Omni-channel comes to life

An interesting reshuffle of urban, physical retail space seems to be underway. First we had dark kitchens, now we’re getting dark stores — Dija and Getir two recent London-based examples. To some extent this is the logical extension of Deliveroo multiplied by the surge in online grocery delivery, but the pandemic seems set to wrought deeper changes in the high street. This week the Guardian reported that more than 17,500 chain store outlets disappeared in 2020¹. Expect this to get worse before it gets better, just in this morning’s FT²:

Renewal will surely follow, but the high street in coming years might look quite different. That clumsy word — Omnichannel — so often bandied around as the future, with little to show for it yet other than click and collect, might actually start to come to life. Three trends are colliding that could lead to a reinvention of how the high-street looks and feels: 1) the cost of retail space plummeting as retailers go out of business and landlords take write-downs -> opens the door for experimentation; 2) normalisation of buying things online through the pandemic will need retailers to do the same thing offices will need to do, which is give people a reason to come in-person -> differentiated, compelling, in-person-only experiences; 3) the getting-towards-breakout stage of technological development in AR/VR.

How could this come together? While AR-VR is rolling out apace into homes — think Ikea Place app, or Oculus Quest 2 — there is likely to be large category of AR-VR-based experiences that don’t have wide-scale deployment in homes anytime soon. VR platforms will take a while, but more intriguingly is something like Smart Mirrors:

This video gives a good sense for where the technology is at right now:

This technology alone could be enough to create a completely new category of clothing shopping experience. Imagine the inverse of a dark store — not a fulfilment hub, but a ‘try it on’ hub. At the moment when you visit a clothing store all the stock is kept onsite; you browse and select. But suppose instead that you visit the store to use a smart mirror. This technology lets you ‘try on’ clothes from an almost endless list of inventory. Instead of 10 t-shirts to choose from there are 10,000. Now imagine that you find a handful of clothes that seem good in the mirror — you ‘order’ them to try on for real. The inventory isn’t held onsite (too much selection) but in a warehouse on the outskirts of London, so you head to mill around town for a couple of hours, have a coffee with a friend. A couple of hours later you get a text to say the order is in, and you head back to the shop to try on these clothes for real. You pick what you like, discard what you don’t, and pay right there and then. No faffing around with taking returns parcels to the post office, no being out of pocket for weeks.

As an experience this would be astounding — you get the best of bottomless online selection to choose from, all in one place, without the inconveniences (not to mention carbon emissions) of having to receive and send parcels at home. It would be fast and spontaneous, without the constraints physical space place on selection to choose from.

Perhaps you imagine a traditional clothing retailer doing this, Monsoon, Ted Baker, John Lewis perhaps, but I see it the other way — it is the natural extension of the online stores’ core competency. They (e.g. Asos, Thread, Boohoo) have had to figure out how to handle discovery, and this is not an easy problem. How do you recommend the right things to people, quickly ? This feels a harder problem than shipping clothes in and out from a suburban warehouse. So who are the masters of online clothing discovery? In the UK: Thread, and in the USA: Stitch Fix.

Stitch Fix are the obvious candidate to do something like this. They are already experts in figuring out what 10–20 articles of clothing you would be most likely to like, they have spent years mapping in exquisite detail all the measurements of articles of clothing (over a hundred attributes per item sometimes), and building the supplier relationships necessary to support this. They are a tech company first, and a clothing retailer second. An in-person experience using the mirror-model could easily be combined with their stylist experience, someone to help you navigate the selection, recommend and try things on in the mirror.

How long until Stitch Fix try something like this? How long before they have a store on Oxford Street? Besides being incredible advertising for them — a presence in the heart of London’s most famous retail district — there is an exquisite data angle for them in it. While they look like a clothing company, they are really a data company — that’s why they poached the the VP of Data Science at Netflix to become their Chief Algorithms Officer. They thrive or fall, in the long-run, on their ability to make high-quality recommendations to users on what clothes they will like. What’s exciting about this mirror-model is how it would accelerate the pace of data acquisition by an order of magnitude. Instead of waiting weeks to find out whether their recommendations were good (based on what items a customer keeps and sends back), they would know this information within hours. Writ large, this means the rate at which the algorithms — the company — learns would leap upwards, allowing them to build better and better user experiences, and getting harder and harder for competitors to catch.

The next stage would be for Stitch Fix to start putting these smart mirrors in offices, but that’s a one for another day….





Data scientist, product junkie, one-time founder. London-based. @tgh44

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Data scientist, product junkie, one-time founder. London-based. @tgh44