H&M announced in March 2018, during its quarterly results, a huge problem: $4.3 Billion in unsold clothes. There are many causes of unsold inventory like a wrong collection/product, bad forecasting, wrong allocations, decrease in traffic, wrong prices… But, the trend has changed and the Swedish fashion retailer announced a 9% sales increase (VAT included), 32% online sales increase (Q3 Like-for-like) and total sales for the new brands increased by 20%.
Karl-Johan Persson, CEO of H&M, commented that “the most important aspect of our improvement work is to develop the assortment in line with customers’ increased expectations and to offer the best combination of fashion, quality and price in a sustainable way… We are therefore now scaling up this to more stores and markets. Our improvement work is benefiting from our investments in advanced data analytics and AI in areas such as quantification, allocation, pricing and trend forecasting“.
New H&M concept store in Karlaplan
Nowadays, technology is offering more and more tools to digest the amount of data that can be used to improve efficiencies across the value chain. Fashion Technology, or Fashtech, is redefining traditional retail business processes, skills and tools that will lead this new era.
These are some recent examples of how H&M is going Fashtech:
• H&M uses Artificial Intelligence to optimize the assortment: H&M is using big data and artificial intelligence to customize the merchandising mix of individual stores.
• H&M´s new fashion brand Nyden is transforming the standard design process into an “as-a-service design model“. Their objective is being closer to the customer and produce fresher collections. This means more than two collections a year.
• New curated store in Karlapan neighborhood in Stockholm, Sweden, with a customized local shopper assortment based on a larger selection of premium quality and trend items.
The latest news regarding H&M innovation is its $13M investment in Thread.
Thread is a menswear and womenswear e-commerce startup that uses online stylists, as well as artificial intelligence (AI) and machine learning, to create a personalised shopping experience.
How does it Work?
- Undertanding the customer profile: A list of Q&A helps Thread to know more about you.
- What are your favourite brands?
- Where do you shop?
- Which of those styles do you like?
- And for work?
- For a dinner or date?
- Budget by category?
- Size & Fit
- Stylist Recommendations: Every week, your stylist will fill your home page with clothes and outfits he or she thinks you’ll like. You can improve your recommendations by clicking to like or dislike items.
Selection of sizes and budget by category
- Browse and Essentials: If you’d like to see more options, use the Browse tab to see clothes in every category—still tailored to your budget, sizes and tastes. Or stock up on the Essentials, our stylists’ favourite staples you can mix and match and wear each season (and all year).
- Make the most of your wardrobe. You can do two things in your Wardrobe tab:
- Add some of your favourite clothes so your stylist can show you how to wear new items with things you already own, and
- Add things you’re looking for—like a white shirt or a new pair of jeans—and your stylist will concentrate on finding you a bunch of great options.
As commented in previous posts, the customization trend is going beyond a niche,cool marketing ad. Customization thru AI is building the new pillars of basics, not any more based on a standard profile but on a unique segment.
Function of beauty illustrates how a customized product could be a new basic for a customer. This means a product that will be ordered regularly, maybe in a monthly basis. It´s a long tail customized product that increases loyalty and also helps to understand new shopping needs, styles or trends. Artificial Intelligence will help Supply Chains to evolve from made-to-stock to segmentations.