Intro

This is the sixth and penultimate part of this multi-part blog series by AICorespot on Fashion Retail and how it is being enhanced and revolutionized by emergent technologies such as AI, ML, and beyond. The sixth part picks up where the fifth part left off, exploring some of the use cases of AI/ML in web-based fashion retail. We will also do a little exercise; we will compare fashion retail from the 1990s to fashion retail today. We will then definitively conclude that AI/ML is retail’s little helper.

AI use cases and deployments in Fashion Retail

What advantages do businesses have to gain?

Utilizing AI-based fashion tools for client purchase forecasting

The cumulative data from the totality of your clientele, AI-based algorithms are utilized to forecast if specific clients are demonstrating indicators of committing to a buy very soon (this is deduced through analysis of the frequency of product pages visits, the consistency with which newsletters and coupons are viewed/opened.) This knowledge is then utilized to verify the purchase and develop a memorable client experience.

AI Use Case – Trend Forecasting

One of the biggest problematic aspects of operations in fashion retail is the issue of excess stock. The power of AI can be tapped into to forecast those products that are required to fulfill upcoming trends and demand, and more specifically – providing insight into the specific volume, preventing overstock.

In hopes of reducing overstock,

• The purchasing capacity of the clientele is considered
• Present stock levels are analyzed against demand and trends
• Using AI tech, if an item is overstock and not trending, the purchasing capacity of the clientele is found to be less, then it’d be wise to arrange a discount scheme.
• Similarly, if an item is trending, is understocked, and the purchasing capacity of the clientele is found to be higher, then it’s wise to engage in heavy marketing.

 Specific algorithms can additionally be deployed to forecast supplier pricing alterations and to suggest the best timings to reduce the purchase expenditure.

 AI Use Case – Inventory Management

One specific use case of AI in fashion retail where the potential is extremely high is inventory administration.

• Retailers within the fashion space have considerable capital in the form of their inventory.
• Artificial Intelligence (AI) is currently being leveraged to assist in increasing stock turnovers
• AI technologies consider the requirement to sell older stock as soon as it is feasible.
• This is an integral AI application that assists fashion retailers pad out their bottom line
• The longer the time you have an inventory item in stock, the lesser the probability of it being sold.

AI Use Case – Best Price Suggestions

With the help of data that is available in the public domain, AI can go through your market rival’s product pricing, their strategies and suggest the best price points to maximize your revenues. These modifications can be automatically applied with a diverse array of strategies.

• Retain the lowest possible pricing, but also retain at the very least, a minimal margin.
• Enhance profit levels through incremental increases to pricing

 AI Use Case – AI Chatbots (Virtual Assistants, Smart Assistants)

AI-driven chatbots, who are also referred to as virtual assistants (VAs) or smart assistants are yet another method in which AI is leveraged within the domain of fashion web-based retail. NLP, which is critical to chatbots, has witnessed explosive amounts of advancement during the COVID-19 pandemic era, with most customers choosing to do their shopping online.

• AI-driven chatbots emulate client service reps
• They help clients identify what they’re seeking
• This type of client service is scalable
• Further, it might outright be a +ve thing for conversion rates

Fashion giant, Levis, is a forerunning presence in the deployment of AI-based chatbots in web-based fashion retail; their chatbot assists clientele to identify the best pair of jeans.

There is no doubt that AI will experience growth in terms of intricacy and sophistication, speed, and accuracy. It has an exceedingly positive outlook. AI will become an integral aspect of our everyday lives, improving our professional and personal lives. The gap between AI-based and AI-ignorant businesses is getting wider and wider. As we observed in one of our earlier blog posts in this series, 44% of fashion retailers in the UK face being shut down due to choosing to stay AI-ignorant.

• AI can detect looming trends quicker than industry experts, specialists, and insiders to improve the design processes.
• Businesses with AI integration and its potent capacities will be able to produce new fashion gear quicker than contestants
• This is also with an increased probability of correlating the market requirements with their collections, turning in more profit than the contestants.

Conclusion

This brings us to the conclusion of the sixth part of this multi-part blog series. The next part will conclude the series. Stay tuned! In this part of the blog, we saw some specific use cases for AI/ML within the retail and a brief perspective on its outlook.