While algorithmic personalization has already taken over the world of music and video, fashion still remains unconquered.

Online clothing stores are striving to implement this technology in order to manage huge product catalogs and show customers exactly what suits them.

After all, the idea is simple: analyze your purchase history, likes on social networks, pages viewed and other data to create an individual profile of each customer's fashion preferences. That's how Spotify and TikTok work, recommending music and videos that you would like, but things are much more complicated in the fashion world.

The complexity of the task is due to a number of factors:

1. Subjectivity:

• Fashion is an area where people's tastes and preferences are individual and multifaceted.

• Data-based algorithms do not always take into account the nuances of personal style, the emotional component of the choice and the context in which the clothes will be worn.

2. Dynamism:

• Fashion trends change quickly, so systems based on purchase history can quickly become outdated.

• Human curators are able to respond more quickly to new trends and offer relevant options.

3. Versatility:

• Fashion is not just clothes, it is a combination of various elements: accessories, shoes, hairstyles, makeup.

• It is difficult for algorithms to take into account the interconnection of all these components and create harmonious images.

Some companies have already achieved some success, for example, Lamoda uses a system that recommends products to customers that are similar to those they have already viewed or added to the cart, and the Farfetch platform has introduced a personal stylist who helps customers create images from those presented in the brand store.

It is important to note that algorithms should not replace the human factor, but complement it.

The ideal personalization system in fashion is a combination of powerful algorithms that analyze data and the experience of professional curators who understand the intricacies of this field.

Statistics:

• According to McKinsey & Company, by 2025 up to 80% of retail purchases will be made under the influence of algorithmic recommendations.

• A study by Forrester showed that customers using personalized recommendations are 30% more likely to make a purchase.

• 71% of consumers say that it is important for them that online stores recommend products that match their individual tastes.

Do you want to keep up to date with the main events in the fashion industry and brand news?