According to the latest market intelligence research report by InsightAce Analytic, the global Artificial Intelligence (A.I.) in Beauty and Cosmetics market size was valued at US$ 2.70 Billion in 2021, and it is expected to reach US$ 13.34 Billion in 2030, record a promising CAGR of 19.7% from 2021 to 2030.

The beauty and cosmetic sector have witnessed a massive upsurge in Artificial Intelligence (A.I.) in recent years. Due to advancements in A.I. technologies and the fact that beauty is characterized as a personalized and engaging market that generates a large amount of data, A.I. appears to be a solution to deal with this complex environment, prompting beauty companies to make data-driven decisions on their strategies to remain competitive. The beauty market has changed dramatically over the last decade, owing to the introduction of new technology and a shift in customer shopping behaviours. The beauty sector has been incorporating digital transformation into its business models to give consumers individualized skin regimens and beauty products tailored to their specific needs.

The Artificial Intelligence (A.I.) In Beauty and Cosmetics Market, growth can be attributed to the Integration of advanced technology like A.I. in the beauty and cosmetic field, providing new ways of engaging with the consumer, bringing efficiency and customized solutions to the beauty client such as virtual try-on and personalized products. Increased demand for beauty products and technological advancements is expected to positively impact market growth. The outbreak of Covid-19 has changed consumer purchasing patterns across the beauty and cosmetic industry due to strict lockdown situations and the practice of social distancing across various countries. However, The COVID-19 crisis is likely to create opportunities for beauty and cosmetic brands due to the growing demand for personalized beauty & cosmetic products and the rapidly evolving e-commerce sector. According to a report, online sales at Sephora now account for 70-80% of total sales after the pandemic.

Prominent beauty assistance tools and magic mirrors are being tried all across the globe to reorient shoppers with beauty tools powered by AI that help them shop in a click based on their without the fear of buying mismatched cosmetics or beauty products!

The post AI adding the masterstroke to the beauty & cosmetics industry first appeared on PHYGITAL RETAIL CONVENTION (PRC).

AI can be applied seamlessly across physical and digital stores and AI in retail involves the use of automation and data analytics to deliver highly personalized shopping experiences to customers. By deploying AI-powered algorithms, retailers can track and capture in-store as well as virtual store data. AI will allow them to execute targeted in-store branding and marketing campaigns based on customers’ preferences, historical basket sizes, spending patterns, location, etc. Additionally, it will help them improve customer loyalty and retention with heightened personalization.

Let’s look at some of the most exciting applications of AI in retail:

* Contactless checkouts: Contactless checkouts make the buying journey shorter and easier for customers, thereby increasing in-store customer satisfaction. A contactless or cashier-less checkout combines the use of cameras, IoT sensors, and computer-vision systems to detect customer interactions, monitor the movement of products, and automatically detect prices. It helps reduce retailers’ operational costs and deliver enhanced shopping experiences to digitally-native consumers.

* Inventory management: Deploying AI in inventory management processes can optimize the supply chain, pricing, and promotional planning. Computer vision is deployed to track items on shelves and carry out a 360-degree inventory scan. Automating inventory management will provide retailers with out-of-stock notifications, boost the store layout, produce heat maps, and forecast the on-shelf time of a product. The benefit here is that AI assists the human workforce and helps bring back products on the shelves as soon as possible.

* Customer behaviour analysis: AI-powered retail analytics solutions captures real-time store data and track customer behaviour across offline and online channels. Using predictive analytics, retailers can build propensity models to conduct forecasting and predict customers’ purchase patterns. This will allow retailers to deliver relevant communication, and provide personalized discounts and offers to initiate a purchase. Brands can also deploy retail analytics in visual merchandising and store audits to identify operational gaps and improve in-store experiences.

* Auditing SKU placement and planograms: Traditionally, performing an audit of the retail shelf has been a manual and time-consuming process. Moreover, it was never fully accurate, and error rates were high. Therefore, the planogram management- which defines where products must be located and displayed in-store- has been an imperfect process. This is where automated image detection and object-detection technologies come in. Together they automate the process from checking prices to identifying products’ locations. The upshot here is that retailers get a unified view of their shelf conditions and make necessary amendments to in-store layout. Essentially, AI software will offer two critical KPIs to retailers: planogram compliance and on-floor availability.

Conclusion
Implementing AI/ML-powered technologies to streamline operations and cut operational overheads is a necessity in the age of labour shortages and e-commerce competition. AI is also critical to delivering personalized and immersive shopping experiences from shelf to checkout, track customers’ interactions and strengthen in-store branding.

— Sanjay Kumar

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