Blending better fashion ideas with juicier data

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Experienced startup watchers will tell you that some ideas just keep coming around again because no-one ever quite does them in a way that sticks.

‘Personalised fashion discovery’ is one such idea, and today’s startup has a fresh take on the problem. Scroll down to read all about Blend.

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Blend draws on social media for better fashion ideas and juicier data

Blend is a startup with a fresh take on a familiar problem: offering personalised fashion recommendations.

In practice, that looks like “TikTok meets Lyst or Farfetch… a more social, engaging, and hyper-personalised fashion shopping experience,” as co-founder Jemima Bunbury puts it.

Rather than just link to shopping sites, Blend will incorporate content from influencers and creators, for a more organic feel.

“We're very aware that people want to discover and explore items of clothing through other people and how they're styling them,” says Bunbury.

Under the (highly fashionable) hood

“Personalisation has been such a buzzword in the fashion industry for so long. So when you say that you're a personalised fashion discovery platform, people think, ‘I've heard this before, what's different here?’

What’s different, as Bunbury and her co-founder Bella Levin explain, is the TikTok-style algorithm behind the scenes learning about your tastes as you use the app. 

“From one second to the next, in-session, we’re able to personalise what products you're being recommended,” says Bunbury. “And we're able to do that by looking at how you compare to other users on the platform and also how products are related on the platform. So ultimately, we look at what is the statistical likelihood of you liking that product.”

The brands a user interacts with, the budget they have, discounts they find appealing, and how long they browse before buying, all factor into what the user is shown. 

“It’s a very rich picture of what your user behaviour is as a consumer, and also what kind of fashion products you like,” says Bunbury.

This rich picture, she notes, should give Blend an edge over online retailers’ own ecommerce interfaces, which, you might have noticed from your own online shopping, tend to look almost identical to each other.

“Probably the funniest insight that we had from a head of product at one of the largest fashion retailers was that the majority of user data they lose, because people don't log in,” says Bunbury.

“Given that we’re app based, we have login by default, whereas retailers have to try to put in these workarounds to get access to data if people don't log in.”

The business model

Blend plans multiple revenue streams: a commission from sales through the platform, a consumer subscription for additional features, and later, B2B services like data and trend forecasting. The startup could potentially provide personalisation tech to brands, too.

“We're currently shaping that with a potential pilot partner at the moment. We're hoping to co-create it with them so that we really understand the inner workings of what our clients are likely to need, beyond our own experience in the fashion industry,” says Bunbury.

“Speaking to retailers, they really struggle to personalise… they're not able to create a full picture of the user and therefore target them according to that. 

“There's also a lot of additional benefit in being able to understand the wider market. And as a multi-brand aggregator that has the ability to pull in product data from all the different retailers, we should have very good coverage of what are the key items that are being purchased, what is getting the most interest, what discounts are being applied, and what prices are people pricing these items at.” 

Essentially, Blend is looking to monetise what they hope will become a detailed picture of consumer fashion retail activity.

Regular readers might remember we profiled Fassion a few months ago, which has some similar ideas but is going more for a more purely retail-focused approach and a strong drive towards independent brands.

The story so far

Bunbury and Levin met on LinkedIn, after Levin had released an initial version of Blend that was very different from what it is today.

Levin has a background in the European startup ecosystem, often in partnerships and business development roles. She also co-founded a creative freelancing marketplace startup. Looking to build something more aligned with her personal interests, she began work on the first version of Blend.

“Originally it was a different concept. It was an on-demand fashion marketplace. The idea was to build something similar to Kickstarter, where brands were able to advertise their ideas and only produce based on actual demand,” Levin says.

Having released that first version, Bunbury got in touch to discuss the concept. She has a background in fashion. She worked with her mum’s brand as she was growing up, which led to internships with big fashion brands. 

Switching into tech, she spent time as an associate at Invoke Capital before moving to Accenture’s startup-focused consultancy, Founders Intelligence.

Together, Bunbury and Levin began to assess how Blend’s proposition could be rethought.

“We started thinking it was a very scalable business, and there were a lot more problems in the fashion space that could be addressed, but we would need to define the bigger problem, which turned out to be personalisation,” explains Levin.

“We interviewed 100 different customers and went back to basics. We asked them open-ended questions on what their key challenges were when they were shopping online,” Bunbury adds.

“The one that came back from every single person we spoke to, and really resonated with us as well, was the idea that it's super-overwhelming to shop online, and demotivating because you spend three hours looking, and you either end up not finding anything you like and then you give up, or you buy 30 things and then return half of them.”

The pair say they heard of particularly organised shoppers who became experts at using filters or used Excel spreadsheets to keep track of the shopping landscape.

While social media recommendations were a common discovery method, customers said this was far from optimal. This feedback inspired Blend’s TikTok-like interface.

Levin and Bunbury are joined at Blend by co-founder and chief product officer Eva Piskova, plus a CTO with a PhD in machine learning, and experience as a Machine Learning and Software engineer.

The roadmap

Blend is gearing up for an invite-only beta launch to their waitlist, which Bunbury said numbered 1,700 at the time we spoke recently. Brand partners are apparently also on board. The beta is scheduled to launch in July, with an official launch of the app to follow later in the year.

From there, they will refine the product based on user feedback while building out their B2B offering.