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How machine learning and AI are changing the face of fashion

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How machine learning and AI are changing the face of fashion

The fashion industry has been swamped by the ongoing technological wave that aims to revolutionize people’s lives. Brands are investing and experimenting in many different tech tools to drive sales and increase brand awareness, improving the relationship with their customers.

Between the many innovations that the world of fashion has adopted recently, AI and machine learning are the most promising by far. AI is already offering many ways for brands to better personalize their offering to consumers [1], for example via recommendation engines showing certain kinds of styles and garments based on the user’s previous browsing sessions.

In the future, smart algorithms will even predict what each specific customer would like to buy next in order to recommend garments based on recent purchases and global trends. It doesn’t stop here: AI will assist retailers all along their marketing journey, deciding when it’s the best time to place new collections, sales and special promotions thanks to their evaluation of shoppers’ behaviors.

On the consumer side, thanks to AI, online shopping is not a “mechanical” habit done through a screen, but can become a mutual conversation between brands and customers, where consumers are assisted in their style choices and purchases.

Machine learning has the ability to analyze consumer intel to create a description of preferences and habits. With time, they’ll be able to understand even more what shoppers are looking for and even predict the next purchase, offering brands the chance to be ahead of the game with personalized recommendations.

Sales and forecasts of consumer habits, tailored-made ad campaigns, pricing optimization and personalized content creation are just a few more areas where machine learning can drastically change a brand’s sales performance, both online and in store.

Why fashion retailers should approach AI and machine learning

There is no doubt that AI and machine learning are set to change the face of shopping; in fact, many retailers have already recognized it. For the remaining skeptics, let me outline three key areas where these new technologies will make a significant difference in the retail industry:

Image recognition

Machine learning can deliver amazing results in terms of image recognition; in the fashion industry this is particularly important for style recommendations. In order to deliver relevant content and suggestions to shoppers, millions of images are used to make computers identify similar garments. Machine learning links this knowledge to fashion trends, past purchases and shopping behaviors to provide the most relevant recommendations.

Collecting data

AI and machine learning allow brands to improve the process of data collection. Big data is fundamental for user acquisition and retention, aiming to deliver to consumers an enhanced shopping experience. For retailers, collecting consumer intel can’t be that easy.

For example, demographic data is important to understand the target audience and their habits, in order to predict future purchases. The problem with this type of data is that it’s not permanent. People’s tastes in terms of fashion can vary over time and for this reason retailers must regularly refresh their research.

AI and machine learning can make this process smoother by connecting past, present and future consumers needs. Smart algorithms can learn from billions of data and store all of the information that brands need to engage with shoppers.

Personalization

To achieve and offer a highly effective level of personalization for their customers, retailers must use the fundamental tools of image recognition and data collection.

Personalization enhances the shopping experience and adds value to it, driving sales and improving engagement among shoppers. It helps customers to find what they are looking for without spending time browsing around and it opens a conversation between the brand and its consumers.

But personalization also requires a lot of data that needs to be processed, stored and linked to each other in order to provide tailor-made contents. AI and machine learning make this possible by analyzing huge amounts of data to create a personalized, omnichannel shopping experience. AI engines are able to look at how customers interact across multiple devices, unifying consumer habits and enabling retailers to deliver tailor-made content across different platforms.

With the help of advanced technology, retailers aim to make further steps in personalization by engaging in conversation with customers. Some brands have pioneered this trend – a recent example is Tommy Hilfiger.

Tommy Hilfiger’s AI-powered experiment

Many brands are already experimenting with AI and machine learning to increase engagement among shoppers; the world’s first example is Tommy Hilfiger chatbot TMY.GRL [2]. Tommy Hilfiger has always been particularly enthusiastic about the tech revolution in the fashion industry and for this reason it was the first to experiment with an AI-powered chatbot, operated within an outstream video ad.

The auto-playing ad video gets personal thanks to the chatbot, which reacts in different ways according to the time of day. It is able to chat with shoppers about new collections, helping them to select garments through quick Q&As.

Source: chatsbotlife.com [3]

The chatbot represents the first attempt to create a digital fashion assistant to support consumers, providing advice and additional information.

Tommy Hilfiger is a good example of how brands can use the power of AI to better understand shoppers’ habits and behaviors in order to deliver relevant and engaging content, enhancing the overall experience. The results can be outstanding: an established relationship with the customer and ultimately boosted sales.

Conclusion

The retail industry is evolving rapidly. Last year, Alibaba’s CEO Jack Ma coined the concept of “New Retail ” referring to “the integration of online, offline, logistics and data across a single value chain.”[4]

To survive and thrive, brands need to invest in new technologies that truly promise to change the face of shopping. It is already happening; something that seemed impossible just a few years ago is now simple and accessible to everyone – just think about personalized newsletters [5].

Promising future improvements will allow retailers to reach a higher level of personalization in order to bond solid and loyal relationships with their customers.

The future of AI and machine learning will undoubtedly allow  us the chance to be experimental with our fashion choices. It won’t be long before you can find, in a few clicks, the exact blouse that the lady in front of you is wearing, or try on alternative and creative outfits and trends without leaving your couch. With advanced technologies, the sky’s the limit.

Related reading

References

  1. ^ brands to better personalize their offering to consumers (www.clickz.com)
  2. ^ Tommy Hilfiger chatbot TMY.GRL (chatbotslife.com)
  3. ^ chatsbotlife.com (chatbotslife.com)
  4. ^ New Retail (fortune.com)
  5. ^ newsletters (www.clickz.com)
  6. ^ … read more (www.clickz.com)
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