Technology is evolving at such a rapid pace that most people can only be aware of their lack of knowledge. Even among American CEOs, many of whom are leading the companies helping to create the digital revolution, only 35% are "clear how robotics and artificial intelligence can improve customer experience." However, as price comparison becomes easier, the ability to improve customer experiences in a £360 million a year UK retail market is an opportunity worth seizing.
The optimism surrounding the potential of big data and AI in retail is not yet matched by the magnitude of online sales. Only 10% of core retail purchases are made through the internet, and in the luxury goods market, where personalised experiences are highly valued, this decreases to only 4%. Therefore, although AI has huge potential, particularly for luxury brands, in-person purchases remain significant. Local stores still play a crucial role in fulfilling customer impulses on essential items, although the convenience of developments such as drone delivery with Amazon's Prime Air are likely to result in increasing online purchases replacing this in the future. High-end retailers will also maintain a physical presence as the shopping experience cannot be completely replicated online, with many customers valuing human interaction and attention from personal shoppers.
Nonetheless, technological advancements and the convenience they provide are creating huge changes. Crucially, the acts of buying and shopping are becoming distinct. Buying is transforming into a process where customers simply add repeat orders to a virtual shopping list, whilst shopping is increasingly valued as an 'experience'. Consumers are choosing to entrust the chore of buying essentials to AI, such as Amazon's home assistant, 'Alexa', which offers the possibility of purchasing goods through just voice command. Almost 50% of consumers are already open to buying items through chatbots such as Alexa, a figure which looks set to increase as the buying process becomes more automated. Therefore, retailers of essential goods will be forced to compete on price to a greater extent, as AI will ease price comparison and be unaffected by advertising in the manner consumers are.
Conversely, luxury and fashion retailers will be able to utilise AI to take advantage of consumers' emotional involvement with purchases, and the experience of shopping, with 40% of luxury good purchases currently influenced by consumers' online experiences. These experiences are positively shaped by 'personalisation' in customer service, and firms must take advantage of this in new and innovative ways. Such innovation will involve advanced marketing strategies, designed to increase emotional engagement with these products. Companies that will continue to rely on consumer choice, rather than merely price competitiveness, must act quickly to gain a competitive advantage. Some forms of AI are already being designed to gain a greater understanding of consumer interests based on their social media presence and online searches, including of images. Other developments include the growth of wearable technologies, enabling firms to collect data regarding the customers' lifestyles, rather than merely their online interactions with retailers. This offers retailers deep insights into their customers' desires, enabling them to tailor recommendations based on, among other data, vital statistics, current location and measurements. Most retailers understand the potential of these opportunities, and PwC research found that 72% of companies plan to use advanced data analytics to boost customer experience.
One example of the potential of AI to personalise 'the consumer journey' is in fashion, with many customers looking for unique products that reflect their personality and style. In addition to improved marketing, companies are adapting to use advanced analytics and big data to better respond to new trends, anticipating consumer preferences. For the foreseeable future, computers lack the creativity required to understand the drivers behind changes in fashion. However, by combining the use of big data to power machine learning, and the creativity offered by human stylists, fashion retailers will be able to respond to changes in tastes more adeptly than in the past. Fashion retailers will also use big data to reduce costs by constructing customer profiles. Currently, 25-40% of online clothing is returned as consumers purchase several items in similar sizes and colours and then return those they like least, known as bracketing. Tracking the items which are not returned to develop customer profiles of style preferences and precise sizing will enable fashion retailers greater understanding of their customers. This understanding will offer convenience for customers and more precision in sales strategy and marketing for firms, whilst reducing returns and waste.
We are living through the fourth industrial revolution, where tastes are changing ever more rapidly, and purely fulfilling demand is no longer sufficient to sustain a competitive advantage. Companies must sample consumer behaviour, identify unmet needs and, consequently, develop new products to meet these needs. As buying and shopping become more distinct, many firms will therefore evolve into information businesses, requiring new technologies to offer conveniences for shoppers and experiences for buyers. But fundamentally, understanding customers and their desires remains crucial for success.