Posted on : 2023-03-19 20:41:20
Article : Good morning, Monday Management solution for TASK 233 - By 2025, at least 90% of new enterprise apps will embed artificial intelligence. Most of these will be AI-enabled apps, delivering incremental improvements to make applications smarter and more dynamic. A Focus on FMCG sector.
In the TASK part of this AI ML topic, we have discussed on salient points of AI ML segments applications in an industry. Now in this solution part we discuss on amazing features for One of the recent examples of applying AI to FMCG companies was Olay (Procter & Gamble). They released a platform which analyses users’ skin and provides personalized skincare routine based on skin age and concerns. The results were amazing! Similarly, many companies have followed using tools of AI ML and now let discuss about few companies brands as examples that are following and how they are leveraging machine learning and AI technology as an integral part of their marketing strategy.
Amazon was one of the first companies to pioneer personalized shopping recommendations, and over the years its algorithms have become increasingly sophisticated. Suggestions are now based not only on past purchases, but also items that other customers have bought, searching, and browsing behaviour, and many other factors. Amazon also uses artificial intelligence to drive dynamic pricing – reducing prices to elicit more sales when needed, and increasing prices when demand is high. The algorithm enables optimal sales and revenue automatically.
Still forging ahead as a leader in the use of technology, Amazon has now opened checkout-free physical stores in Seattle, Chicago, and San Francisco, which have AI-powered sensors and cameras. This technology can tell exactly which items a customer has picked up and will charge them automatically as they walk out of the store using the Amazon Go app. This AI ML application is being followed in India in some metro cities outlets. Amazon is even getting in on the trend of using AI in the fashion industry with Echo Look – its AI-driven personal stylist that uses machine-learning algorithms to suggest individual outfit recommendations, thereby driving more sales of apparel, shoes, and accessories.
Starbucks presented a strategic plan for using AI and big data in 2016 itself, and the brand has made good on its promises to investors by enhancing its reward program and personalization to connect more deeply with its customers. Personalization has always been a key part of the customer experience at Starbucks, with the ability to customize drinks for your individual taste. Now the company is using its loyalty card and mobile app to collect and analyze customer data including purchases, where they are made, and at what time of day.
The company uses predictive analytics to process this data in order to deliver personalized marketing messages to customers including recommendations when they’re approaching their local stores, and offers aimed at increasing their average spend. A virtual barista service on the app powered by AI also allows customers to place orders directly from their phone via voice command. As well as delivering a more personalized customer experience, Starbucks uses their data from 90 million transactions every week to inform business decisions such as where to open new stores, and which products they should offer.
Chinese retail and technology multinational, Alibaba Group, opened its first “Fashion AI” store earlier. The store aims to streamline the fashion retail experience for customers with intelligent garment tags that detect when the item is touched, smart mirrors that display clothing information and suggest coordinating items, and future plans for integration with a virtual wardrobe app that will allow customers to see the outfits they tried on in-store. This is not the company’s first foray into artificial intelligence. In 2015, Alibaba launched its smart customer service system, which automated customer service so well that it achieved satisfaction ratings higher than the human agents. Alibaba also uses similar technology to Amazon to drive personalized recommendations and search results to shoppers, as well as automatically-generated storefronts that display the most appealing items for individual customers. The company has a massive customer base, with 567 million active buyers and millions of visits across its website and apps each day. This massive amount of data on customer habits is ideal fodder for AI processing, and no doubt the company has more plans for how it can be utilized in the future.
End point- From hawkers to roadside stalls to branded showrooms to ecommerce portals, the process of selling consumer goods and services through retail channels has followed an interesting evolution over the years. It is worth noting that with every refinement, the task has continually become more complex and specialised, requiring newer techniques by the sellers.
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