Artificial intelligence was widely believed to exist only in movies when most people were growing up. Rather than a myth, AI actually works and helps us in more ways than we could ever imagine. Even in the fashion industry, we human beings make mistakes on a daily basis. There can be missed stitches in the sewing room or fabric that is cut wrong, causing the manufacturing department frustration and disappointment. Artificial intelligence can help in these situations. With artificial intelligence and fashion, there is no doubt that this partnership will succeed for years to come.
As part of the various key divisions within this industry, AI transforming the fashion industry. The use of artificial intelligence is playing a big role in transforming the fashion industry from design to manufacturing to logistics and marketing.
Promoting and selling fashion goods with artificial intelligence
As much as it is about manufacturing fashion products, the fashion industry is about creating demand and brand awareness. It is of vital importance to clothing and apparel brands to find new and effective ways of getting their goods in front of buyers and creating awareness. The use of artificial intelligence and machine learning by fashion brands is on the rise as a means of improving users’ shopping experiences, automating sales processes with intelligent automation, and enhancing the sales process with predictive analytics and guided sales.
In addition to chatbots and voice assistants, fashion brands now use devices like Amazon Alexa, Apple Siri, Google Home, and Microsoft Cortana to bridge the gap between consumers and brands.
Design and manufacturing of fashion with artificial intelligence
According to a documentary called “Minimalism”, clothing can have as many as 52 seasons. Because fashion and design constantly change, retailers need to accurately predict next season’s consumer preferences. Data from the prior year is used by retailers to estimate sales for a current year. The sales of a product can be affected by many factors, which are difficult to predict, such as changing trends. With artificial intelligence-based forecasting, however, errors can be reduced by as much as 50%.
Textile manufacturing can also be enhanced by AI technologies once the clothes have been designed. Fashion manufacturers to boost manufacturing efficiency and complement human workers use artificial intelligence (AI). Machine learning algorithms are now being used to spot defects in fabrics and make sure the finished textile’s colors match the original design. Quality assurance processes are becoming more efficient as a result of AI technology, such as computer vision technologies.
Additionally, intelligent, AI-enabled systems can provide greater insight into fashion trends, purchasing patterns, and inventory management for fashion brands by identifying patterns and performing predictive analytics. The online personal styling service Stitch Fix is a company at the forefront of applying AI to fashion. To improve customer service and improve supply chain efficiency, the company uses machine learning algorithms.
Changing Fashion Trends
We have known for years that the fashion industry is one of the highest-paying industries in the world. People wear cloths every day, and they want the best styles. Intelligent machines will not only make factories and shelves more efficient, but it will also make everything better. Artificial intelligence helps companies gain insight into what customers like and dislike, and ensure the customer gets what he or she wants.
The Fashion Industry is predicted to grow to 7.3 billion dollars by 2022 as a result of artificial intelligence. Companies will be able to generate more sales by being able to predict accurate fashion trends as well as create new looks. Customer satisfaction is key. AI helps deliver exactly what the customer wants or helps the customer determine what they want. The consumer leaves happy and returns again and again every season to update his or her seasonal wardrobe.
- Artificial intelligence can customise recommendations to show different results depending on the region a retailer operates in. Different geographical locations have significantly different preferences, trends, and style identities.
- Retailers can tailor the definition of a ‘region’ according to their own regional strategies.
- Retailers might consider Europe and Asia macroregions, for example. During the same time, another retailer might want to tailor results further by micro-region within Europe for displaying different recommendations in Northern Europe, Central Europe and Southern Europe.
Segmentation of personalization by customer
AI allows retailers to target different segments of customers based on their strategic goals. If a customer segment is more interested in upselling than cross-selling, an upselling recommendation may make more sense, and vice versa. Retailers can use AI to reach their business objectives on a segment-by-segment basis by combining different identity data with different strategic business goals.
Based on a customer’s preferences, AI and machine learning can be used to make product recommendations and visual similarity assessments that are hyper-personalized:
- Body Type, based on complimenting their figure
- Colouring, based on the combination of hair and eye colour, skin tone and undertones
- Occasions they want to dress for
- Style Persona, based on their taste and identity such as fashion-forward or traditional
- Data on a customer’s past browsing and buying behavior can be combined with these information.
- Every product on the online store has personalized similarity and outfit recommendations based on the customer’s preferences.
- A bespoke personal styling service can now provide online recommendations of the same quality.
Customers of any segment can receive in-person styling services, without having to pay for stylists dedicated to them.
A continuous integration of artificial intelligence into fashion retailers’ omnichannel customer journeys enables them to better address each customer pain point and differentiate themselves from the competition.
As with finding the perfect suit, integrating AI into a fashion business will require a tailored application. One size does not fit all.
When fashion retailers use AI as Augmented Intelligence to supercharge their existing business model, they’ll scale their resources, amplify their core strengths, and use data-driven insight to overcome their weaknesses and increase their penetration. A business that increases market share and revenue while reducing operational costs becomes more profitable.