Technology is reevaluating traditional retail and fashion industry supply chains. Even as fashion retail is still spinning from the immense changes in e-commerce platforms, new innovations are breaking ground in supply chain management. Supply chain automation could be the answer to what trouble retail businesses such as long supply processes, delays from concept to market, and slow implementation of the latest trends.
According to a January 2017 report released by the McKinsey Global Institute, tasks that are likely to be automated by 2055 — from predictable physical activities to data collecting and processing — currently makeup 51 percent of work tasks in the United States, accounting for almost $2.7 trillion in wages. The industries most likely to be affected include manufacturing and retail. There is also some of articles about fashion industries implement AI in their business
Here are the points to consider why adopting supply chain automation will allow certain retail organizations to lead the charge into the future.
Alternative for 'Out-of-Stock' Product :
When a product goes out of stock or size, customers are redirected to multiple relevant product pages on the retailer’s website. They can easily find what they are looking for without the hassle of restarting a product search, which often leads to frustration and site abandonment.
That’s why AI uses visual detection and key product attributes to recommend visually similar alternatives for 'Out-of-Stock' products on a fashion retailer’s online store.
'How to style clothes' recommendation :
Customers often want to try out new clothes but simply don’t know how to style them. Outfit recommendations show customers the ways they can wear different products together.
Inspiring the customer with editorial quality AI styling means upselling and increasing basket size from just one product to a complete look.
Personalized Recommendations :
Trends, style identities, and personal taste can significantly vary between different geographical locations.AI can personalize recommendations to show different results for different regions a retailer operates in.
Taking into account their individual:
- Body Type, based on complimenting their figure
- Coloring, based on the combination of hair and eye color, skin tone, and undertones
- Occasions they want to dress for
- Style Persona, based on their taste and identity such as fashion-forward or traditional
fashion-specific information enables customers to filter their search by specific attributes they want to see: such as color, print, fit, fabric.
Product searches return results with increased accuracy and relevance that bring the customer closer to a buying decision.
Natural Language Search:
Natural Language Processing (NLP) is the ability of a computer program to understand daily language as spoken by humans.
AI allows customers to search for products using the language and descriptions that they would naturally use in their daily life.
Product ranking enables the best customer-to-product matching and ensures the right products are seen by the right customers at the right time.