Fashion retailer reduces product returns by 20% with Audiens

Serial returners were a £1m problem for this well-known fashion retailer. They classify serial returners as customers who return products up to three times a month. This creates significant processing and restocking costs.

Many returns are genuine — with customers choosing the wrong sizes, or over-ordering due to indecision. But others were regularly taking advantage of the retailer and its returns system to ‘rent’ outfits for free.

The challenge:

Increase the retailer’s profits by reducing customer returns and associated costs, while improving the customer experience to drive customer loyalty.

The approach:

Audiens identified three serial returner customer personas:

1: Misfitting: Unsure of which size to buy. Orders a range of items to try and returns the ones that don’t fit.

2: Undecideds: Not sure what they want. Routinely orders similar products with slight variations in color or style.

3: Free rentals and Instagrammers: Wants a new outfit every week for events or social media, without having to pay for it. Repeat orders for clothing and accessories ahead of a weekend, only to return them the following week.

Audiens created audience segments based on these personas from retailer’s customer data. We also provided behavioral insights for each persona’s customers and the retailer updated its CRM and ecommerce system to record them. This gives their Customer Care teams more information on each customer and their usual purchasing behavior. Handy information to have if a customer gets in touch for any reason.

Using SMS and email, the retailer created personalized campaigns for the Misfitting and Undecided customers with suggestions and offers based on how they usually behaved and purchased.

To help Misfitting customers, the retailer provided more size and fit information e.g. which style’s and brand’s sizing is roomy, which are form-fitting or run small etc. After confirming a customer’s size with a successful purchase that’s not returned, the retailer can now make future recommendations of brands and styles that are less likely to be returned.

Undecided customers were sent personalized brand and range recommendations to help them make buying decisions and offered subscription products and personal shopping experiences for extra reassurance.

Reducing the number of Free rentals and Instagrammer purchases needed a different approach. The customers who regularly purchased but always returned were first warned and ultimately blocked from purchasing.

The results:

Key Stats:

– 20% product returns

fewer customers returning products

+ £1m savings

Reduction in returns admin cost

The retailer’s weekly returns fell from over 35% to under 29%, saving in excess of £1 million per year.

Customer engagement, repeat purchases, and brand loyalty levels all increased.

Next steps:

The retailer is continuing to extend its customer personalization capabilities including recommending products based on previous purchase history, lookalike shopping trends, customer profiles and personal preferences. This also includes automated size recommendations based on a customer’s returns history.

“Identify struggling customers from those abusing the system and respond appropriately. Choose a tougher approach for some, without compromising on experience for other shoppers. Uncertain customers are better supported by personalized marketing communications.”