Ever since Japanese ‘organizing consultant’ Marie Kondo’s consistently best-selling 2011 opus The Life-Changing Magic of Tidying Up de-cluttering has become an international obsession, part of a pseudo-spiritual quest for more meaningful living. And with good reason; according to the UK arm of US weight loss business Weight Watchers there is currently at least £10.5bn of unworn items in Britain’s wardrobes. While part of that figure comes from too-wishful thinking (the extra pounds never shifted, the clothes that never fit) there’s also the more significant story of too much stuff presenting a simple lack of visibility, clouding our judgement regarding what we need or want to buy next. The result is a vastly unsatisfying cycle of irrelevant things and increasingly flabby shopper-brand relationships.
Reclaiming the peace of mind that comes with neither wasting precious resources or your own cold hard cash is what London-based Save Your Wardrobe Co-Founder Hasna Kourda, an economics and corporate strategy graduate and a former luxury fashion sales assistant, is banking on: “When I worked in retail I saw a massive loss of trust between consumers and brands because people constantly felt they were being given the hard sell, not serviced according to what they really wanted or needed. Part of the aim of this concept, which fundamentally remedies the fact most people don’t even know what’s in their own wardrobe, is to re-build loyalty and create relevancy, which will raise sales figures if not numbers of ‘things’ sold.”
The app, which is free to users (brands will pay for the data/insights it delivers) is rooted in the building of an entire virtual wardrobe. This happens in two ways to encompass both new and existing items. Firstly, using advanced computer vision tech users can photograph their existing clothing which the system will then categorize, in most cases even establishing the brand. Secondly, users can allow (ostensibly via Google GOOGL +0.21%permissions) their digital receipts to be automatically read. Assuming the brand in question is affiliated to SYW via an AP the system will recognize the SKU, allowing it to register every detail including size, color, and date of purchase. A 30-day cooling period will adjust the data should items be returned.
Alex Holyoake / Unsplash
Computer vision tech will recognize and categorize items (Credit: Alex Holyoake).
In order to avoid the system becoming nothing more than a backwards-looking personal fashion filter bubble -rendering it much harder to offer suggestions or predict new influences – SYW is currently working with vast fashion shopping network ShopStyle’s database of brands so users can also browse a vast number of brands to create product wish-lists. Later, it will also tap into users’ social media activity to flesh out their profiles still further.
The system will also be connected to users’ calendars, so it knows, for example, when they’re due to go on holiday, and to where, or when they have a job interview coming up and will send them product recommendations. Users have a dashboard showing both their curated selections of clothing for various occasions (“playlists of outfits”) as well as their full digitized wardrobe, generating an enormous sense of control.
For brands investing in the concept as a tool to help them plan, produce, market and/or buy more accurately, the critical factor is that it will provide a window onto tastes and preferences, grouping users into clusters and micro segments – essentially people exhibiting similar desires, behaviors or attitudes. .
A second layer, devised to take the intelligence offered to the next level, is the introduction of a suite of core services – dry cleaning, repairs, re-sales and alteration – that Kourda believes will spotlight how users feel about their clothing. It will, she suggests, present a kind of longer-than-usual narrative for products, understanding them not as single purchases but an ongoing story that reflects the attitudes of their owners. “This is where online fashion retail has become slightly unstuck,” says Kourda. “It doesn’t present the full picture of searching, buying and aftercare over time and nor does it tap into the notion of buying mindfully.”
Furthering the notion of a more mindful mode of operating in general, drawing on her own experiences of luxury selling, Kourda believes the app’s success will lie in “assisting not annoying people with relentless alerts. It’s about understanding the key moments. For that reason, we won’t be pestering people by sending notifications [that appear outside the app, on users’ home-screens]. We believe that getting the timing right is what will create a ‘sticky’ system’.” No ads, nor sponsored content affirm a commitment to useful engagement over mercenary marketing.
As with any algorithm/machine learning based system the more parties involved and the more data is accrued the more pertinent the suggestions. “There is an opportunity here for real relevancy, rather than creating product and then working out how to sell it to people,” says Kourda. “We want people [customers and brands] not to think of store as cash machines chasing money but places for amplified experiences and connections. Customers want to feel ‘seen’, they actively expect it.”