By Diletta Bortesi, Marketing Director, Fashion & Lifestyle, at Studio Mirari.

Anticipating Uncertainty and Managing the Tariff Impact While Preserving Premium Brand Positioning

If you’re an Italian fashion brand selling in the U.S., chances are you’ve found yourself wondering:
How should we respond to rising tariffs? Should we increase prices? Cut margins? Leave the market altogether?

In spring 2025, these questions became pressing when the U.S. announced potential new duties on Made in Italy apparel. For brands with significant exposure to the American market, the implications went far beyond pricing, they threatened long-term brand perception and customer loyalty.

In this article, we’ll walk you through a real case: a premium Italian fashion brand (with 100% production in Italy) facing this exact challenge. The approach we took, a multi-tiered plan that combined communication strategy, pricing intelligence, logistics and market diversification, offers a model you might find helpful too.

The Challenge: How to Stay Premium Without Losing Customers

Tariffs create a domino effect: production costs rise, prices may need to increase, and customers, especially in the premium and affordable luxury segments, can be quick to walk away.

While some brands chose to pass the cost onto the customer through price hikes, that strategy is risky: it can erode trust and dilute the brand’s value proposition, especially if not handled with care.

Deloitte forecasts show that rising tariffs could significantly dampen U.S. consumer spending in the coming years, highlighting the long-term risks of relying solely on price increases. ¹

¹  Tariffs will impact the economy … and so will uncertainty – Deloitte.com

Meanwhile, new data from Vogue Business (July 2025) confirms that U.S. apparel prices are already rising, with handbags showing some of the steepest increases: Burberry (+12%), Bottega Veneta (+8%), Louis Vuitton (+5%). T-shirts and sunglasses are also climbing across top brands, while only sneakers and wool coats remain stable. As pricing pressure intensifies, even affluent consumers are starting to scale back spending.²

² “Tariffs’ impact on fashion is finally here — here’s what the data shows”, Vogue Business, July 18, 2025.

This highlights the limits of relying solely on price hikes to absorb the cost of tariffs. The goal here was to stay premium, preserve customer trust, and avoid panic, all while building resilience.

Objectives

• Preserve relationships with U.S. customers
  
• Limit the potential financial impact of tariffs
  
• Strengthen the “Made in Italy” brand positioning
  
• Activate alternative strategies to offset potential market losses
  

A Multi-Level Response

1.Direct, Calibrated Communication with End Customers

Rather than staying silent or going full alarmist, the brand added a subtle banner to its U.S. site:

“Shop before it’s too late: your favorite Made in Italy brand may be subject to increased duties.”

It was just enough to prompt action, without creating anxiety. Messaging in email and social channels reinforced this with a sense of exclusivity and timing, rather than fear.

2. Reinforced the Brand Story

Email campaigns targeted at U.S. customers were redesigned to spotlight:

• the craftsmanship behind Made in Italy,
  
• the uniqueness of their production model,
  
• and the opportunity to buy before macroeconomic changes took effect.
  

By weaving these elements into a compelling and authentic narrative, we not only reinforced the brand’s positioning but also encouraged immediate engagement. Remember: consistent storytelling remains one of the most powerful tools for building long-term brand equity.

3.New Market Scouting and Strategic Budget Reallocation

Recognizing the need for geographic diversification, the brand launched test campaigns in receptive markets such as Canada, Australia, and the Middle East. This was made possible by a new digital strategy that included:

• shifting focus away from top-of-funnel activity in the U.S.
  
• reallocating budget toward acquisition campaigns in target markets,
  
• using these campaigns to test resonance, price elasticity, and messaging effectiveness to support future distribution opportunities.

By exploring new geographies with agility and strategic intent, the brand positioned itself to mitigate risk and build resilience over the medium term.

4. Strategic Pricing Adjustments and Smarter Shipping 

We didn’t just raise prices across the board. Instead, we:

• adjusted pricing on selected SKUs, avoiding distortions compared to other markets,
  
• optimized shipping and returns costs to preserve customer trust and perceived value on the product
  
• and bundled offers where it made sense ensuring overall business sustainability
  

The goal was to absorb part of the tariff impact while keeping the customer experience seamless.

5. Improved Logistics with a U.S.-Friendly Model

To avoid delays and keep costs down, the brand considered:

• warehousing inventory at wholesale value in the U.S.,
  
• experimenting with on-demand shipments: grouping orders in Italy, shipping in batches to the U.S., and fulfilling locally.
  

This allowed to maintain a seamless and unchanged shopping experience for customers, while improving delivery speed and lowering duties.

The Results

This strategy helped the brand achieve several medium- to long-term goals, including:

• Maintaining a stable performance in the U.S. despite the tariff pressure,
  
• Strengthening brand trust among customers through transparent and timely communication,
  
• Increasing net U.S. revenue by +22.2% YoY, with a +32.3% peak in May 2025,
  

Laying the foundation for sustainable growth in new markets.

Monthly growth in U.S. direct-to-consumer sales throughout 2025

Key Takeaways for Fashion Brands Facing Tariff Pressure

1. Start communicating early but keep it calm, clear, and customer-first.
   
2. Reinforce your brand story, because price adjustments alone won’t win.
   
3. Don’t panic-price, adjust carefully, strategically, and only where needed.
   
4. Use testing to prepare new markets for scalable growth.
   
5. Optimize logistics creatively to cut costs without killing your D2C model.
   
6. Turn the challenge into a brand moment: transparency and agility build long-term trust.
   

If you’re facing similar questions in your organization, we hope this case gives you some good inspiration. Tariffs may be outside your control, but how you respond can shape your brand’s future.

About the author

Diletta Bortesi is a Marketing Director with 20+ years of experience in marketing and communications, focused on the Fashion & Lifestyle sectors. She brings a 360-degree perspective to the field, combining strategic vision with hands-on expertise.

About the author: Lorenzo Bortolotto, Alpenite

Lorenzo Bortolotto is an expert in innovative technologies, with long experience in the ERP, business processes, eCommerce, web portals, AI and Web3.0 sectors. Thanks to his technical and business skills, his ability to communicate and listen, Lorenzo helps decision makers choose the solutions best suited to their needs, accompanying them in the implementation and adoption of high added value projects. Over the years, Lorenzo has collaborated with hundreds of companies, creating customized workshops and demos, for all organizational levels, with the aim of promoting the understanding and transformation of processes and technologies, and stimulating the awareness necessary to make informed decisions and overcome the limit of “Never invest in a business you can’t understand”. –Warren Buffett

What is Predictive Analysis and Why is it Important for Your E-commerce?

Predictive analysis is the use of data mining, statistics, and artificial intelligence techniques to analyze historical and current data and predict the future behaviour of customers, markets, and processes. For an e-commerce business, predictive analysis can be a valuable tool to optimize inventory management, determining the quantity and types of products to stock to meet demand.

Optimal inventory minimizes storage and procurement costs, avoids stockouts and excess inventory, and maximizes sales and profits.

How Predictive Analysis Works for Inventory Management

Predictive analysis relies on machine learning algorithms that learn from past and present data to generate forecasts on various aspects of demand, such as volume, seasonality, segmentation, price sensitivity, and promotions. These predictions can be used to calculate the optimal inventory level for each product based on factors like probability of sale, purchase cost, profit margin, delivery time, expiration date, etc. Additionally, predictive analysis can help identify the most profitable products, emerging trends, cross-selling and up-selling opportunities, and the most effective pricing and marketing strategies.

Advantages of Predictive Analysis for Your E-commerce

Predictive analysis can bring numerous advantages to your e-commerce, including:

1. Reducing inventory management costs by avoiding waste, losses, damages, and obsolescence.
2. Increasing sales and profits by offering the right products at the right time and price.
3. Improving customer satisfaction and loyalty by ensuring the availability of desired products and swift deliveries.
4. Optimizing strategic decisions based on reliable and up-to-date data.

Implementing Predictive Analysis in Your E-commerce

To implement predictive analysis in your e-commerce, you need to:

1. Have an e-commerce platform that allows you to collect and integrate data from various sources such as the website, social media, customer feedback, suppliers, competitors, etc.
2. Use a predictive analysis solution that suits your needs, budget, and level of expertise. Choose from cloud, on-premise, or hybrid solutions, and ready-made or custom solutions.
3. Define goals and metrics for predictive analysis, monitor results, and performance.
4. Test and validate predictions by comparing them with real data and customer expectations.
5. Act based on predictions by adapting inventory management, pricing, and marketing strategies.

Moreover, having an experienced partner in predictive analysis projects is often a competitive advantage. Such a partner can offer qualified and personalized consultation, supporting the client in every project phase—from defining the problem and goals to selecting the most suitable solutions to implementation and maintenance, ensuring quality, security, and effectiveness.

Predictive analysis requires continuous model verification to ensure they are updated, aligned with reality, and in line with business objectives. A dedicated team can monitor model performance, detect anomalies or deviations, and make necessary adjustments to optimize results.

Lastly, a partner can provide the necessary skills for managing and using the predictive analysis solution through training, assistance, and knowledge transfer, making the client independent in system management to fully exploit predictive analysis potential for their business.

A real Use Case example

Now, let’s present the use case of Modayola, a multi-brand online platform offering high-quality clothing and accessories.

Before describing Modayola’s benefits and results, it’s essential to note that Modayola is a fictional name used to preserve the company’s privacy, with a non-disclosure agreement (NDA) in place to protect the competitive advantage derived from the investment in predictive analysis.

Modayola faced the challenge of managing an extensive and diverse catalog with thousands of products from various suppliers. Additionally, it had to consider the ever-changing and heterogeneous purchasing preferences and behaviours of its customers.

To tackle this challenge, Modayola turned to Alpenite, a company within the Arsenalia group specializing in AI applied to the e-commerce sector. Alpenite’s idea for Fashionista was to create a predictive system integrated with e-commerce and the company’s ERP, utilizing artificial intelligence to anticipate the demand and supply for each product, streamlining the purchasing process from various suppliers.

The project unfolded in several phases.

1. Initially, Alpenite studied the process and collected and analyzed Modayola’s historical and current data related to sales, inventory, costs, suppliers, customers, feedback, and marketing campaigns.
2. Next, Alpenite constructed and trained predictive models using machine learning and deep learning techniques to generate accurate and reliable forecasts for various aspects of Fashionista’s business.
3. Finally, Alpenite integrated the predictive models into Modayola’s ERP, creating interactive dashboards and automatic alerts to facilitate decision-making and action.

Predictive analysis brought significant benefits to Modayola. After the first year, online revenue increased by approximately 20%, while profit margin increased by 10%. It was able to reduce waste and excess inventory, optimize collaboration with suppliers, and also respond more accurately to customer needs.

Alpenite, part of the Arsenalia Group, is an innovative consulting firm that empowers businesses to achieve excellence throughout every stage of the customer experience journey. Together with Alpenite, companies shape the future of their business by developing a digital strategy that aligns with business expectations and with the brand promise; designing, building, and evolving digital solutions to deliver exceptional experiences; and managing digital processes that amplify the value of the business and enhance its performance.