Spotlight On: Market, Trend, And Competitive Analysis

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Looking across the industry to see what the competition is doing, and then peering over its parapets to put a finger on the pulse of culture, is the way fashion has always worked. Brands and retailers have long recognised that they vie against one another for a share of discretionary spending, just as readily as they’ve understood that fashion is anchored in the zeitgeist in a way that few other industries besides music and art are. So earning that share, at least for the majority of companies who are not culture-defining in their own right, has always been a matter of identifying change, predicting or sensing demand, and then, as far as possible, compressing the time it takes to create products that meet the market at just the right moment.

There is a Wayne Gretzky quote, beloved of Apple Co-Founder Steve Jobs, and potentially misattributed given it came from Wayne’s father, Walter. Regardless of its provenance, it captures the essence of what trend, market, and competitive analysis is all about: skating to where the puck is going to be, not where it’s already been. Or, in other words, being able to identify where the world, the wide spectrum of commodity prices, the changing climate and much more is all headed in advance, and then getting there ahead of the competition – ideally with product that hits the right bars of quality and price along the way.

But while that strategic ambition is arguably the oldest trick in fashion’s book, the discipline of parsing the outer world, forecasting what it’s going to want, and then mapping that to products that are feasible to create within the constraints of material and production availability, looks barely recognisable today relative to how it looked less than a decade ago.

Today, fashion organisations are not only working to very different definition of the axiomatic labels for this category – market, trend, and competition – but also working with a set of tools, channels, and data sources that seem pitched more at data scientists than the creative, artistic cohort that planning, merchandising, buying, and design teams typically consider themselves to be.

Consider the competitive landscape first. What used to be something the typical brand could physically travel to, on a buying trip or by walking the thoroughfares of their nearest retail destination, is now a heterogenous and extremely diffuse mix of different players who each specialise in different channels, and whose value proposition to consumers has become increasingly blurry. Mid-market brands are pursuing “premiumisation” strategies, elevating their collections and their prices. Luxury is splitting into accessible and “ultra-luxe” lanes. The definition of “value,” too, has been redrawn multiple times in a compressed window, and is continuously being sketched over today as costs of living spiral to different degrees, in different markets.

And the levers that companies have in front of them, available to pull, are all, themselves, counterweighted by constraints. From raw material inputs to manufacturing capacity, resources are either becoming scarcer or more expensive to secure. Price elasticity is becoming progressively narrower and more brittle, as the consumer market’s willingness to absorb higher costs dwindles, and margin targets are under threat. And as a direct consequence, the pressure on each individual style to succeed is both acute and more difficult to deliver against than at any point in recent memory; and with such long lead times (a typical nine to twelve months to bring a product to market)  playing the odds, and accepting a high failure rate in order to find a narrow set of bestsellers that will amortise margin pressure across an assortment, represents a profound risk. 

Across essentially every category bar luxury, fashion companies are also facing disruption from a new class of competitors who seem to be playing a fundamentally different game. Ultra fast, high-volume international operators like SHEIN can, effectively, ignore many of these constraints as a function of their sheer scale and volume. Their own direct competition is minimal (albeit fierce, as ongoing legal battles attest). They have the ability to brute-force trend acuity by simply introducing thousands of styles in the time traditional companies make single digit assortments. And they operate, according to governments on both sides of the Atlantic, in a market that’s unfairly tilted in their favour, benefitting from import duty exceptions, preferential state treatment and subsidies in their home countries, and imbalances in take-home wages and cost of living between different geographies.

In a meaningful sense, what it means to compete in mass market fashion is fully up for grabs, and this has markedly extended the scope of what brand and retail businesses want from the technology they use to benchmark the competitive landscape. The value return of this cohort of solutions is being measured more directly on the bottom line – giving the right platforms a clear-cut ROI, and shrinking the timeline by which the wrong tools will end up being discarded.

Then consider the fashion market, in the sense of the buying public. According to the Business of Fashion, growth is currently forecast to remain in the low single digits worldwide, putting a cap on the industry’s ambitions to grow the pie as a whole, rather than just their share of it. At the same time, spending that would have been fashion’s to swallow in the past is now finding its way onto the plates of sectors like entertainment, travel, and experiences. With price sensitivity on the rise at one end of the value spectrum, and demand for high-end differentiation escalating at the other, brand loyalty, too, is hard-won and even harder to keep.

And “the market” is no longer synonymous with the sale of new clothing. Resale is forecast to grow 2x or 3x quicker than first-hand as we barrel towards 2027. Brands and retailers are, rightly, concerned about that uptick cannibalising their trade in new garments, but they also – again rightly – do not want to cede ownership and control of that secondary market to third parties and intermediaries.

So as much as fashion is struggling to reckon with a new definition of what it means to sell against the competition, the industry is also staring down a very definition profile of who it’s selling to. Here, again, the pressure is on technology to deliver meaningful, real-time insights. The platforms that can deliver this will earn hooks into the most pivotal decisions that are being made, and re-made in response to changing circumstances, 

Finally, the very concept of a trend is becoming harder to pin down. Where once cultural signals were gatekept by editors and creative directors, social platforms have now both decentralised the authority and industrialised the fad – making it harder than ever to distinguish a passing fancy from an enduring shift. The forecasting profession draws this line clearly. Speaking on The Interline Podcast earlier this year, WGSN CEO Carla Buzasi described the difference between fads, which “come and go really, really fast”, amplified because they make good headlines, and trends, which, by definition, have measurable longevity and volume.

As part of the same interview, Busazi also articulated a caution to brands that see matching the pace of the trend cycle as essential to remaining competitive. “Sometimes being the first to market is not the place that you want to be,” with intentionality of decision-making superseding the intuitive drive to simply make everything the market might want.

But if the tools that brands rely on to understand the competitive landscape, the market, and the notion of what constitutes a trend are assuming a heightened importance, the data underneath those tools is arguably even more valuable – but also more precarious. Real-time data is available everywhere a company chooses to look, from social movements to scraped promotions, and the ability to separate the signal from the noise is now, effectively, beyond the capability of human beings… unless they are aided by machine learning tools and AI, both of which have become fundamental parts of every software product that caters to this market segment. 

This is something that Centric Software refers to as a “360° view of the entire market”, and that its case studies suggest can realise up to 12% increase in average initial price points.

This is something that Centric Software refers to as a “360° view of the entire market”, and that its case studies suggest can realise up to 12% increase in average initial price points.

This trend towards planning, pricing, and product decisions being made on the basis of AI-derived insights and data is also effecting a change in the userbase for market, competitive, and trend analysis platforms – encompassing but also extending beyond core teams. Where once these tools were purposefully calibrated for planners, merchandising teams, and similar end users, now the same insights can be surfaced through natural language interfaces for a much wider range of stakeholders across different stages of the product journey.

This does not, we must note, mean that every stakeholder at every brand is supported by the right culture to actually act on the insights that are put in front of them. Much as has happened in software engineering, where the prevailing assumption is that executing on ideas is no longer the bottleneck, and actually having the right ideas to begin with is, simply acquiring the platforms that can support companies in such a fast-changing market is just the beginning step.

Our guidance for companies evaluating the mature solutions that make up this category, then, is to take the shifting foundations of market, trend, and competition as a given, and to then distinguish between the idea of “data tourism” (simply surfacing more insights) and the reality of reorienting operations to take advantage of a way of working that’s more aligned with reality and less anchored in the outdated notion that fashion can afford to dictate rather than listen before acting.

In practice, this means better, deeper, and more fully-rounded connections between the disciplines that are directly covered in this market segment and the wider technology estate, from PLM to eCommerce.