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Artificial Intelligence and Machine Learning in the Fashion Industry

Artificial Intelligence and Machine Learning in the Fashion Industry

Fashion is one of the largest global industries – but it is not one of the first industries you think of when it comes to artificial intelligence (AI), or machine learning (ML).

However, many brands and designers are taking advantage of the new technologies to improve things such as design, manufacturing, production, and customer experience. Additionally, due to the highly competitive market, fashion brands are rapidly implementing AI and ML to remain relevant.

Keep reading to find out more!

How AI and Machine Learning can help?

Predicting Trends

Predicting trends is a labour-intensive task, involving complex manual observations, data collection, and data analysis. Utilising AI and machine learning allows for direct data collection, identifying patterns, and predictive analysis.

This allows for fashion brands to easily keep up with the latest fashion trends and predict customers preferences for the next season. AI-based approaches can reduce forecasting error by as much as 50%!

Personalisation

AI and ML have the ability to provide personalised recommendations.

  1. Personalisation per region: AI can personalise recommendations to show alternate results in different regions. This is important as trends, styles and personal tastes can differ greatly between geographic regions.
  2. Personalisation per segment: Recommendations can be personalised to connect with various customer segments. This can help businesses achieve segment based business objectives. 
    1. Personalisation per customer: The power of ML and AI can create hyper-personalised recommendations for each customer. Taking into account their body type, colouring, occasion, and style persona and merging this information with past browsing/purchases allows for a completely customised experience. 
    Designing

    As AI and ML-based approaches have the ability to predict future trends and consumer preferences; this allows for a more efficient designing process. AI-powered fashion designing based on customer’s preferred colours, styles and textures enable designers to create exactly what is in demand.

    Manufacturing and Inventory

    Implementing AI and machine learning into the fashion manufacturing process allows for an extremely efficient process. Computer vision enabled by AI/ML can make sure the colours and finishes of textiles are as they should be as well as spot any defects.

    Additionally, accurate predictions of inventory demands are possible; therefore, significantly reducing last minute manufacturing and waste.

    Benefits of AI and ML in the Fashion Industry

    Improved Customer Experience

    The customer experience can be improved by implementing AI/ML in fashion in few ways: 

    Personalisation: Personalised products and services are something every customer wants, no matter what industry. AI/ML allows businesses to easily follow fashion trends and individual purchase behaviours, allowing for personalised recommendations for each customer. This means improved customer satisfaction + loyalty.

    Customer Service: Implementing AI/ML means enhanced customer service, further improving the customer experience. Chatbots allow for the user to receive instant support and the possibilities are endless! They can help with product recommendations, sizing, return policies and much more.

    User Experience: Using AI/ML allows for a unique and easy to use interface giving the customer a seamless experience. For example, taking a photo of an outfit you like on a celebrity and getting a similar looking outfit displayed in the app.

    Save Time and Costs
    1. AI and ML’s capabilities allow for improved inventory management, meaning less waste. Less waste = less cost!
    2. AI/ML’s computer vision technology can help spot counterfeit products and stop them from entering the market. This keeps your products in high demand and you won’t lose money to counterfeit alternatives. 
    3. Automated processes mean no more repetitive tasks – therefore, employees can save time and money by focusing on other priorities. 
    4. Returning of sold items increases operational costs – AI and ML’s personalisation abilities reduce returned products, saving you money.

    Want to incorporate some of these ideas such as chatbots and personalisation into your business? Contact us and we at xEnabler can help!

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