keeps not more than one size, if at all.
Three Ways Fashion Retailers Can Reduce Product Return Rates
These results imply interesting implications for retailers to increase revenue while keeping the return rate under control:
First, for fashion brands and retailers, offering products in a relevant range of colours in their online shop can inspire their customers to order and try out different colours. This can even shift customers’ focus away from ordering items in different sizes to getting more inspired by different looks. According to our purchase data, this form of customer inspiration can lead to higher order values, increasing revenue while keeping returns under control and even reduce them.
Second, putting a stronger focus on recommending complementary items, instead of similar items, can also help to reduce returns by increasing the chances that customers keep at least something or even the whole outfit.
Third, an intelligent targeting of persuasive communication based on behavioral science (e.g., via behavioral nudges) can drive shopping behavior towards better-informed and inspired purchase decisions. An example would be shifting demand towards ordering items in different colours and outfits of complementary products.
If you want to learn more on how to optimize revenues while lowering return rates and how behavioral science can help to drive shopping behavior accordingly, then feel free to reach out to us.
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1 EHI (2019): Versand- und Retourenmanagement im E-Commerce 2019
2 Reuters (2013): https://www.reuters.com/article/net-us-retail-online-returns-idUSBRE98Q0GS20131002