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GUEST COMMENT How AI is making sure customers get the beauty products they want, when they want them

Trading isn’t easy – we know this. With the current precarious retail climate, it’s important that businesses don’t feel as though they’re alone in this struggle. The British Retail Consortium (BRC) announced that July 2019 was the worst for sales growth since records began. And this environment is particularly challenging for fast-moving industries like the beauty sector. 

Take the launch of the Kylie Jenner Lip Kit in 2016, which took the beauty world by storm – selling out in less than 10 minutes after going live. Some customers were even prudent enough to buy in bulk, selling them on at an inflated price online. This then created a huge ripple effect, with brands bringing liquid and matte lipsticks to market to capitalise on Kylie Cosmetics’ success. If Kylie Cosmetics had been better able to predict the sheer size of the demand, and if beauty retailers had been able to predict the growing trend around matte lipsticks, they would have been better prepared to meet consumer demand.

With that being the case, judging exactly what products customers want, and the amount they want, can be a tricky process. The margin of error on customer demand forecasting is as high as 32% in retail, which means retailers could be making better use of their warehouse space and their resources. With the help of artificial intelligence (AI), businesses could reduce stock levels by £23bn.

So how are retailers using AI to ensure customers get the beauty products they want, when they want them?

Evolving customer trends

Trends in the beauty industry are transient, and there’s always a new trend around the corner or that next product that shifts the consumer demand. The constantly evolving trends in the industry make second guessing customer preferences difficult for beauty sellers. There are lots of different variables to consider when predicting product demand, which makes demand profiles increasingly tough to build accurately. While buyers at beauty brands will no doubt be experts in the field, with excellent knowledge of what’s hot and what’s not – there’s only so much they can do without AI.

Currently, as people are starting to become more environmentally conscious, the beauty world is experiencing a real buzz around sustainable cosmetics. Ethical cosmetics brands like Ethique are leading the way with their handmade, vegan beauty bar. So much so, they now have 55,000 people on the waiting list for the second release of products, after the first round of their plastic-free beauty range sold better than expected.

Shifts in culture, such as a stronger focus on societal issues, are reflected in customer preferences. A product with sustainability at the heart of its pitch may not have had a mass appeal a few years ago,  but now it’s a must-have that is potentially cutting into the sales of other popular sellers. The exact number of product sales is difficult for one person, or even a team of people to predict, given the number of variables that can influence a sale. That’s why retailers are using AI to support in predicting these variables.

AI-driven product replenishmentv

In today’s tech and data-driven world, retailers are using AI to be smart with forecasting to replenish products. This will ensure that in-store, brands can better predict the amount of a product they need, based on popularity online. A multi-channel approach is a must for brands who are looking to maximise their efficiency. Consumer behaviour online lets beauty companies know what products are popular, which tones sell best, which items are frequently bought together, and lots more. This data is incredibly valuable for informing key business decisions and it would be wasteful not to use it to choose which products to stock in physical stores, and in what volume. Data collected from online transactions should be fed back into brick-and-mortar stores to meet customer needs – not operate in silos.

Furthermore, AI can be used to personalise an online store to a user’s taste – making smart recommendations based on customer buying history. So, not only are consumers getting what they want, when they want it – they’re being surprised with products they love, that they didn’t even know about, providing that extra ‘wow’ moment that creates brand loyalty.

Being efficient with forecasting

Forward-thinking beauty retailers are utilising their historical data to forecast demand accurately. Making use of the data collected online and at points of sale is good practice. Combining this with data from the warehouse as well, means that retailers are empowered with a holistic, data-driven view on what products customers want.

Once brands have this information available to them, they can enlist the help of AI to accurately allocate stock accordingly – so it’s no longer a case of going off of intuition alone. This means that when beauty buyers purchase their stock, they do so backed by evidence. This is how innovative retailers are ensuring they hit sales targets and avoid excess stock that ties up capital and erodes margin.

No one knows the beauty industry better than the people that work in it. The role of AI is simply to ensure the business operation runs as efficiently as possible, by making sure the right amount of stock is stored, so customers can have what they want, when they want it – but without brands wasting money and storage on excess products.

Mylo Portas is head of retail at Peak

Main image: Adobe Stock

Author image courtesy of Mylo Portas/Peak

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