What’s happening in ‘content commerce’?

Last week I wrote about Grabble and reviewing their app spurred me on to look at other apps in the ‘content commerce’ space. In essence, content commerce is about obtaining revenue from your digital content, irrespective of the form the content comes in (e.g. blog, film, music, etc.). These are some of the content commerce examples I looked at:

The Hunt

The Hunt‘s strapline reads “Style & Shopping” and that’s exactly what you get. Very much image driven, the user can search for fashion and styling ideas. I didn’t find the app the easiest to use, and I wasn’t sure about the ‘return of investment’ I was getting on the effort I had to put in to find a piece of clothing ‘similar to this’ (see Fig. 1 below). I can see, however, that The Hunt does help users discovering new fashion items and sharing these with their friends for input.

Fig. 1 – Screenshot of an exact match for Dark Maroon Nike’s – Taken from: https://www.thehunt.com/the-hunt/dhXw8s-dark-maroon-nike%2527s

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Gilt

Gilt is a member’s only community which offers products from the world’s biggest fashion and accessory brands with discounts of up to 70 percent. I can imagine that Gilt acts as a trusted style adviser in the eyes of its community members and I can therefore imagine its curated ‘top picks’ section to get a higher clickthrough rates than similar sites (see Fig. 2 below).

Fig. 2 – Screenshot of ‘Top Picks’ on Gilt – Taken from: http://www.gilt.com/

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Spring

Spring is another good example of an eCommerce site with a strong curated feel about it. Spring offers an Instagram-like photo feed of products to purchase, with a curated community of brands that includes luxury labels and emerging designers. The collections displayed have been curated by influencers and editors (see Fig. 3 below). Spring has no shopping cart. After users have initially filled out credit card and shipping info, they just swipe beneath an item to buy it. And after users like an item, the relevant seller can send them push notifications.

Fig. 3 – Screenshot of collection on Spring – Taken from: https://www.shopspring.com/

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Product Hunt

Product Hunt is one of my favourite places when it comes to finding out about new gadgets and technologies. The combination of a dedicated community curating the products shown based on votes and related conversations between community members works really well. I know that the good people at Product Hunt are looking to expand into non-tech areas, and it will be interesting to see if and when they’ll be able to build up a community around fashion for example.

Fig. 4 – Screenshot of ‘products’ screen on Product Hunt’s iOS app

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Mumsnet

If we take the definition of content commerce at its most basic level, then I would say Mumsnet is a great example. Mumsnet is a large community and acts a go-to place for lots of mothers and mothers to be. Below example of a page where users can read trike and ride-on reviews as well as engage in ‘discussions of the day’ is a really good example of how you can combine relevant content with eCommerce (see Fig. 5 below).

Fig. 5 – Screenshot of Mumsnet product reviews page – Taken from:http://www.mumsnet.com/reviews/on-the-move/trikes-and-ride-ons

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Related links for further learning:

  1. http://www.practicalecommerce.com/articles/78916-13-Innovative-Mobile-Commerce-Apps
  2. http://www.imediaconnection.com/content/38837.asp#multiview
  3. https://stacksocial.com/
  4. http://www.forbes.com/sites/lorikozlowski/2014/02/05/where-content-meets-commerce-apps-gadgets-and-drones-all-hand-picked-by-humans/
  5. http://www.ebaypartnernetworkblog.com/uk/2014/03/06/ebay-launches-collections-follow-passion/
  6. http://content2commerce.com/agenda/
  7. http://www.econtentmag.com/Articles/Resources/Defining-EContent/What-is-Content-Commerce-80914.htm
  8. https://branch.io/content-analytics/
  9. https://gigaom.com/2010/10/26/419-why-content-and-commerce-is-a-marriage-made-in-heaven/
  10. http://skimlinks.com/features
  11. https://www.shopdirect.com/
  12. http://www.diagonal-view.com/

App review: Grabble

“Grabble: Buy Fashion and Shop With Style” is the tagline of the app on the iOS app store. I’m intrigued by the name of this app and its tagline. Is Grabble like Asos or Net A Porter, or is it more like Thread … Grabble is one of the few apps where I really don’t know what to expect. All the more reason to do a review and see what this app is all about:

  1. My quick summary of the app (before using it)?  I expect an app that will help me buy clothes that suit my style and budget. Fashion recommendations might well be the strongest point of this app; using my data and that of users with a similar style to make relevant suggestions.
  2. How does the app explain itself in the first minute? – When I open the app, I am immediately impressed by the great moving images (see Fig. 1 below). This first impression reminds me of the Audioboom app, I like the aspirational people and stylish items of clothing. There are clear calls to action at the bottom of the screen, making it easy for me to get started. But, at this stage I’m not entirely sure what I’ll be signing up to … a personal fashion adviser, a fashion eCommerce app or a mixture of both? I decide to click on the cross in the top right corner of my screen to see what happens.
  3. Getting started, what’s the process like? – This is good. By clicking on the cross, it seems that I don’t have to sign up straight away. Instead, I just need to indicate whether I want to shop for men’s or womenswear. After I click on menswear, I land on a screen which provides me with more clarity about what the app is all about: “your daily feed of great fashion, beauty and homeware. Every day our team of stylists find the best products online.” I now understand that if I sign up to Grabble, I can expect to receive daily alerts about the latest, carefully curated fashion and style tips. When I click on “next” at the bottom of the screen, I see a picture of an old-school gramophone and a green heart which says “Grab it!” (see Fig. 4 below). If I want to ‘grab’ this item, I just need to swipe to the right and I’ll be alerted as soon as the item goes on sale. I can always swipe to the left if an item doesn’t suit my style (see Fig. 5 below). Everything comes together when I land on a screen where I read that I can buy my “favourite Grabs easily and securely. And get free delivery with every order!” (see Fig. 6 below).
  4. How does the app compare to similar apps? – In terms of pure user experience, I feel that only Pinterest comes close. Adding, viewing and ‘visiting’ my pins are all part of one seamless and simple experience (see Fig. 7 below) however, the retailer integration on Grabble feels more seamless and intuitive. By contrast, when I first opened the Nuji app (see Fig. 8 below), which is a close competitor in the UK, I didn’t find the first image particularly welcoming. Better was the simplicity of Fancy (see Fig. 9 below), although this app doesn’t feel half as stylish and inspirational as Grabble and somewhere between the two sits Wanelo (see Fig. 10 below).
  5. Did the app deliver on my expectations? – Yes and no. Let’s start with the ‘no’ part. It took a while for me to understand what the app was about. Initially, I thought I’d be subjected to an experience similar to Thread where I’d have to enter my style preferences, physical attributes, etc. On the contrary, the effort required felt minimal and I got the sense that once I start ‘grabbing’ or buying more items, Grabble’s recommendations will be on the money, especially given the large number of brands – 1,500 – on Grabble’s platform. Once I got that, it felt like the perfect app, but I do believe the app can work harder on making that clearer upfront.

Main learning point: I can now understand why big fashion retailers such as Zara, Uniqlo and Asos are all on Grabble’s platform, as it provides such a seamless integration between product discovery and purchase. Apart from the fact that it took while to understand the app’s main purpose, I really like the way Grabble recommends products within different categories based on the items users either ‘grab’ or ‘throw’.

Fig. 1 – Screenshot of Grabble’s opening screen on Grabble’s iOS app

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Fig. 2 – Screenshot of the “I want to shop for …” screen on Grabble’s iOS app

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Fig. 3 – Screenshot of Grabble’s first menswear screen on Grabble’s menswear iOS app

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Fig. 4 – Screenshot of an item that I can ‘grab’ on Grabble’s iOS app

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Fig. 5 – Screenshot of an item that I can ‘throw away’ on Grabble’s iOS app

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Fig. 6 – Screenshots of main landing screens on Grabble’s iOS app

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Fig. 7 – Screenshot of my “Sneakers worth checking out” board on Pinterest’s iOS app

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Fig. 8 – Screenshot of the landing screen of Nuji’s iOS app

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Fig. 9 – Screenshot of Fancy’s landing screen on iOS

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Fig. 10 – Screenshot of Wanelo’s landing screen on iOs

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Related links for further learning:

  1. http://www.telegraph.co.uk/finance/festival-of-business/11423613/Grabble-app-raises-1.2m-from-high-profile-e-commerce-angels.html
  2. http://www.forbes.com/sites/edmundingham/2015/01/19/tinder-for-fashion-app-grabble-targets-1m-users-as-ecommerce-moves-to-mobile/
  3. http://www.dailymail.co.uk/femail/article-2891194/Is-Tinder-FASHION-Swipe-right-style-matches-shopping-app-Grabble.html
  4. http://startupbeat.com/2013/10/16/grabble-targeting-fashion-forward-freshers-social-fashion-commerce-platform-id3507/
  5. http://techcrunch.com/2014/05/13/u-k-wanelo-competitor-nuji-launches-a-weird-app-with-an-interactive-woman-as-part-of-its-interface/
  6. http://www.businessinsider.com/pinshoppr-2012-5?IR=T

Site review: Thread

Thread looks like the perfect site for fashionable men or those who perhaps want to become a bit more fashionable. It was founded by serial entrepreneur Kieran O’Neill who explained to GQ at the end of last year what Thread is all about: “what’s special is that you have access to the exact same stylists that celebrities or wealthy individuals have access to.”

Kieran then went on to explain that Thread wants users to build a long term relationship with their stylists. I decided to have a go for myself and see what I can to do improve my style:

  1. How did this site come to my attention? – A friend of my mine, who I know to be very fashionable, mentioned Thread to me.
  2. My quick summary of the site (before using it) – A style guide for men who want to find out about fashion & apparel online which (1) fits their personal style and (2) takes away the need to search in multiple places online.
  3. How does the app explain itself in the first minute? – Thread’s homepage states in bold letters: “Dress well without trying”. It then explains – in less bold letters – that one of Thread’s stylists can help you find clothes you’ll love, “all online and completely free”.
  4. Getting started, what’s the sign-up process like (1)? – First, I got asked the standard stuff like my gender, age and date of birth. Things got more interesting when I was asked to select a style that I was aiming for (see Fig. 1 below). Knowing that I could select as many styles as I wanted, I selected 5 different styles which I felt came closest to the look that I’m aiming for. The only downside was that when I wanted to go back and add a few more styles, I realised that there wasn’t a “back” button.
  5. Getting started, what’s the sign-up process like (2)? – I then had to give an indication of how much I usually spend on each item. Perhaps it’s just me, but I felt a tad confused by the term “usually”, especially since I sometimes a spend quite a lot of money on clothing (relatively speaking) and other times next to nothing. For example, I’m an addict for sneakers so my collection contains Nike Air Force 1s that weren’t that cheap as well as Converse All Stars which were very cheap in comparison. It might have been better to have been able to use budget ranges rather than a set price point when answering this question.
  6. Getting started, what’s the sign-up process like (3)? – The next step, selecting the brands that I wear, felt easy and intuitive (see Fig. 3 below). I picked a few brands and added a brand that wasn’t on the list. I was then asked to upload some photos of myself (see Fig. 4 below). Perhaps I had missed it when I first arrived on the site, but for me this was the first point where I started to understand where all the previous steps were taking me; enabling a dedicated stylist to provide me with recommendations tailored to my style and brand preferences. It wasn’t clear, however, from the explanatory text what would happen if I didn’t upload a picture of myself. Would the stylist recommendations be less good? Would the whole process come to a halt? It might be an idea to have an explanatory text which appears when a user hovers over the “Skip” button. The actual photo upload process from Facebook was very straightforward.
  7. Getting started, what’s the sign-up process like (4)? – Even though I had pressed “Done” after uploading my photos, I was nevertheless presented with another step: “What do you usually wear to work? Select by clicking on the pictures, and hit “Next Step” when done” (see Fig. 5 below). Perhaps others may well consider my next suggestion superfluous, but how about adding that one can select as many styles as they like? Not only would this be consistent with the copy used for previous steps but it would also work well with the scenario whereby men dress smart 4 days per week, apart from on ‘Casual Fridays’.
  8. Getting started, what’s the sign-up process like (5)? – Next, I was asked about the trouser fit that I prefer. To be honest, by this point I was starting to get a little bit restless. Nonetheless, I clicked on the trouser styles that I tend to wear most often (see Fig. 6 below). I then expected to be asked about the type of shirt fit I preferred. Instead, I was asked about the types of shoes that I prefer. I selected sandals/flip-flops and sneakers/trainers (see Fig. 7 below), followed by specific colours that I preferred (see Fig. 8 below).
  9. Getting started, what’s the sign-up process like (6)?  I felt I was getting close to the end when I was asked whether I was “open to trying more daring fashion styles?”. What!? Perhaps I was just getting a bit tired at this stage, but I was like: “are you telling me that my current fashion style isn’t daring enough!?” and “what does daring mean?” (I know guys for whom wearing a slim fit shirt takes them way out of their comfort zones but I also know guys who wear pink clothes like it’s nobody’s business – their interpretations of “daring” are likely to vary). I then realised that I was being a bit facetious, since a good stylist would be able to interpret what “daring” constitutes for each individual user, based on their input as part of the previous steps. Outcome: I dropped my initial thoughts, as they didn’t make sense!
  10. Getting started, what’s the sign-up process like (7)?  After I’d indicated which styles and products I’d never wear (see Fig. 10 below), I was then asked some check box questions which aimed to give Thread and its stylists a bit more context about me. Answering questions on the amount of style help I felt I needed and my reason for using Thread actually felt quite helpful (see Fig. 11 below). What I found most helpful when it came to selecting my sizes (see Fig. 12 below) was the ability to leave a comment on any specific requirements. For example, I left a comment in the text field to say that when I buy shirts, I sometimes buy them in size “small” and other times in size “medium”, depending on the make of the shirt (I assumed that the stylist would be able to work out that I’ve got funny shoulders from the pics that I uploaded earlier).
  11. Getting started, what’s the sign-up process like (8)?  I found the brief description of “How Thread works” (see Fig. 13 below) very helpful. Part of me was wondering whether some of the info in this description could have been peppered throughout the different onboarding steps. Doing so could in my opinion have helped to provide the user with a clear picture of the end goal. By this stage I was ready to get some good fashion advice and it was great that I could indicate to my stylist what I was looking for in my first outfit (see Fig. 14 below). Et voila, I was then presented with my personal stylist, Sophie Gaten (see Fig. 15 below).
  12. How easy to use was the site? – The signup process mostly felt easy and intuitive. As noted above, I felt that there were few points within the signup process where additional explanatory text could have been beneficial. Also, I believe it would be good if the site would provide with more opportunities to mention specific clothing requirements or issues. For example, I liked a recent F&F fashion campaign by social media agency We Are Social which allowed users to pose more specific styling enquiries or requirements.
  13. How did I feel while exploring the site? – Not sure if one can truly refer to the onboarding process as “exploring”, I guess that will come once I’ve received some specific recommendations from Sophie, my personal stylist. Having gone through all the steps of the signup process, I have some suggestions for potential improvements that Thread could consider in order to keep users fully engaged throughout the process (see Fig. 16 below).
  14. How does this app compare to similar sites? – As intuitive as I found Thread, I really struggled with a similar app in CoolGuy; I clicked on the icons for “My Closet” and “Outfits” but struggled to grasp what was expected of me or what the app was about. My first impression of Trunk Club, which promises similar things to Thread, was that this site wasn’t geared to people like me. Purely based on the imagery used, I got the sense that people wearing baggy Carhartt trousers and colourful sneakers, might not be well served by Trunk Club’s personal stylists. It would be good to see what the user experience on similar apps for women (e.g. My Shape Stylist and Blynk) is like.
  15. Did the app deliver on my expectations? – Overall, I was very happy with the signup process, even though it did feel lengthy at times. The proof is in the pudding, so I’m looking forward to Thread’s actual recommendations!

Fig. 1 – Signing up for Thread: Screenshot of “What kind of style are you aiming for? Select as many as you like”

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Fig. 2 – Signing up for Thread: Screenshot of “How much do you usually spend? Select the amount you usually spend on each item”

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Fig. 3 – Signing up for Thread: screenshot of “What brands do you wear – Select as many as you like”

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Fig. 4 – Signing up for Thread: screenshot of “Upload photos of you”

 

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Fig. 5 – Signing up for Thread: screenshot of “What do you usually wear to work?”

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Fig. 6 – Signing up for Thread: screenshot of “Which trouser fits do you prefer?”

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Fig. 7 – Signing up for Thread: screenshot of “Are there any of these shoe types you prefer?”

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Fig. 8 – Signing up for Thread: screenshot of “Which colours can your stylist include in their recommendations?”

 

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Fig. 9 – Signing up for Thread: “How open are you to trying more daring fashion styles?”

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Fig. 10 – Signing up for Thread: “Are there any of these styles you’d never consider wearing?”

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Fig. 11 – Signing up for Thread – Screenshot of “Tell us a couple things about yourself”

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Fig. 12 – Signing up for thread – Screenshot of “Select your sizes”

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Fig. 13 – Signing up for Thread  – Screenshot of “How Thread Works”

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Fig. 14 – Signing up for Thread – Screenshot of “Tell your stylist what you’re looking for your in your first outfits”

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Fig. 15 – Signing up for Thread – Screenshot of my personal stylist

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Fig. 16 – Suggested improvements in relation to Thread’s signup

  • Ability for users to save their signup information and be able to come back to it later – There were quite a few steps to go through, which made me think that it would be good for users to feel comfortable abandoning the process halfway through, knowing that they can always come back to and edit their info.
  • Style summary at the end – I like having my style profile captured as part of my account info on Thread. However, it would be great if users could be presented with their profiles at the end of the signup process, prior to ‘submitting’ one’s profile. This way users will have the opportunity to edit any info before sending it over to Thread and their dedicated stylist.
  • Progress bar – Given the number of steps involved in the signup process, I’d suggest introducing a progress bar which gives users a sense of where they are in the process. During the signup process I felt at times  that I wasn’t sure when this process was ever going to end. It would be good if I could see a visual representation of the remaining steps and understand the consequences of skipping a step.

Related links for further learning:

  1. http://reviewify.co.uk/thread-free-personal-stylist-review/
  2. http://www.gq-magazine.co.uk/style/articles/2014-01/02/kieran-oneill-thread-personal-stylist-website-for-men
  3. http://www.businessoffashion.com/2013/12/thread-kieran-oneill-offers-a-personal-stylist-for-every-shopper.html
  4. http://adamreynolds85.blogspot.co.uk/2013/08/threadcom-shop-with-online-stylist-for.html

EDITD and applying big data analytics to the fashion industry

Since I went to a talk about visual search of fashion products, I’ve been keen to find out more about how the fashion industry uses big data analytics to make product decisions. I then came across EDITD, which is a real-time fashion analytics company based in London. Given my passion for both fashion and data, I thought I’d have a closer look into what EDITD do:

  1. EDITD’s mission – EDITD’s overall mission is to “help the world’s apparel retailers, brands, and suppliers deliver the right products at the right price and the right time”. Given the fast pace nature of the fashion industry decisions about product planning and the right amount of stock are absolutely critical. Julia Fowler, co-founder of EDITD, gives a good example when she explains that “today, an EDITD user can simply run a query on cardigans, for example, and receive results in under a second. More than 50 million SKU (Stock Keeping Units, MA) are tracked by the system.” I came across another good example in EDITD’s UK lingerie market retail calendar which aggregated data on new arrivals, discounts and sellouts can help merchandisers planning timing and location of their stock (see Fig. 1 below). It also helps navigate promotional activity and discounting.
  2. EDITD’s product – It was interesting to see what kind of features are included in EDITD’s product offering (see Fig. 2). I read in article in Fortune that EDITD’s dataset includes 53 billion data points on the fashion industry dating back more than 4 years. The Fortune article also mentioned that EDITD’s data covers more than 1,000 retailers across the globe. The way in which EDITD aggregates all this data through its different features (see Fig. 2) is where the main value of using EDITD’s services comes into play.
  3. Tangible benefits – Earlier this year, fashion retailer Asos said that using EDITD led to a 37% revenue increase in the last quarter of 2013. This was due to the data insights provided by EDITD which helped structure Asos’ pricing competitively. Geoff Watts, EDITD’s CEO, told The Guardian that the main value for Asos from using EDITD came from using their insights to make informed buying decisions grounded in data. “Retail on a basic level is all about buying the right things, so getting that right and making sure you’re selling the right product at the right price is really what dictates your success,” Watts said. Maria Hollins, Asos’ retail director, echoed this and stressed the importance of Asos making the right decisions faster than their competitors.“At ASOS, being first for fashion means being always competitive and having just the right assortment,” she said. “We’re using Editd every day to help us make critical buying and trading decisions”. If anything, EDITD saves retailers and brands from having to do so-called “comp shopping”, having to spend time going to competitor sites and stores to buy their products and compare prices. Instead, through EDITD, people can see at a glance what the competitive price points are (see Fig. 4 below).

Main learning point: I can see why brands and retailers are keen to use EDIT’s data tools and insights on a daily basis. The data on fashion and apparel has been aggregated and presented in such way that it accommodates fast decision making. I was particularly impressed with what I’ve seen of EDITD’s front-end dashboard and the way in which its purpose built product tracker provides real-time market visibility.

Fig. 1 – EDITD’s UK lingerie market retail calendar – Taken from: http://editd.com/blog/2014/10/timing-why-uk-lingerie-market-blooms-in-may/

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 Fig. 2 – EDITD’s main product features – Taken from: http://editd.com/product/features/

  • Market Analytics – EDITD offers a product tracker built specifically for the fashion and apparel industry. The tool provides real-time market visibility, analysis of new stock and discount activity, entry and exit prices and number of options in stock which enables retailers to benchmark their performance against each brand or retailer, providing insights into market positioning.
  • Retail Reporting – EDITD offers daily and week reports on what’s selling the fastest and the latest trends in new arrivals.
  • Visual Merchandising – EDITD has an archive of newsletters, blogs and webpages with real-time updates for brands and retailers across the whole market, worldwide. The idea is that every communication with customers is captured, to help users find discount cycles, product trends and themes, and understand their retail cadence.
  • Trend Dashboard – EDITD’s real-time tracking monitors trend progress, and historic data shows performance and trajectory. This data is all captured in EDITD’s Trend Dashboard (see Fig. 3 below).
  • Runway & Street – If you want to get a better sense of emerging trends straight from runway shows or the ‘streets’, EDITD provides visual reports on new fashion and apparel trends to look out for.
  • Social Monitor – EDITD has a Social Monitor which combines the knowledge of over 800,000 thought-leaders, key influencers and fashion experts providing an instant source of inspiration and insight into the hottest trends and opinions.

Fig. 3 – Screenshot of EDITD’s Trend Dashboard – Taken from: http://editd.com/product/features/

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Fig. 4 – Screenshot of EDITD’s front-end providing competitive insights – Taken from: http://menapparelonline.com/blog/fashion/fashion-data-tool-editd-helps-asos-push-revenues-up-37-the-guardian/

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Related links for further learning:

  1. http://fortune.com/2014/09/22/fashion-industry-big-data-analytics/
  2. http://www.theguardian.com/technology/2014/jan/30/fashion-data-tool-editd-helps-asos-push-revenues-up-37
  3. http://www.wgsn.com/en/
  4. http://menapparelonline.com/blog/fashion/fashion-data-tool-editd-helps-asos-push-revenues-up-37-the-guardian/
  5. http://editd.com/blog/2014/10/timing-why-uk-lingerie-market-blooms-in-may/

Find similar fashion through Cortexica visual search

Last week, I went to a great talk by Alex Semenzato, who works as a Business Development Manager at Cortexica and is founder of FashTech. In his talk, Alex explained about the visual technology as developed by Cortexica. He discussed this technology in the context of fashion products, making the case for how visual search can really change the way we find out about fashion products and trends.

Especially given that fashion is such a visual product, it was very interesting to hear about how visual search can drive product discovery. Because of its visual nature, I can imagine that it’s much easier to explain what you’re looking for through images than through text.This is what I learned from Alex Semenzato’s talk:

  1. Find similar – The main proposition behind using Cortexica’s findSimilar™ software is that “you can shop any look just by taking a picture”. Users can take a picture on their mobiles of a design pattern or look that they like and use the visual search functionality on the client app to find either the exact item, or the most similar option(s) within the retailer’s database. One big caveat though: the quality of your visual search results is very dependent on the products available in the database of the retailer whose app you’re using. For instance, when I did a visual search through the Zalando app, the most relevant results that the app returned didn’t get  close to the look that I was searching for (see Fig. 1 below). In comparison, the results that the Macy’s app returned already felt more relevant (see Fig. 1 below).
  2. Matching – Alex explained that the matching between user’s pictures against fingerprints in the retailer database takes into account things such as colour pattern, texture and – eventually – shape. The technical challenge is to really get this mix right when doing the matching against available items in a retailer’s database. For example, the search technology needs to understand the different textures that a fabric like denim can have. It will be interesting to see how Cortexica’s competitors such as Snap FashionChic Engine and ASAP54 compare in this respect.
  3. Big data – In his presentation, Alex talked about potential B2C opportunities around Cortexica’s visual search capability. “Big data” was the first thing that he mentioned. Sometimes it feels like I can’t go to a presentation without at least one person mentioning the words “big data”, but it being able to measure makes a lot of sense in the context of visual search and fashion. One could use the analytics around products searched for (and bought) to gauge demand and to aid with product on-boarding. However, as a member in the audience rightly pointed out; the value of past data can be quite limited in the world of fashion, where it’s all about today’s trends. Alex talked about using the data generated from visual searches also in relation to merchandising solutions, associating similar items with the main product that one wants to promote.
  4. Things to watch out for – With the previous point about data opportunities come questions around data protection and data ownership. I would like to find out more about visual search and aspects like data usage and ownership. Think about questions such as “can I just use the data generated from ‘street style images’?” and “will the retailer own the images that I took and any associated data?” which I’d love to get answers on. Also, I wondered – after having had a play with the functionality – how to get the user experience around visual search right, especially if users don’t discover the type of product or look that they were looking for. For example, how do you keep users engaged if their retailer or publisher app doesn’t return the desired results?

Main learning point: I really enjoyed Alex Semenzato’s talk about the visual search capability as developed by Cortexica. It seems like a very logical and intuitive way to discover new products and I can see the visual aspect working particularly well in relation to fashion products. Given that this is a relatively new technology, there are few things which still need to pan out: the use of data and the overarching discovery experience for the user. Cortexica has definitely created and interesting piece of technology which can benefit both consumers and retailers alike.

Fig. 1 – Using Cortexica “Find Similar” visual search through the Zalando app

The image that I searched on:

IMG_2416

 

The “most relevant” results that I got back on Zalando’s app:

IMG_2417

 

The “most relevant” results that I got back on Macy’s app:

IMG_2418

 

Related links for further learning:

  1. http://www.snapfashion.co.uk/
  2. http://www.chicengine.com/
  3. http://www.businessoffashion.com/2014/05/visual-search-set-make-world-imagery-shopable.html
  4. https://www.asap54.com/
  5. http://thenextweb.com/apps/2013/01/17/stileeye-launches-its-visual-engine-for-fashion-out-of-beta/
  6. http://blog.neimanmarcus.com/press-room/neiman-marcus-partners-with-slyce-to-introduce-single-tap-visual-search-technology-revolutionizing-luxury-shopping-with-snap-find-shop/
  7. http://www.telegraph.co.uk/finance/businessclub/11168037/Virtual-fitting-room-Metail-firm-raises-7.5m-as-consumers-find-new-ways-to-shop-online.html
  8. http://www.magicmirror.me/