In the 1990s, a fashion trend could last for years. Bootcut jeans reigned for nearly a decade. Retailers had the luxury of time — time to observe what was happening on the runways, time to study what was selling in flagship stores, and time to react through careful merchandise assortment planning cycles.
In today’s market, that luxury no longer exists.
Driven by social media, algorithmic influence, and rapidly shifting consumer behaviors, we now live in a world of microtrends — aesthetic waves that emerge seemingly overnight, dominate the digital conversation for a week or two, and then vanish. A product once expected to sell steadily for months might now spike in demand for just a few days, only to stagnate before it even hits the shop floor.
Retailers haven’t just lost control of the trend cycle. In many cases, they’ve lost the visibility and agility needed to keep up with it.
How the Trend Cycle Got Shorter
To understand what’s changed, we need to look at the evolution of how trends used to be created and distributed. In the late 20th century and early 2000s, the trend cycle was governed by a relatively small number of players. Fashion designers, glossy magazines, television shows, and celebrity endorsements all played a role in determining what was “in” — and that determination often held firm for several quarters, sometimes longer. Consumers were slower to shift preferences, and retailers could plan assortments confidently using data from previous seasons.
Today, the process is inverted. Platforms like TikTok, Instagram, and YouTube have decentralized trend creation. Consumers themselves — especially younger ones — are driving trends through content creation, product hauls, and viral commentary. Entire aesthetics can emerge from a 15-second video. Suddenly, a specific shoe, shade of blush, or type of handbag becomes the “it” product — not because it was featured in Vogue, but because it was worn by someone with a loyal digital following.
Gen Z consumers are significantly more experimental in their buying behavior than previous generations. According to McKinsey, 62% of Gen Z shoppers say they would still check out other options even if they have a favorite brand, and more than half would switch if a different brand offered better price or quality. This fluid sense of loyalty is matched by a preference for discovery-driven shopping.
In a separate McKinsey report, Gen Zers were found to make purchases on social media four times more often than older generations. Unlike older consumers who tend to research or buy through traditional retail channels, Gen Z often encounters products passively — through influencer content, trending videos, and algorithmic recommendations. Platforms like TikTok, Instagram, and YouTube are not just marketing channels for this generation; they are active storefronts. This shift has dramatically accelerated how trends emerge and fade, making real-time visibility and responsiveness critical for retailers.
In this new environment, visibility is fleeting, and momentum is fragile. By the time a trend is obvious in sales data, it may already be fading.
Image Source: TikTok Newsroom – “Introducing TikTok Shop“
From Viral to Vanished: Real Examples
Recent Gen Z-driven trends triggered unexpected demand spikes, throwing established assortment plans off course – let’s look at a few examples.
Maybelline’s Lash Sensational Sky High Mascara is one example. After a handful of beauty influencers posted TikTok reviews in early 2021, it sold out 5 times across major U.S. retailers within days. The product became a top-seller, restocked multiple times, and gained international popularity – all driven by social momentum, not a traditional campaign. However, like many viral sensations, the initial hype eventually cooled. Sales normalized, and retailers were left managing the tail end of a demand spike that didn’t follow a predictable curve.
Prime Hydration Drink, launched by YouTubers Logan Paul and KSI, followed a similar path. The drink became a status symbol among teens and Gen Z consumers almost overnight. Resale prices soared. By 2024, UK sales had dropped by nearly 50%. The brand was still selling, but the frenzy was over – and with it, the risky guesswork that comes with viral trends.
In both cases, the product succeeded. But the demand curve was anything but linear, and for retailers trying to plan inventory, that’s the real challenge.
Why Traditional Assortment Planning Falls Short
Assortment planning, a cornerstone of successful retail, involves selecting the right mix of products to meet anticipated customer demand: by category, price point, colour, size, location, and within budget.
Many retailers still rely on outdated assortment planning approaches that are slow, top-down, and overly dependent on last year’s data. That approach may have worked when assortment planning was guided by predictable seasonal cycles. In today’s accelerated environment, however, that rigidity becomes a liability.
A product that becomes popular on Monday may be irrelevant by Friday. Relying solely on historical data, annual forecasts, or intuition is no longer practical. Traditional assortment planning tools and methods are not designed to handle the speed, complexity, or unpredictability of the current retail landscape.
The results are familiar: too much of the wrong product, not enough of the right one, misalignment across channels, and increased dependence on markdowns to clear unsold stock.
Retailers are not just missing demand. They are absorbing the financial fallout of poor timing.
The Role of Modern Assortment Planning
Assortment planning must become more dynamic and responsive to keep pace with rapidly changing consumer behavior. This doesn’t mean abandoning foundational retail practices. It means enhancing them with real-time data, predictive modeling, and smarter tools.
Modern assortment planning platforms help retailers:
- Detect early signals of emerging trends
- Model various buying scenarios before committing to inventory
- Decide how deep to go into a trend without overcommitting
- Adjust assortments continuously, not just at fixed intervals
Modern solutions, such as Retalon’s assortment planning software, don’t just show what’s trending — they simulate how that trend might perform across regions, channels, and customer segments. Planners can run “what-if” scenarios to see how different depth levels, timing windows, or store allocations might impact sell-through and margin. They can monitor real-time demand signals — like sales velocity, social media mentions, or localized traffic patterns — and make mid-cycle adjustments, such as redistributing inventory or delaying reorders. These capabilities reduce the lag between trend emergence and retail response, helping teams act faster without relying on guesswork.
These systems allow retailers to act earlier, adapt faster, and reduce risk. The goal is not to chase every trend, but to distinguish which ones are worth pursuing and how far to go before scaling back.
Forecasting the Unpredictable
Many retailers treat demand forecasting and assortment planning as separate activities. That is not the case.
When predictive forecasting solutions are integrated into assortment planning, retailers gain a clearer view of both demand potential and trend volatility. They can simulate what happens if a product takes off, or fizzles, and build flexible strategies accordingly.
This is especially valuable in trend-sensitive categories like beauty, apparel, accessories, and consumer electronics. Even a short delay can turn a viral winner into dead stock.
With predictive insight, planning teams can make more confident decisions about not just what to stock, but how much, where, and for how long.
Assortment Planning in Fashion: Why Agility is the New Advantage
In this environment of more connected, more experimental, and more impatient consumers, Retailers that want to stay relevant and profitable need to rethink their approach.
That starts with moving beyond static, historical planning – toward intelligent, adaptive AI-driven systems.
If you’re looking for a more agile assortment planning software, get in touch with our experts to learn more.
About the Author
Marina Krupnik is a Marketing Specialist at Retalon, where she turns complex retail tech into stories that actually make sense—and sometimes even make you smile. With a background in Honours Psychology from the University of Guelph, she’s fascinated by what makes people tick (and click). Whether she’s decoding buyer behavior or translating AI-speak into plain English, Marina is on a mission to make cutting-edge innovation feel refreshingly human. 
