ISSUES WHICH CAN BE SOLVED WITH AI
Artificial intelligence and machine learning are impacting fundamentally the consumer packaged goods (CPG)and food and beverage industries.
F&B retailers use AI to automate inventory management. One use case is to have staff take photos of store shelves to initiate a machine-learning process that automatically detects missing or misplaced items and notifies stakeholders to restock or make corrections.
AI and image-recognition technologies can ease the procurement process and reduce the time it takes to send an order. Employees can just take a photo of an item to activate an automated database search for the exact item or an equivalent product.
Personalized customer service
Using chatbots or voice assistants powered by natural language processing and machine learning, companies can tap consumer shopping data and history to provide hyper-personalized and automated customer service experiences.
Heightened consumer engagement.
CPG players can use AI to maintain strong empathy with their audience. By closely monitoring conversations on social media, AI can be used to analyze consumer data and identify sentiment or behaviour that are crucial not only in building positive experiences but also in the development and design of new product lines.
Benefits of AI in Consumer Goods and Retail
AI for the Consumer Goods and Retail Businesses: What are the benefits and where should one start?
- On-time or faster deliveries through AI
- Consumers get what they wish for
- Goods travel safely
- Fewer goods are stolen
On-time or faster deliveries through AI
Delivery delays and out-of-stock items cause consumer frustration. Wouldn’t it be ideal if companies knew who was likely to buy what and when? Supply chain professionals could then make sure they had the right manpower, warehouse and transport capacities, or even send goods to be stored close to delivery addresses before we buy them (a process known as “anticipatory shipping”). Amazon has been experimenting with AI for years – for example in its cashier-less store – but other companies are close behind. Otto, a German e-commerce merchant, has created a system that analyses around 3 billion transactions and 200 variables, including sales data, website searches and weather information. With 90 percent accuracy, it is able to predict sales behaviour in the next 30 days. Now, the company purchases around 200,000 items a month without human intervention. Surplus stock has declined by a fifth and product returns by more than two million items a year. While customers receive their orders more promptly and efficiently, the planet benefits too, as fewer shipped packages need to be sent back.
Consumers get what they wish for
A major challenge in the supply chain is predicting next season’s hit products. Merchants have to make choices early on, and accept the risk that their stockpiled goods may not be bought. On the other side, consumers also have to hope that retailers have in stock what they want to buy. Supply-demand uncertainties and mismatches are costly and inefficient for all participants. Brand reputation is at stake, and consumers pay a higher price to cover the risk. One AI-powered approach is dubbed optimised line planning, which integrates data such as internal sales and customer records, competitive intelligence, trend analysis and social media preferences to create a customer profile or persona. This customer segmentation allows retailers to determine the selection of products that will resonate best with each persona. Designers can create placeholders for next season, and even calculate expected revenues. This provides confidence that both sales targets and the needs of the consumer will be met.
Goods travel safely
When supply-chain professionals know what is happening, they can ensure packages will arrive despite any adverse conditions. The Tel Aviv maritime data provider Windward says it is able, through AI, to predict shipping safety worldwide. The Israeli startup signed a deal with London-based insurance market Lloyd’s in November 2017, with Windward providing Lloyd’s member companiessoftware that forecasts maritime hostilities or accidents at sea. Flextronics International – which counts Apple, Microsoft and Ford Motor as customers – has pioneered software that generates real-time alerts of supply-chain disruptions throughout its 14,000-strong network of global suppliers. The AI-based system helps predict actual and potential problems, such as supplier delays, strikes, earthquakes or tsunamis, and allows the relevant teams to make informed decisions to keep inventory moving and consumers happy.
Fewer goods are stolen
Some orders don’t arrive due to crime. The FBI estimates that cargo theft costs US businesses more than $30 billion each year. Facial recognition and the detection of suspicious behaviour can help prevent this. At the Chinese AI research company Yitu Technology, the pass cards of staff and visitors taking the lifts to floors 23 and 25 are read automatically – no swipe required – and each passenger is deposited at their specified floor, and only there. Cameras record everyone entering the building, and track them once they are inside. “Our machines can very easily recognise you among at least 2 billion people in a matter of seconds,” says Yitu co-founder and chief executive Zhu Long. Yitu’s generic portrait platform already contains 1.8 billion photographs of those logged in the national database and everyone who visited China recently. 320 million of the photos have come from China’s borders, where pictures are taken of everyone who enters and leaves the country. This cutting-edge technology can be used to protect any kind of asset – from vehicles to shops, to warehouses and even entire cities. In Boston, intelligent security cameras are even anticipatingcrime. The security system monitors feeds in real time and alerts authorities the moment it identifies unusual activity.
Interesting Projects & Applications of AI in the Retail and Consumer Goods Sector
- Sephora’s Virtual Artist app
- Automated irrigation systems
- My Beauty Matches’s personalised beauty
- Proven’s stand on fake reviews
Sephora’s Virtual Artist app
While the predominant function of Sephora’s Virtual Artist app is to allow beauty buyers to try on products virtually via augmented reality, the brand recently introduced a colour match tool, powered by AI. This tool determines the particular shade of a product on a photo and suggests similar products available at Sephora that the consumer can then try on and purchase.
Olay’s Skin Advisor
If there’s one sector where AI has been making a lot of noise, it’s beauty. Olay’s Skin Advisor is an online consultation platform that can tell the true age of a user’s skin from a selfie. By using AI to both evaluate and determine problem areas, as well as the overall condition of the skin, it also provides personalised skincare routines and reports.
My Beauty Matches’s personalised beauty
With over 170 retail partners and 300,000 products, My Beauty Matches claims to be the world’s first personalised beauty product recommendation and price comparison site, and is dedicated to ramping up conversion rates and increasing basket sizes for other brands. More specifically, it uses AI to help partners including Harrods, Harvey Nichols and Bobbi Brown run hyper-targeted campaigns to people wanting personalised beauty suggestions.
Proven’s stand on fake reviews
Proven is a newly launched beauty brand that uses AI to provide the most personalised offering possible. Rather than sifting through products, it searches through reviews of those products to offer individual skincare routines. To date it has been reported that the brand’s tool has analysed 8 million skincare product reviews in order to eliminate fake reviews, save time for consumers and offer personalised recommendations that actually matter.