September 18, 2020
Fashion is one of the industries in the post-coronavirus era, which certainly incorporates innovative tech at a much faster pace than it has ever been.
A new and inventive perspective to engage customers has come out from incorporating AI in fashion.
Artificial Intelligence (AI) in fashion is transforming the entire functioning of the market, playing a vital role in all principal segments.
Design, production, supply chains, e-commerce, and marketing are only some of the fashion segments AI is affecting.
In fact, as we're diving deep into digitalization, AI and machine learning-based developments in the fashion industry provide retailers with an integrated approach that lets them harness AI's insight into fashion and leverage the trends for their own advantage.
Juniper Research discovered that the global retail spending for AI services is projected to hit $12 billion by the end of 2023.
After the COVID-19 crisis, this number will probably be even bigger, as AI powers retailers to make better business decisions.
In 2019, IBM conducted research discovering that the retail industry was planning to leverage AI in six areas—demand forecasting (85%), supply chain planning (85%), customer intelligence (79%), marketing and advertising (75%), store operations (73%), and pricing and promotion (73%).
When it comes to AI in fashion, the technology is improving almost every aspect of companies' functioning, especially e-commerce AI.
Here are some of the most popular uses of AI in e-commerce:
Product recommendations are one way AI is taking fashion e-commerce to the next level.
While looking for fashion pieces on e-commerce pages, the AI engine shows users product recommendations based on various characteristics, such as related items, color choice, price, and other features.
Machine learning algorithms analyze the user's behavior and choose the recommended products accordingly.
Next, visual search is a prevalent use of AI in e-commerce where users can upload a picture of the item they want and get the most similar one.
Visual search technology based on AI-powered computer vision enables fashion retailers to suggest conceptually or aesthetically similar products to consumers, eliminating text-based search struggle.
Automatic tagging categorizes and tags photos based on attributes in the product catalog, utilizing sophisticated AI algorithms.
These algorithms accelerate the tagging process, making it automated and removing any need for human intervention, thanks to Deep Learning.
AI also helps fashion retailers provide better customer service through chatbots and enables designers to predict fashion trends by utilizing predictive algorithms.
Besides that, it also eliminates mistakes and makes the merchandise distribution process fast with automated supply chain management.
However, this year's coronavirus crisis is transforming the industry. Only a month after it had started, clothing sales had fallen by 34%.
Production was also going down, while many retailers decided to close their physical stores. H&M, Zara, and Gap were only some of them.
The situation accelerates the digitization process of fashion retailers, encouraging them to focus on e-commerce.
Consumers are not shopping the same way they used to. As they can't travel much, they buy items that will make their stay at home more comfortable.
Fashion retailers recognize this trend, so they are also favorizing lounge-wear items.
For example, Uniqlo started selling casual wear at reduced prices.
What is more, Browns witnessed a 70% sales increase in this segment.
Offline retail is obviously affected the most, while online retail might not be able to cover all the losses.
Several designers and stores sell their new products at low rates, generating at least some sales.
They seek to find more innovative ways to recycle their summer offerings into their winter releases, without many options left.
The crisis we didn't expect brought us the future of fashion we thought we'd see years later.
Now, fashion retailers have to be quick, acting as the market demands them to.
After the crisis, the fashion industry will turn to e-commerce, as this is the segment that will definitely survive.
However, things won't be the same as before.
That's why it's essential to turn to a long-term strategy to prepare fashion retailers for the new era.
Supply chains are now actually fragmented.
This means stores need to concentrate on product adjustments and pricing changes to respond to these shifts.
However, their long-term decisions should be based on the ability to predict consumer behavior.
To be able to perform this, fashion retailers need data. A lot of data.
AI will have a crucial role in helping companies process large amounts of data and forecast customer behavior trends.
AI-based systems can process vast volumes of data to identify patterns reflecting the basis of complicated business strategies, recognize images and human speech, forecast customer behavior, and many other activities.
The best thing about AI algorithms is they are continuously learning from the data and evolving.
For the following year, fashion retailers will have to develop the most optimal mix of AI and human work.
Those who will succeed will have the most relevant online offering based on relevant and real-time customer data.
They will become more flexible with the ability to react according to changes and will be able to predict future demand.
With so many examples, fashion retailers will have to think about their AI objectives, reflecting the segments with the most remarkable ability to bring value to their particular market strategic plan.
With optimal use, AI can become an essential part of a fashion retailer's strategy.
Pixyle's AI suite is the right choice to prepare you for the e-commerce challenges 2021 will bring.
Use the power of our product recommendations, automatic tagging, and visual search engines to take customer experience to the next level.