For Designer Fashion Brands, Data-Driven Partnerships are a Survival Issue
TL;DR — The fashion industry is struggling, but stronger partnerships (via better data) are coming to the rescue.
Anyone who’s worked in the fashion industry knows that relationships between designer brands and retailers can be difficult to navigate. Enormous time and energy are spent evaluating partnerships and renegotiating agreements. Minor issues, particularly around pricing, can spiral into major disputes.
But this model is failing. In the last few years, we’ve seen powerhouse brands crumble and retail chains shutter. There are three main reasons to consider.
Reason 1: Shoppers have the power
In 1997, fashion consumers had no knowledge of prices or styles beyond their local department stores. In 2017, a shopper can try on a skirt by a French designer in a Dubai department store, compare prices on her phone in the dressing room, and have it express-shipped from an Australian retail competitor at half the cost, later that day.
In other words, fashion has entered the age of global e-commerce transparency.
If there’s a weakness in your distribution chain, shoppers will find it. And if your prices aren’t competitive, shoppers will go elsewhere. This puts a lot of upward pressure on fashion companies, straining business relationships.
Reason 2: Stakes are high for everyone
Fashion brands avoid unnecessary discounting at all costs, and for very good reason. If that Australian retailer is pricing the skirt too low — whether intentionally or not — it can steal an unfair share of the market. To avoid being stuck with excess inventory, the Dubai department store might discount the style and negotiate markdown allowances, cutting into the brand’s margins. By triggering this ‘race to the bottom,’ a single rogue retailer can ruin a brand’s entire season. If it happens often enough, it can even sink the brand.
By triggering this ‘race to the bottom,’ a single rogue retailer can ruin a brand’s entire season. If it happens often enough, it can even sink the brand.
Retailers are walking a similar tightrope. If other retailers are setting lower prices, consumers will flee, leaving them holding unsold inventory. Facing seasonal turnover, their only option is to dump it on the market at discount rates, taking a substantial loss. The brand’s prestige is damaged and nobody wins.
Without better data, simple misunderstandings will continue to escalate into major issues that drain everyone’s resources.
Reason 3: Fashion pricing is hard. Really hard.
So why do brands and retailers struggle to know whether their partners are dealing with them fairly? Just think about the onslaught of data they’re facing.
A mid-sized fashion brand might offer thousands of SKUs, most of which turn over seasonally. Multiply each of those items by dozens of retailers, and factor in seasonal, monthly, weekly, or even daily price adjustments. Then factor in sales, promotions, discounts, different markets and languages, and currency exchange rates.
The resulting dataset is large and volatile. No human being can wrap their heads around it, much less boil it down into a clear action plan. Most fashion businesses are behind the times technologically to begin with. They’re still manually gathering data, relying on Excel spreadsheets, historical reports, and educated guesswork to inform their business decisions.
Adapt, or be left behind
So that’s the old model: Brands and retailers build high-stakes relationships under heavy financial pressure, with virtually no market intelligence.
But not every fashion business is clinging to this failing approach. A small (but growing) group of thought leaders in the fashion industry are rolling out cutting-edge technology to get the intelligence they need. And not coincidentally, many of them are reporting strong financial results recently.
How is this possible? And why has it taken so long?
Tech created this problem, and tech can fix it
This solution is fairly recent for a good reason: The technical challenges are enormous. Fashion has more SKUs and more seasonal turnover than any other vertical in retail. Styles are marketed with conflicting codes, inconsistent language, and varied photography. But (with enough determination and resources), it is now possible to make data-driven pricing and merchandising decisions, globally, in real-time.
This is a seismic shift for the industry. At Ragtrades, we’ve had a front-row seat to these changes. Businesses are now asking questions that were historically unanswerable due to inadequate data. For example:
- When exactly did retailer X sell out of our 5 top-selling styles in Japan?
- Is retailer Y undercutting us in all markets, or just in Japan and Australia?
- Did retailer Z lower their European prices yesterday, or was that an exchange rate fluctuation?
But tactical pricing and merchandising decisions are just the beginning. With the arrival of global market intelligence, fashion companies are changing their whole approach to partnership.
Better data, better priorities
Extremely precise, data-driven discussions are now a reality for brands and retailers. Instead of getting hung up on anecdotes or statistical anomalies, they can identify exactly which pricing factors (e.g. global premiums, exchange rates, discounts) are affecting their bottom lines. They can reach mutually beneficial agreements around merchandise flow, and nail down markdown cadences that work for everyone.
In other words, we’re seeing the inception of the data-driven partnership. And it will soon become a criterion for fashion companies selecting new partners. Retailers will choose brand partners who are tuned into the market landscape and use data proactively. Brands will hunt down retail partners who optimize their market performance, fine-tuning prices on the SKU level and discounting inventory only when it makes sense.
To put it simply, data-driven partnerships are more stable, more efficient, and more profitable than anything we’ve seen before.
To put it simply, data-driven partnerships are more stable, more efficient, and more profitable than anything we’ve seen before. The brands and retailers savvy enough to ride this wave — whether they’re traditional department stores or nimble young brands — will claim an outsized role in fashion’s future.
This is just one way data is transforming the fashion industry. Coming this winter, we’ll discuss how AI is revolutionizing buying and merchandising, how shipping and duties factor into pricing, and more. Stay tuned.
Visit Ragtrades.ai to request a demo or learn more about Ragtrades.
