prada SS24

How can fashion departments leverage runway analysis into actionable insights to cater to their market?

Key takeaways

  • While the Fashion Week runway showcases the vanguard of fashion, it is not where the story ends.
  • Heuritech's fashion experts study the latest runway styles and then analyse their adoption into the mainstream market using our AI-powered tool.
  • Through a series of key questions, this article explores how these data-driven insights assist various departments to leverage these insights coming from the runway.

Paris, Milan, New York, London… Each season, the spotlight shines on the glitz and glamour of Fashion Week, where designers unveil their latest collections. Yet, is the future of fashion solely determined by what graces the runways during these extravagant events? 

To be fair, even if it’s of great inspiration and often great market hits, at the end of the day, it is one thing that designers put on the runway and a completely another story of how consumers actually adopt it.

This is where Heuritech’s predictive data comes into play.

For a proper analysis, our Fashion Week insights are not coming from the styles spotted on the runway but rather from the future evolution of them on the market. 


Through a series of key questions, this article explores how these data-driven insights can assist buyers’ decision-making, empower marketing teams, inspire apparel brands to refine their strategies, guide the delicate art of collection balancing, and transform the world of visual merchandising.

Left: Prada

How can these data insights help buyers?

Buyers in the fashion industry can benefit from predictive data insights in the following ways:

  • Improved Merchandise Selection: Buyers can make more informed decisions about which styles to stock in their stores. By understanding consumer preferences, they can curate collections that are more likely to resonate with their target audience.
  • Reduced Inventory Risk: Predictive insights can help buyers avoid overstocking unpopular items, reducing excess inventory and potential losses.
  • Enhanced Stock Turnover and Effective Forecasting: Stocking popular items and anticipating demand early enable buyers to increase merchandise turnover rates and gain a competitive edge in the market, resulting in higher profits.

Using Heuritech’s SS’24 Fashion Week report as an example:

An easier way to understand this concept is through a simple statement: by using predictive data analysis, you can accurately predict what consumers will be interested in the future. 

For instance, according to our Fashion Week SS’24 report, see-through (+6% growth), polka dots, micro shorts, and corsets emerged as popular styles of the season.

Armed with this information, buyers have ample time to prepare and be ready to cater to their consumers the following year.

Image: Data from Fashion Week SS’24 Heuritech Report

Our report also provides data on materials, patterns, shapes, and accessories according to different buyer personas (mainstream, trendy, and edgy.)

It’s like having a crystal ball that can show you the evolution of the market. This advantage is significant because it eliminates the need for guessing and risky decision-making that was prevalent in the past.

FW 24 Women's Fashion Week Report

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Report | FW ’24 Women’s Fashion Week

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How can these data insights help marketing teams?

For marketing teams, these insights can be a powerful tool to:

  • Targeted Campaigns: Marketing teams can craft campaigns that resonate with the specific styles that data suggests will be popular, increasing the effectiveness of their marketing efforts.
  • Personalisation: Personalized marketing strategies can be implemented based on consumer preferences, driving engagement and conversions.
  • Content Creation: Data insights can guide content creation by focusing on the styles and elements that are expected to trend. This can lead to more engaging and shareable content.
  • Optimised Ad Spend: Marketing teams can allocate their budgets more efficiently by targeting ads and promotions toward the styles with the highest predicted demand.

Using Heuritech’s SS’24 Fashion Week report as an example:

Last year, pastel colours saw a decline of -3% for the SS’23, so it is likely merchandisers didn’t experience a big interest from consumers around those tones, so stayed away from them. 

However, for this season, SS’24, that would be a mistake.

According to our data, these shades, which, in fact, had experienced a decrease before, are expected to grow by +4% for the upcoming Spring season.

This increase extends to various pastel shades, except for Vanilla Yellow, signifying a resurgence of these soft and enchanting colours.

Image: Data from Fashion Week SS’24 Heuritech Report

Specifically for merchandising teams working on digital strategies, this signifies that it is a good time to start preparing content around pastels, to push that “our 5 pastels picks from our collection” TikTok video or newsletter, or even prioritise these hues for Influencer gifting.

Beyond this, having this foresight also helps merchandisers to prepare their campaigns in advance and communicate new collections based on styles that are ensured will be best-sellers.

How can these data insights help apparel brands?

Apparel brands can leverage these insights to refine their strategies:

  • Market Segmentation: Apparel brands can identify which styles are likely to gain popularity in different regions or cities. This enables them to tailor their offerings to specific markets.
  • Price Optimization: They can adjust their pricing strategies based on consumer demand. Premium pricing can be applied to highly sought-after styles.
  • Limited Editions: Apparel brands can create limited edition pieces based on data insights, making them more exclusive and appealing to high-end consumers.
  • Partnerships and Collaborations: By understanding future trends, apparel brands can engage in collaborations with designers or influencers to create unique collections that align with the predicted popular styles.

Using Heuritech’s SS’24 Fashion Week report as an example:

Paris Fashion Week collections may say something, but consumers in China don’t necessarily have to listen. 

Having a successful style that works for one market doesn’t ensure it would work on the rest. For instance, our analysis of SS’24 Fashion Week said:

In Europe, data shows patterned dresses will be a big hit, with a 14% growth, it almost promised to be a best-seller. 

However, how will this style perform in China? Heuritech’s data shows a decrease of -2% for patterned dresses in Chinese female consumers. And even more, for USA female consumers for SS’24, we expect a -8% decline.

Image: Data from Fashion Week SS’24 Heuritech Report

Using the insights derived from the data, brands which cater to the European market can now strategise for SS’24 by launching a limited-edition collection focusing on patterned fabrics. 

However, it is advised to implement a different strategy for Chinese and US markets, as consumers in these regions are expected to be less receptive.

These data insights help apparel brands focus on the styles that will be popular in each market instead of wasting efforts on wrong offerings.

How can merchandisers balance a collection with predictive data insights?

Balancing a fashion collection is crucial to appeal to a broad audience. Data insights can help in the following ways:

  • Diversity in Styles: Data can guide the inclusion of a variety of styles, from mainstream to trendy, to cater to different consumer preferences.
  • Consumer-Centric Approach: Balancing a collection means ensuring it caters to the various tastes and needs of consumers, which data can inform.
  • Stock Allocation: Insights can help determine how much inventory to allocate to different styles within a collection, avoiding overemphasis on a single style.

Using Heuritech’s SS’24 Fashion Week report as an example:

Basing decisions on Heuritech’s data insights from Fashion Week makes it easier to balance a collection by providing a deeper understanding of how each consumer segment will adapt styles, allowing brands to plan inventory accordingly. 

As an example from our SS’24 report, metallic tones are taking a prominent place on the runway, making it a good bet for brands catering to diverse targets. 

But some metallics will be more popular than others. Our experts consider metallic pants a rising star, with a +7% growth compared to last year. For a safer option, brands should focus their metallic offerings around pants.

Image: Data from Fashion Week SS’24 Heuritech Report

To complement the collection, metallic tone tops would also be a successful addition. With a +4% growth in Europe vs SS’23, our experts consider them a consistent riser as their popularity continues to grow. 

According to our predictive data, the less popular choice would be metallic tones skirts, with just a +1% growth. However, this doesn’t mean they should be avoided entirely, but allocating less inventory of this style will be a safer choice. 

This information is crucial for inventory planning as the promised best sellers should be the priority and keep less safer options for smaller offerings.

How can these data insights help visual merchandising?

In the specific case of visual merchandisers can benefit from predictive data insights in several ways:

  • Store Layout and Display: Data can inform how to arrange and display merchandise to highlight the predicted popular styles, making them more visible to customers.
  • In-Store Promotion: Styles and themes with high predicted demand can be promoted through window displays and in-store marketing materials.
  • Stock Rotation: Data insights can guide the rotation of stock and displays to keep the store fresh and in line with evolving consumer preferences.

Using Heuritech’s SS’24 Fashion Week report as an example:

During the SS’24 Fashion Week, Heuritech’s experts presented the season’s key themes. 

One is called “Bold Blends: Where Delicacy Meets Daring”. This theme is about blending masculine and feminine aesthetics by combining robust, utilitarian materials with ultra-feminine codes.

Visual merchandisers seeking to attract consumers to stores may want to play around with this theme, already expected to be popular, by creating storytelling that catches people’s attention.

By leveraging the data insights provided by Heuritech, they know that for representing this theme, the key colours to consider are Taupe, with a +2% growth in Europe, and Khaki, with a +1% growth.

Image: Data from Fashion Week SS’24 Heuritech Report

In terms of shape, oversized jackets continue to be a consistent riser. With a +11% growth compared to last year, they offer the ideal balance between masculinity and femininity by being paired with soft dresses and mini skirts.

Another shape to consider is wide-leg trousers. With a +4% expected growth in Europe, these masculine bottoms can be paired with body-revealing tops and ultra-feminine blouses, creating a striking blend of styles that characterise this theme.

Image: Data from Fashion Week SS’24 Heuritech Report

Leveraging this information provides visual merchandisers insights into presenting store collections to successfully reflect the theme behind it and catch consumers’ interest.

With this article, we wanted to address how Heuritech data insights can assist various departments within a brand. 

In the case of Fashion Week, it is more complex than just analysing and counting the numbers of what was presented on the runway; a proper market analysis also requires understanding how the consumers will respond to it and adopt it. 

Thus, predictive data solutions such as Heuritech are crucial.

Only this level of data analysis is instrumental in enabling fashion and sportswear brands to cater to consumers’ preferences successfully as it goes beyond just what was spotted; it is a complete analysis of the fashion market’s future.

Would you like to learn more about our solution? Don’t hesitate to contact our team.

Macarena fashion content manager

About the writer: Macarena Blanco, Fashion Content Manager

Macarena writes about the fashion industry with a focus on data analytics and technology, with the aim to achieve more sustainable solutions.

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