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All that fits

 

Blog

All That Fits. Gribbin Strategic's blog keeping you up to date on new trends in the industry and advice on how to navigate the fashion and apparel industry.


 

Shoptalk 2018 - Part One: 'it's all about fit'

Hi, all. I want to share as much of what I saw and learned at Shoptalk last week as I can with all of you. It’s an exhausting but stimulating four days of non-stop action. I’ll do this in two entries, one about ‘fit technologies’ and the second about everything else. As you may know, I’ve been termed the “fit guru” in the press and I still love following up on the new tech startups trying to solve problems that I've been working on for almost two decades ago (before AI to help, by the way). FYI, while I’ve officially launched my new consultancy now (April 1), I will not be doing fit-related work. When it comes to fit consulting, I will be referring any inquiries to the fabulous team I’ve built and trained at Alvanon over the past twelve years. They are truly the best!

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Shoptalk was, once again, one of the most interesting and informative conferences on the calendar. It was held two weeks ago in Las Vegas and had over 8,500 attendees this year, up 60% from last year. There were also a record number of exhibitors running the gamut from big tech like Google and Facebook to financial firms like Visa, Mastercard, Amex, and Chase, to probably a couple hundred fledgling technology start-ups.

The whole point of Shoptalk is to understand and explain the intersection of legacy retail and ecommerce, through the lens of technology innovation, in order to predict the future of retail; so, in that context, the message of ‘fit’ is a pretty important one.

True Fit, which recently raised another equity round $55mm, bringing total capital raised to $95mm to date), had a huge booth and hourly fashion shows on an elevated runway. Their new round is going into funding new AI technology which uses machine learning to accurately predict not only size but fashion, color and style preferences. They don’t report revenues but claim they tripled their revenue last year from 2016; they have 120 employees based in Boston with plans for another 35 this year. I’m not a big fan of their base consumer size prediction solution, but that ultimately may not be the point. They have more data than anyone in the field and will ultimately bring complementary value to one of the big tech players. A senior executive from one of their largest customers told me, “it doesn’t really work that well, but it’s the best online customer engagement tool we’ve ever tried….”.

The other fit-related companies exhibiting included Like A Glove, who sells a sensor-laden tight that measures you when you put it on and recommends the best fitting jeans in terms of brand and size. It might work, and it might be very cool technology, but I struggle to figure out how it scales. They are trying to sell the tight (on sale now for $68) to consumers, a big ask; then they have to hope the consumer uses the “one-size-fits-all/ size 0 to 20” tight correctly. Even if all works as planned, though, they recommend well-known brands who may or may not be able to fit the “hard-to-fit” consumers who are desperate enough to buy the tights in the first place. I certainly wish them luck, though.

Then, I met the co-founders of Bold Metrics, who uses AI and algorithms to predict body measurements based on a consumer’s answers to a handful of questions. They count Levi’s, Express, Men’s Wearhouse and G-Star among their clients; they are still in the proof of concept stage (after 5-6 years now) and claim to use their solution primarily as a size prediction tool on a client’s e-commerce platforms. They have a second solution using augmented reality where they create an avatar from a customer’s predicted measurements for virtual try-ons and they have a third solution called ‘Apparel Insights’ which purports to use client data to drive insights into garment specifications among other things. They present the data similarly to how Alvanon presents bell curve distribution data but, in questioning the co-founders, I don’t think they really understand apparel (in terms of design, tech design or production issues like sewing tolerance or shrinkage); they are really data/tech geeks trying to solve what they perceive to be the massive returns/conversion problems facing online retail. Daina and Morgan, the co-founders, are very passionate, though and I wish them the best.

I also had meetings with Sizer, a very cool smartphone body scan solution out of Israel; and 3D Look, another smartphone body scan solution out of San Francisco and Ukraine that I’ve tried and it really seems to work for capturing key measurements (even if your clothed). I met a friend from Fit Analytics, the German-based online size prediction provider whom we’ve partnered with previously on a marketing event; they have some real traction because they’re using a brand’s own transaction data and AI to predict sizes for online shoppers. Their solution has very little friction, no photos, no list of questions. I also had an interesting discussion with Air Tailor, a NY-startup that has an app that retailers can use to facilitate alterations of garments (mostly sleeve and trouser hems) in order to help close more sales; interestingly, they are building a “database of consumer measurements” every time they get garments to alter (what they’re really getting is data on finished garment measurements and the difference between original garment specs and, who knows, there might be value in that).

All of these companies, plus about 18-20 others by my count, are all trying to solve the problem of how to determine the right size to buy online, or how to customize fit for any given consumer. The amount of private equity money thrown into this space, not just now but over the past twenty years (including my old company, Intellifit) has been staggering, yet they’re all still out there with the problem unsolved…..my prediction: there will have to be consolidation of the best technologies married with the best business models, probably sooner rather than later since the clock is ticking and my guess is that the cash is burning.