In 1909, Henry Ford famously said about the Model T, “Any customer can have a car painted any colour that he wants so long as it is black.” Retail offerings and customer expectations have changed dramatically since then, of course.
Today’s consumers want products that meet their personal needs, preferences and lifestyles, and they won’t just settle for black. They also want to build relationships with their favourite brands, and they expect retailers to be responsive when they communicate with them.
The rewards are immense for retailers that are willing to reciprocate and offer individual and personalised products and services to customers. And there are powerful technologies available to help.
AI, coupled with data analytics is a strong combination that can give retailers the data-driven capabilities they need to stay ahead of the competition. The technology is especially helpful in transforming established businesses so they can appeal to younger shoppers. That way, traditional retailers can avoid losing out in the fast-moving market where digital-first competitors are trying to steal a march.
Kate's Wedding Dress
In a world where customer behaviour, interests and preferences are constantly changing, retailers need to stay alert. It’s important for them to recognise and, if possible, anticipate product trends. It’s also necessary to analyse and understand buying behaviour to stay ahead. And businesses must be able to respond quickly to spikes in demand as they happen. These are all things that AI and analytics can assist with.
Retailers who can keep up with consumer trends stand to clean up: Kate Middleton’s wedding dress exemplified this in 2011. It took just 36 hours for the first bride to be seen wearing a replica one; the global race was on to copy and sell this must-have item.
Kate’s dress aside, the point is to have a heightened awareness of what the customer wants, and this is where AI can become a business driver. Particularly when the business applies it to all the information it's able to gather on its customers.
Then, by creating what has been termed a single customer view (SCV), it’s possible to deliver a personal and highly relevant customer experience. By doing so, you can optimise sales, and increase brand loyalty and customer lifetime value.
The majority of today’s retailers do not have a single view into their customer data. Many have made headway with digital loyalty initiatives, perhaps pioneering loyalty cards or membership schemes. A lot of stores have also developed their social media channels, or online shopping sites and micro-sites, or expanded their relationships with third party suppliers or in-store franchises. But the different activities are rarely joined up, so data stays in silos.
The idea of an SCV is to gather information about your customers and assemble it into one single record you can use to give them the personal VIP treatment. It means building a picture of the ways in which the customer engages, whether that’s through a phone or desktop, via the website, email or social media, or physically visiting a store.
It also means knowing when they like to interact, where they buy, and why they are engaging with your brand. And crucially, it involves tracking their browsing and buying behaviour to work out what they like to purchase, how much they spend, and how often they shop with you.
Armed with this information, retailers can apply AI and data analytics to sell customers what they actually want.
One way that AI can help is to analyse the SCV to enter the customer’s mindset, grasping their interests and discovering trends. With this information, retailers can put customers into segments - or micro-segments - of similar types of buyers. These could be divided by geography, income, age, or preferences, among other criteria. It makes it easier to target individuals with exactly the right offer at the right time, using the right channel for them, and address them by name.
AI can also be used with the SCV to predict future demand based on customer past interests, or their purchasing history. For example, they might buy an item once a year, or every three years. This information can inform sales and marketing campaigns that can be personalised to the individual to maximise sales.
AI and data analytics are helping businesses to innovate personalised offerings and customise their retail selling strategies. For example, Boots is partnering with ITV to launch AI-powered ‘Shoppable TV’ where viewers with a smart TV can buy items they see on screen during Love Island, completing the purchase on their phone.
Meanwhile, retailers and service providers are adding emerging technologies into the mix to further combine the physical and digital world and enhance the customer experience.
Luxury fashion brand Burberry has designed virtual outfits for Honour of Kings, one of China’s most popular video games; and online casinos are offering interactive 3D experiences through VR. And in the physical world, stores have continued to use in-store tablets and kiosks for customers to search and view products and stock levels, and develop mobile phone apps that boost customer engagement and loyalty.
At WORTH, we are finding that our retail business clients are moving away from deploying technology for its own sake, which is a refreshing departure. Instead, they’re looking for practical opportunities to use AI, analytics and rich interfaces to give customers a personalised and relevant shopping experience. What Henry Ford would have made of it all, one can only imagine.
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