Amazon, Etam: the dressing room comes home
- In the United States, Amazon launches its Prime Wardrobe service
- In France, Etam announces its “Try at Home” service for June
The hallmark of a dressing room is that it is a quiet and intimate space in the store to allow each customer to try before they buy. And why shouldn’t this phase of reflection move to the customer’s home? Each with their own formulas, Amazon and Etam are making progress on the subject.
AMAZON Prime Wardrobe
Last week, Amazon US has extended the Prime Wardrobe service, which started in Last june in beta. Prime Wardrobe is a “try-before-you-buy” service that allows you to try on clothes in the comfort of your own home before deciding to buy them.
The principle :
- Prime customer selects 3 or more items on Amazon.com (clothing, footwear and accessories)
- He receives them at home and has 7 days to decide
- Returns unwanted items using a pre-filled UPS return label
- He settles retained articles online.
Shipping and returns are free. The delivery time may be a little longer than the 2 days guaranteed to Prime Members.
On the brand side, the products eligible for Prime Wardrobe are both Amazon own brands and big names in clothing such as Tommy Hilfiger, Adidas, Guess, Levi’s, Calvin Klein, Nine West, etc.
Amazon is only endorsing a practice that already exists in retail (“zapping” the dressing room box knowing that you can easily return a garment that does not suit) but pushing the concept further with two facilities:
- No money to advance before deciding
- The return is extremely easy.
Launched in beta test last June, Amazon has amended slightly the conditions in November: still reserved for Prime members, the service is limited to 10 items, with a reduction linked to the purchase amount (20 dollars reduction for an order of 200 dollars or more, 50 dollars for 400 dollars or more ).
This “try-before-you-buy” practice should quickly become widespread in the clothing sector. Asos, Topshop and others have launched their own service, available on their app.
The bedroom becomes a dressing room
The phenomenon is not new, but it is growing: the classic model according to which you pay for your purchase before receiving it at home is being called into question. Among the significant players:
- Stitch Fix, first site for recommendations and personalized box deliveries (5 clothes and accessories. No store, no subscription, registration required). Founded in 2011 in San Francisco, Stitch Fix broke into the Nasdaq last October. The historically profitable company achieved $ 977M in sales in 2017 and employs 5,800 people. 75+ data scientists and 3,400+ stylists work together – algorithmic models validated by a dedicated advisor – to serve the best selection to each of the 2.4 million active clients.
- Gwynnie Bee (similar model) chose to to provide to other retailers its platform of white label box subscriptions and has already signed with Anne Taylor and New York & Company.
In addition to the service provided to the customer, Prime Wardrobe allows Amazon to acquire a quantity of data, distinguishing the items considered from those actually kept.
Wardrobe is similar in this to the box models. These make intensive use of customer feedback: when paying online for retained items, the customer is invited to give their impressions of the items received. And Customers Respond: Stitch Fix has an 85% response rate. Example of structured and unstructured feadback data: size, price, style, silhouette, quality, opinion on the full experience, wish to receive or not a new package in the future.
This new category of data – between the items that tempt the customer and the items actually kept – (the equivalent of the wearing at the exit of the fitting rooms) will allow Amazon to know that, for example, articles of clothing for children A, B, C, D and E have tried this home in which there is a 2-4 year old girl, residing in a given postal code, but only items B and D were actually purchased. Interesting data to carry out this type of predictive:
- Predictive buying behavior
- Predictive demand (manufacture of clothing and brands to offer)
- Optimization of stock according to demand (localization of items in warehouses)
- Design of new clothes (style, size…).
Etam “Try at home”
Guest of Karine Vergniol in the show Innovate for Commerce on BFM Business, Jonathan Attali, E-commerce and Innovation Director at Etam, announced the launch by June of the “Try at Home” service.
” This service ” Explain Jonathan attali ” allows the customer to place an order on the site, not to be debited, to have 10 days to try and to make a return, either in a warehouse or in an ETAM store “.
The customer who buys lingerie online always wonders if the product will fit her. It is a major brake in this sector. Asked by Karine Vergniol, Jonathan Attali figures at 10-12% the return rate at Etam, all categories of products combined. As in all retail, returns are a real subject at Etam, which today offers 30 days to return its product: “ It is a stock that sleeps outside, that the customer will keep at home for 20-25 days before returning to the store. And during this time, another customer who would like this product does not have it available and will be frustrated. »Explains Jonathan Attali.
Returns are free in one of the 450 Etam stores (where 85% of returns are made).
By offering this new “Try at Home” service, Etam seeks above all to offer the best customer experience and the most practical service to its customers. Along the way, Etam will be able to assess three important elements:
- Is the cash advance to try a product problematic for Etam customers?
- Does this service generate new customers?
- Does this service help to build loyalty?
Another ambition: to collect new data to feed this group which outperform thanks to Digital and Artificial Intelligence.
The correspondant :
Laurence Faguer is a marketer and entrepreneur “go-between” France and USA, founder of Customer Insight.
At the request of French companies, she identifies in person innovations in Digital, Mobile and Retail in the United States, before they are known in France, then helps them to successfully transpose these successful strategies in the US
Laurence is US expert for FrenchWeb who resumes from time to time the publication of articles on her blog.