Men’s fashion startup Thread raises $22 million

Thread
cofounders Ben Phillips and Kieran O’Neill, and style director
Shaunie Brett
Thread

• Menswear startup Thread has raised $22 million
  (£16.7 million) to help men navigate clothes shopping.
• Thread uses a mix of machine learning and real-life
  stylists to learn about its customers’ fashion tastes, and
  recommend stylish clothing accordingly.
• The company has well-known brands such as Hugo Boss
  and Barbour on board, and more than 1 million customers.
• The company will use the money to cement itself as
  a household name and build up its technical capabilities.

Thread, the startup that helps men who hate shopping buy clothes,
has raised $22 million (£16.7 million) in venture capital backing
to expand its technical capabilities and to cement itself as a
household name.

Thread has more than a million customers signed up to its
service, which takes a few registration details about a user’s
fashion taste and budget, then uses that information to recommend
new outfits.

As customers buy more clothing through the app, Thread’s
algorithm learns more about what they like and makes new
recommendations accordingly. It also learns from clothes
customers click on but don’t buy, what they scroll past, and what
the weather’s like.

The idea is that men who hate rifling through racks of clothes in
physical stores can still look smart and on-trend by buying
through Thread. Well-known brands such as Barbour and Hugo Boss
are available through the service.

The startup employs 10 full-time stylists who curate outfits and
write personalised messages to customers. But much of the
recommendation load is handled by Thread’s homegrown machine
learning algorithm, much like Spotify’s algorithm recommends
music.

A quarter of Thread’s users buy all their clothes through the
service

Chief executive and serial entrepreneur Kieran O’Niell said a
quarter of Thread’s users buy all their clothing through the
service. It’s currently only available to male shoppers in the
UK, but O’Niell said the plan was to introduce womenswear to the
app some time in the future.

It has, he said, taken almost four years to get the machine
learning aspect right. “If you use off-the-shelf approaches, you
get boring results,” he said. “Like if you buy a black T-shirt,
you would be recommended a grey T-shirt. So we had to create
something that would understand what you like… and factor in
individual preferences, plus what the weather is like, and stuff
you already own.”

One thing the service could do better, he said, was adapt to
customers’ changing tastes. “What we’re not good at is someone
who did want [certain] stuff, has changed, and now wants more
adventurous stuff. There’s more we can do on that side.”

O’Neill added that most of Thread’s customers were aged between
25 and 45. “I was surprised our customer base is as old as it
is,” he said. “I would have thought a younger guy would be more
fashion-conscious, it turns out lots of guys between 25 and 45
want to dress well [and] don’t like shopping.”

Thread’s latest round was led by new investors Balderton, Forward
Partners, Beringea and H&M’s investment arm. The round
included a small amount of debt financing from Triplepoint
Capital. High-profile previous investors include DeepMind
cofounders Demis Hassabis and Mustafa Suleyman, and prestigious
Silicon Valley bootcamp Y Combinator.

O’Neill also plans to follow a startup trend set by the likes of
Monzo and BrewDog: letting customers buy in. The company will
open up to crowd investors via Crowdcube in November. The plan is
to raise £500,000 to £1 million, though O’Neill said Thread may
cap the round.

“From the beginning we we always wanted to hold back part of it
so customers can invest,” he said. “The main reason we have
succeeded is because of loyal customers, and it’s just a way of
offering them the chance to invest in the business. We’re not
doing it to raise lots of extra cash.”