Artificial intelligence (AI) is rapidly changing the fashion industry. While some companies are taking a wait-and-see approach, others are taking bold steps forward.
In the fifth part of the “AI in Fashion” series, FashionUnited speaks with Gordon Smit, head of technology at the Dutch lingerie company Hunkemöller.
How do you see AI and what does Hunkemöller use it for?
AI has become essential in modern organizations, especially in the fashion industry. Companies that are not yet working with AI are falling hopelessly behind. In order to remain competitive, AI must be firmly anchored and continuously developed.
Our data team has grown from three to twelve people in a year and a half. We use AI across our entire value chain. This ranges from product development and design to sales and analysis.
Do you have any concrete examples?
We are currently experimenting with 3D design in the design phase. By viewing products completely digitally and in 360 degrees, we can dramatically reduce the number of physical samples from Asia. Our goal is one pattern rather than four or five per design/style. This saves time and costs.
AI also helps us with image classification. Lingerie photos sometimes show a lot of skin, so Google often classifies them as “adult content.” This negatively affects our ability to be discovered. Using AI, we can predict which photos are likely to be rejected and which are safe to post online.
Another important application is price elasticity. Take Black Friday for example. We used to intuitively start offering discounts in November. Today we are taking a completely data-driven approach. Machine learning-Models determine exactly when a product should be reduced and by how much. This has been proven to lead to better margins.
We also use AI for customer feedback. Together with Google, we developed a tool that automatically translates hundreds of thousands of reviews and measures sentiment. This allowed us to uncover customers’ biggest frustrations and respond to them immediately.
We are also working on branch clustering. The AI identifies which branches serve similar customer profiles. By grouping the stores based on data, the product range per cluster can be tailored much better. These analyzes sometimes require processing billions of records. A task that was impossible to do manually.
What has this AI journey brought so far?
Hunkemöller has undergone a major data transformation in recent years. We had over 25 different data sources. These were brought together into a single central database three to four years ago. We were sitting on a data goldmine, but we couldn’t access it yet. Bringing all these sources together was a huge task, but now we are reaping the rewards. It gave us new information, such as patterns in purchasing behavior through store clustering.
The next step is to really activate all of these new insights, like we did with customer feedback.
What lessons have you learned and what are the challenges?
The most important lesson is that the master data must be in order. If the data is wrong, it remains “shit in, shit out”. For example, for price elasticity and store clustering, we had to significantly optimize our data. It took us two years of blood, sweat and tears to create a solid foundation.
Another major challenge with AI lies in its acceptance. Using AI in a large organization is very different from private use. Asking an everyday AI like ChatGPT to create an itinerary is easy. Using them professionally is a completely different matter. For example, how do you ensure that 6,500 employees can write good prompts?
We are now developing training and guidelines to make employees more AI-savvy. We are also building a central AI strategy so that the teams don’t all work with different tools. This coordination is crucial, as many companies will likely recognize.
What’s next for Hunkemöller when it comes to AI?
I just read a report that says 90 percent of companies are already using AI. But 67 percent of them are still in pilot mode. This is pretty recognizable. When it comes to findings, Hunkemöller is progressive. In other areas, however, we are still in the discovery phase.
One of the areas we are just beginning to explore is creative AI. Physical shoots remain essential to create magic, emotion and atmosphere. However, AI can support and change them in the future. It can expand creative possibilities or improve efficiency, for example by traveling less.
Additionally, we want to use AI to optimize our marketing mix and better understand the returns of our campaigns.
Where do you see the biggest opportunities for AI in fashion?
The greatest opportunities lie in the creative field. Think about trend analysis: what should be developed, what designs are created, in which direction is the market moving? You can create mood boards with AI or convert patterns into a 3D design. This technology already exists, but is not yet used on a large scale in fashion.
European players like Zara and Loavies and Chinese giants like Shein and Temu have very short lead times from design to delivery; often it is only a few weeks or days. We can’t keep up with this pace. The design and production of lingerie is done entirely in-house and is more complex than making a t-shirt or sweater. Nevertheless, our time to market can and must become shorter. I am convinced that AI will play a key role in this.
One final piece of advice?
Last year I said that companies should implement AI gradually: start small, run pilots, and then scale slowly. My opinion on this has completely changed. AI has given time a new dimension. A few years ago meant past five, six or seven years ago. When I talk about “the past” today in relation to AI, I mean two or three months ago. Developments are moving so quickly that small steps no longer work.
For companies currently in the experimentation and exploration phase: Provide support within the organization. Employees need to understand that AI will not take over their jobs. Instead, it frees up time so they can do their jobs better. AI tools can bring enormous efficiency gains, especially in retail, where things are always stressful.
For companies that have not yet started with AI, my tip is: data, bold, underlined and with an exclamation mark!
AI tools were used to transcribe this interview and as a writing aid.
This article was created using digital tools translated.
FashionUnited uses artificial intelligence to speed up the translation of articles and improve the end result. They help us to make FashionUnited’s international reporting quickly and comprehensively accessible to a German-speaking readership. Articles translated using AI-based tools are proofread and carefully edited by our editors before they are published. If you have any questions or comments, please email [email protected]