Innovative Retailer – Dressipi


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The Name: Dressipi

The Place: Well, as so often in innovative retail it is an online set up, but there are reports of around 14 people working in an office in Great Portland Street, London.

The story: It’s women, it’s fashion, and it’s technology. But not necessarily in that order. In fact I would put the technology first. Dressipi would/could not describe itself as a retailer for the very good reason that it does not sell any clothes, and the founders refer to themselves primarily as technologists but this company is changing the way fashion retailing online is going so they’re in this column and that’s that.

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Sarah McVittie, co-founder, Dressipi

Alright. Calm down. I’m sure it’s fine. Let’s start at the beginning: Okay, founders Sarah McVittie and Donna Kelly came to the conclusion around 2010 that a business space existed for a fashion service that didn’t just push products at you but helped you to sift through those products to only show you the ones most likely to interest you. And thus the ‘fashion fingerprint’ idea was born.

So I say mirror, mirror on the wall, find me the fairest black dress of them all… And instead of being faced with visiting tens of different retailers’ sites and then sifting the stock on each of them yourself, the Dressipi service will give you an instant edit of the styles most suitable for you. And around one million individuals have signed up so far.

Like it. How is my fingerprint taken? Well, by doing a simple survey that will eventually assign you around 120 metadata points. It’s all about algorithms.

Algorithms? Meta-whatsits? Sort of like 120 things about you, your vital stats, preferences, attitudes, favourite colours, occasions etcetera. Using those the tech can then scan what’s out there and provide the closest match.

Whatever. When do I get to see the dress? First all garments also go through a tagging and labelling process which assigns around 50 features to each piece, things like colour, texture, sleeve length.

Style profiles  must haves(1)

Dressipi style profile

Yeah. Is the dress coming anytime soon? I’m trying to explain the genius of the system to you. Then what McVittie calls the ‘dating site for clothes’ comes into play and pits these two sets of data against each other to come up with…

My dress! It’s a beautiful idea: There are many beautiful things about Dressipi. The first is that it is free to the consumer.

Wait, they do this out of the goodness of their hearts. What kind of a hard-nosed business decision is that? Listen, there are two parts to this business. A B2C part and a B2B part which run in parallel with one another. Everyone is very keen to keep the personal styling service free for now. But the other half of it is the white label service Dressipi provides for some of the UK’s major retailers and I think you will find that this is where the lucre is.


Examples? Marks & Spencer, Boden, Brand Alley, Debenhams, and a well-publicised partnership with eBay to integrate with their fashion gallery are just a few.

And why would buy tadalafil online canada Debenhams be interested in giving a free style advisor service to the customer? Duh! Because of the bane of every clothing retailers life – the returns. Using this technology has a drastic downward impact on return rates. Plus they can use the invaluable information customers are giving them to work out why those tops with the silly puffy sleeves are still sitting on the shelves at Sale time. The customer engagement is so strong that by solving the consumer’s problems by default it helps the retailer.

Any other advantages? Yes indeedy. Higher sales. Let me describe the typical customer to you. She is very ABC1, 30 to 45-years-old, a busy career woman, probably urban, and with no time to waste. Completely different to yourself.

Yes, I see that: Doing a fashion fingerprint makes them instantly more fashion confident and here comes the counter-intuitive bit. People who don’t know what looks best on them dither about, browse endlessly and then eventually buy absolutely nothing. Women with the confidence of stylist advice behind them get out the credit cards and shout “hey-ho here we go”. According to McVittie they will purchase three times more.

Crumbs: The average spend after a Dressipi shop is £120.

Lawks. Question though – wouldn’t it be possible for a canny retailer just to pay Dressipi to promote their clothes? Wash your mouth out. It only works if it is completely independent. There are no affiliates, no preferred suppliers. The B2C part is exactly that – a consumer site and it grows largely through word of mouth. Dressipi does not do any marketing yet still they grow very quickly.

There must be loads of others doing this sort of thing though: The fashion technology space is, as they say, “very noisy” but this is probably the only outfit combining all three components of data/fashion/heavy-technology. Clothes buying is an emotional purchase so the technology needs to be clever to reflect that, which is why a tech person doesn’t go near clothes labelling without a stylist holding their hand.

Sweet. So what’s new then? Other retail partnerships are always developing, customer friendly apps such as the size-finder which caters for the problem that a size 12 means something completely different from one retailer to the next. There is interest in the technology from most big markets but obviously geographical tweaks are required. Apart from that, it is personalised outfits that are the next big thing, along with a fully portable service which provides an in-store connection between the online offer and the in-store multi-channel offering.

What? It means the shop assistant will have all the fingerprint info on a tablet and be able to help customers on a much more personal one-to-one basis.

Oh right. I would now advise getting a big name to provide investment gravitas: Amateur. They are way ahead of you. No less a personage than Sir Stuart Rose is Chairman and has been providing aforementioned retail weight since 2012.

Oh. Does he have an algorithm: I couldn’t possibly comment

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