The Long View | How Realtime Data is Reshaping the Fashion Business

Julia Fowler and Geoff Watts | Source: Editd

LONDON, United Kingdom — Clearance sales point to a perennial problem in the fashion industry: the misalignment of supply and demand. Using traditional market research, brands and retailers are unable to predict with high accuracy what products consumers will actually purchase during any given season. As a result, merchandise that doesn’t sell is marked down, while demand for popular items goes unmet, leading to significant loss of income.

But better aligning supply and demand is a complex matter. That’s because, in trend-driven product categories like fashion, historical sales data never results in consistently better commercial decisions. What brands and retailers really require is information about what’s going to happen, not what’s already happened. But traditional fashion forecasting tools like panel-based research and trend reports are slow and unscientific, leaving buyers and merchants to make important business decisions based largely on intuition.

Now, an ambitious London-based startup called Editd — which, earlier this summer, raised a $1.6 million round of seed funding led by Index Ventures, investors in Net-a-Porter, Etsy and ASOS — is offering a realtime data monitoring and analytics platform that makes commercial decision-making in the fashion industry more scientific.

Crawling fashion retail sites, monitoring consumer opinions on social media and analysing output from key industry events, the platform blends machine-learning with human editing to turn vast amounts of raw data, captured in realtime, into the kind of actionable information that can give brands and retailers a competitive edge when making decisions like placing orders, determining pricing and managing merchandising.

BoF spoke with the founders of Editd, Geoff Watts and Julia Fowler, to find out more about how data-driven intelligence is revolutionising retail and reshaping the business of fashion.

BoF: What’s wrong with the way most fashion forecasting works today?

GW: A tangible lack of data and facts, plus the collapse of seasonal fashion is putting a lot of pressure on the way the industry works today. Most businesses have sales reporting or business intelligence to know what is selling, so they already understand the value of data at a trading level. This sales data combined with a great understanding of their customer, inspiration from trend services or their own research is what they use to make an educated guess about where things are going. But even the geniuses can’t get it 100 percent right — otherwise clearance sales wouldn’t exist because everything would sell through!

JF: Seasonal fashion is dead and speed-to-market now is the market — even on the high end. Many brands that work with us are doing 10 or more drops a year, so although the weather is seasonal, fashion is constantly variable. People expect to see new garments on every visit to a store and the production capacity is there to make it happen. Traditional forecasting isn’t a good fit when production can be so close to the market.

BoF: How can technology make this process more scientific?

GW: The cleverest businesses can know exactly what their customers want by using technology. You can measure consumers and the entire trading environment. Customers express themselves constantly online either through Twitter, on their blog, clicking a ‘Like’ button, adding a product to a basket, or buying something. The retail market is measurable — there’s never been more accurate, factual information on exactly what’s happening in realtime than now. It’s an incredible strategic advantage. But the breadth of information out there is too great for people to process and synthesise into actionable information. That’s why we developed Editd.

BoF: Last year, researchers discovered that they could predict, with astonishing accuracy, how well a movie would sell in its first couple of weekends by analysing mentions on Twitter. Can a similar analysis of realtime social data accurately predict demand for fashion products?

JF: Definitely. Though fashion is more nuanced than movie releases. People express opinions about fashion constantly — we have more than 100 million opinions sourced over the past 12 months specifically on individual garments, fabrics, prints and styles. One great example is our data on the longevity of skinny jeans — a trend that endured much longer than traditional forecasting would have predicted. The demand curve was obvious in our data. Making calls on short-term trends based on data is tremendously valuable as well. The ability to know if coloured denim, or leopard print will endure for the next 3 months is vital.

BoF: What types of data should fashion brands be monitoring to generate the most accurate predictions?

GW: Brands should get to know their competition and the full market. Your own sales reporting can’t tell you about something you never produced. Social data should be used beyond the marketing department; buyers and designers should understand what people are saying — it’s an incredibly powerful channel. But good data is useless without good execution. Last week it was 105 degrees in Manhattan and retailers had plenty of notice. Despite that, virtually all summer apparel was on sale and visual merchandising centred around coats and knitwear. It’s a perfect example of lost profit opportunities.

BoF: In a product category as emotional as fashion, to what degree should data drive design, buying and merchandising decisions? Can data-driven intelligence ever completely replace human intuition? What is the right mix?

GW: Some decisions will be handed off to technology, like when to discount, replenish, or what quantities to order. Computing can never replace human creativity, but designers and buyers should always keep their eye on the data — there’s nothing more satisfying than creating a best-seller.

BoF: Who is doing this well today?

JF: Burberry are a great example. They have strong creative direction while blurring the line between being a technology and a fashion company. There’s no doubt that they’ve directly interacted with their customers, understand social and can interpret the whole market. They have short-circuited the risk of production and holding inventory by introducing capsule collections, taking pre-orders before garments are produced, and having iPads in stores to view and order stock that’s not held on-site. Having that much data and being that close to their customers makes traditional forecasting irrelevant.

BoF: How will the rise of data-driven intelligence change the fashion industry in the years to come?

GW: One of the biggest wins will be to reduce wastage, which is an epidemic in the fashion business. We’re excited about the creative benefits too. With production capacity evolving as it is and the ability to understand consumers, we think it won’t be long before the fashion industry can be more experimental and less homogenised, while still being profitable.

Vikram Alexei Kansara is Managing Editor of The Business of Fashion

Related Articles

Post a Comment


  1. This is very exciting to see advances in data mining and forecasting applied to fashion. It’s great to see a start-up like Editd.

    However, I think that clearance sales are not a “problem” per se. Assuming products are not sold at a loss (i.e. price is not less than marginal costs), clearance sales should still generate profits. Sales are a classic example of price discrimination – they reach consumers who have lower price points and are willing to wait.

    Unsold products and wastage are a different story. Data-driven intelligence should make a huge difference.

    Nicola from Dundee, Dundee City, United Kingdom
  2. Congratulations Julia and Geoff on an idea and concept whose time is long overdue!

    Mind you, I still find that with all of the current analysis, trend forecasting and “crystal ball” predictions out there, buyers still quite often overlook their most accessible information…the voice of the sale people who hear all from the customer…often before it hits Twitter, Facebook or the latest fashion blog!

    Good luck going forward.

  3. This seems to be a ridiculously over-engineered solution (albeit an ingenious one) to an artificial problem that was created by the fashion industry in order to maximise consumption. The technology exists to manufacture on-demand whereby customers can become involved in the design of the product – this build-to-order approach eliminates the risk of missed sales or unsold stock; the customer gets product with greater personal value that they would be more likely to keep; and the planet is happy because there is less over-production. I believe Burberry are about to launch something similar to this very soon.

  4. Having worked in Merchandising, Planning, Production and Product Development – from both sides of the fashion industry – retail and manufacturing – I would love to sit-in on an Editd sales meeting. As a relatively new blogger, I’ve seen and experienced the power of social media marketing – there’s no doubt that data-driven intelligence will be invaluable to forecasters both on the retail and manufacturing side. The issue I have is how to take the real-time information into actionable execution – considering production lead times and sourcing of materials. A department store buyer – can turnaround this data and possibly affect same season sales/profits, but what about private label retailers – and manufacturers – who are probably now finalizing Spring 2012 designs and work with much longer lead times? With regard to Laura’s comment – I agree – the sales force voice (back in my time) was the best source of information regarding consumer demand – but that’s where the internet and social media have changed the game. Back in the ’90s we were looking up LY’s sales, weeks-of-supply, best/worst sellers manually off of dot-matrix printed reports. The other issue I have, is with “smarter” forecasting – the goal is higher turnover and leaner inventories – which all looks beautiful to the bottom line, but merchandised in a 3,000 sq.ft store looks bare. The economy has changed the retail atmosphere dramatically – and as a “shopper” (who no longer works in the industry), I was pretty shocked to see the same shoe merchandised in 5 different places at one department store recently (may have “tricked” the traditional shopper, but not this trained one). My size (of the shoe I wanted to try on) was “on display” with every other shoe size in the run. As for the 105 degree weather and with fall coats and knits visually merchandised – that is the first-to-market cycle that hasn’t changed in decades – Fall Lines shipping in June – Resort shipping as early as November. It’s a brilliant concept, Editd. I wish I was still behind the scenes to see how it’ll change the retail atmosphere in the upcoming years.

  5. Editd is doing a fantastic job bridging fashion and the big data.

    In all other industries – even those driven largely by emotions – it’s the big data that helps gain efficiencies and impact the bottom line. It was time there were companies like Editd bringing the same to the fashion.

    Looking forward to seeing more news on them.

  6. The technologies developed by Editd are moving upstream the value chain of the industry but, I believe, it’s application won’t be easy to do outside specific markets. I find this technology hard to be globalized as the use of social media networks is assymetric in the various big european/american cities.
    Nevertheless it should be a powerful tool to merchandisers, forecasters, producers as it’s novelty could transform itself in a very imnportant quantum leap of fashion industry.
    I will try to follow the company.

    paulo cruz from Porto, Porto, Portugal
  7. I think Editd’s product is fabulous. As a new fashion blogger, I am constantly overwhelmed by how much information is available about what’s on trend and a brand’s perceived position in the market. While there is a short list of social media outlets that may qualify as “fashion influencers” that are quite well known, the community of independent fashion bloggers is staggering. As is the problem in many industries, businesses don’t quite yet know how to harness this vast supply of data and and create meaningful, powerful information.

    While I agree with Cecilia’s comment about the value of Editd from the perspective of a manufacturer who has to deal with long lead times, I think that the shift towards “fast” fashion, with respect to the demise of traditional seasons and speed-to-market demands, is a permanent one. With the pace technology is advancing at and the market’s expectation to have things NOW, I think the fashion industry is going to need to shake up and change it’s model. Tools like Editd will help the industry make those steps forward.

  8. As a Fashion teacher at MODPSE Paris,on top of Running GOLD KALAA label,I am very interested to know more and add this into my Fashion Marketing courses!
    Annick Jehanne