In the early days of e-commerce, we used to talk about where internet users and online shoppers were on the “experience curve”: most people started their e-commerce lives buying something low on the curve such as a book, CD, or DVD — something with a fixed function and format, that you could count on to look and work a certain way when it made its way into your hands.
On the higher end of the curve were items such as clothes and furniture which — back then — people were more wary of buying “unseen”. Descriptions and images weren’t enough for newbie online shoppers to have confidence in the fit and texture.
Given this “e-tailers” worldwide have poured themselves into solving the problem, offering sophisticated tools to help people better understand look, feel, texture, and fit before they click “add to cart”. This is critical because fashion e-commerce struggles with some of the highest return rates in any retail category, as high as 50% in some cases. And unlike real world retail, the cost and logistics of returns typically shift to the seller. This can whittle away at profits and become a customer service nightmare.
So how do you sell more product and reduce expensive returns? You get better at meeting customer expectations. Or at least that’s the answer of several fashion-related tech innovations.
For example, Israeli start-up Zeekit is getting serious traction from stores aiming to integrate “virtual fitting room” technology into their sites. British fast fashion retailer Asos is one of the latest to deploy this tool that uses real-time image processing and augmented reality to enable users, or shoppers, to “try on” clothing items.
Users upload a photo of themselves to the site, then Zeekit’s patented technology “maps” the image to the piece of clothing in question. It does this by breaking both into thousands of segments, so the result isn’t a simple overlay like a paper doll, but the appearance of actually wearing the clothing in question to meet their proportions and simulate fit.
It does this so seamlessly — no pun intended — and quickly, that you can scroll through photos of yourself wearing just about the entire sales catalogue.
This is what international retailers are having to grapple with: a consumer with all the power and choice, but limited loyalty
Another start-up that just launched is The Yes, which hopes to learn a consumer’s preferences and specifics (such as size) so smartly that it can offer a personalised selection of clothing across brands.
The idea is that all users’ results are unique to them. If Zeekit is the poster child for deploying augmented reality (AR) in clothing sales, then tools like The Yes are aiming to be that for the power of the recommendation engine (normally associated with Netflix and Spotify).
On the other side of the coin are innovators aiming to sell their data-driven insights to the manufacturers and retailers. Spate was started by some escapees of the Google Trends team, who have turned their learnings into predicting what the next big thing will be, and to sell that insight on to companies.
All of which is further breaking down concepts such as brand loyalty, and driving fragmentation of the market. This is what international retailers are having to grapple with: a consumer with all the power and choice, but limited loyalty. These consumers are happy to buy their clothes online, and the logistics systems in markets such as the UK and US allow for delivery that is cheap and efficient.
SA has additional challenges: a much smaller pool of consumers who are both happy to spend and be connected. But this is changing, and rapidly. This is just one area in which demand for data science will increase.
I spoke to Shaun Dippnall from Explore Data Science Academy (EDSA) earlier this year about the school (of which he is a cofounder) and their aspirations.
Dippnall and his partners started EDSA in 2017. It began with about 100 students who had signed on for a year. It has since grown exponentially, as have its goals: to produce 5,000 new data scientists by 2025. EDSA takes on students in its various data science courses, directly and via corporate partners. It announced a partnership with African Bank last month to train 50 data scientists for the bank.
Financial companies and banks have been quick to jump on the data science bandwagon. The big grocers too are doing interesting things with customer segmentation and behavioural analytics.
Local apparel makers and sellers with aspirations to surviving the next decade should be looking at how they can prepare to meet the digital expectations of consumers, and streamline their supply side through data-led insights.
• Thompson Ferreira is a freelance journalist, impactAFRICA fellow and WanaData member
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