Almost half of the clothing items bought on online in the UK is returned, mostly due to incorrect sizes. This is a huge environmental problem. And many are trying to solve it, as I adressed in a recent post.
Now, online fashion retailer Asos is introducing a new online sizing tool that attempts to take a step in this direction too. Their fit assistant combines machine learning with a visual questionnaire in order to take into account a wider range of body types and shapes. That is, not only height and weight, but bust size, belly shape, hip width, age, and also what kind of fit the customer is looking for.
Then they blend this customer data with recommendations from the customer’s previous purchases and returns, along with what other customers with similar body types have been happy with.
That’s lot of data though, and quite personal too, which means you have to be ok with giving away all that to a retailer.
The question is also if getting the fit right the first time, necessarily helps lower returns (and thereby the number of harmful transports). Maybe we’ll just shop even more? Worth thinking about.
Screen shot from Asos Fit Assistance.
AI as a creative tool? The idea is getting more and more attention among labels and designers, as I have adressed in previous blog posts. The other day the italian online retailer Yoox (who is a part of the Net-a-porter group) announced a new, yet unnamed label. The new collection will be informed by data, but still be designed by the human creative team, The Current Daily reports.
“By using the data, we think the creative team can interpret better our customer needs going forward, Federico Marchetti, CEO of the Net-a-porter group, said when speaking at a Wired Smarter conference on Monday.
The YNAP aren’t newcomers when it comes to AI. Their logistics center is already fully automated and they have also given their personal shoppers an AI tool to help them give better advice to customers.
Using it in the creative process though, opens up for concerns about what it does to creativity.
Do human creativity and machines really mix? Marchetti wants to explore that. Maybe in the future we will see labels like ”Made in Italy” replaced by ”Made by humans”, he suggested.
“Man is about emotions. It’s about beauty. It’s about feelings. The machine is about speed, information power and the future. Can these two worlds co-exist? We must make choices to strike the right balance.”.
Speaking about L’Oreal – the company actually showcased one of their existing beauty tech services at SXSW the other day. A couple of years ago, their Innovation Lab developed a dispenser using artificial intelligence to mix foundation specifically adapted to the user’s skin. What it does, is that it collects data from three points in the users face and this data is picked up by an algorithm that identifies the levels of cyan, magenta and yellow in the customer’s skin.
The company actually debuted this tech exclusively at store chain Nordstrom in 2016, but according to Decoded Fashion it is still the most advanced innovation out there as of yet.
And foundation shades continue to remain a hard nut to crack for consumers. Although many brands provide a much wider range of shades these days, it can still be tricky to find the absolute right shade for your individual skin tone.
So I imagine that using data to come to terms with this might be worth quite a lot.
Oh yes, it looks like our selfies are about to get to much better in the near future. Amazon is now adding a voice controlled, standalone selfie camera to its AI assistant Alexa. Echo Look has a lot of the same features as the last one, but with four LED lights, a depth-sensing system that blurs the background, and the possibility to take videos to get the best view of your outfit from every angle. With the function ”Style check” it uses machine learning to compare outfits and give style tips. The more you use it, the smarter it gets. The camera is not yet available to the public, but when it does it will sell for about 200 dollars, according to Fashion and Mash. Wanna see for yourself how it works? Take a look at this promo video.
Oh yeah, retail tech is certainly happening now. And proof of that is that tech giant Intel is just about to invest 100 million dollar in retail tech over the next five years, according to Fashion and Mash. The idea is to create a platform based on IoT solutions that’s supposed to bring efficient and personalized shopping and also involve virtual reality and artificial intelligence experiences. Sound exciting indeed.
Meanwhile Rebecca Minkoff is launching a venture capital fund to find talent and resource in the tech startup scene that can benefit them and also the industry at large. And Rebecca Minkoff is certainly no stranger to retail tech solutions. They introduced the first connected fitting room in their flagship store in 2014 and recently also added a self-checkout service.
Kan man skaffa sig en perfekt garderob med ändlösa stylingmöjligheter baserad på endast 40 plagg, inklusive skor och accessoarer? Ja, det hävdar Epytom, en stylingservice som använder artificiell intelligens och big data för att erbjuda personliga stiltips via Facebook Messenger. Tjänsten är en chatbot, alltså en datorgenererad concierge som du alltså kan konversera med via messenger precis som du gör med vänner och bekanta. Baserat på vilken kroppstyp och färgpreferenser man har, får man sedan outfittips för en hel vecka som utgår från en standardiserad capsule wardrobe, alltså en sorts basgarderob med vad jag gissar är etablerade klassiker. Man slipper alltså tänka på vad man ska ha på sig, vilket ju kan vara kanon om man behöver vara välklädd varje dag men varken har tid, lust eller intresse nog för att engagera sig. En annan fin sak är att det sannolikt gör att man slipper shoppa så mycket, dels på grund av att man troligen redan har ett gäng av dessa 40 plagg, dels att de inköp man kanske behöver komplettera med, blir mer genomtänkta.
Känns klart lovande om man är beredd att koppla den till sin Facebook, vilket jag måste erkänna att jag tvekar att göra. För hur mycket av mina data behöver den egentligen för att kunna leverera tjänsten på ett tillfredställande sätt? Hur mycket kan jag styra själv? Alla dessa frågor. Och så avstannar processen trots att jag håller på att gå åt av nyfikenhet.
Foto: Screenshots from Epytom Insta