The impact of AI on the UK retail industry
In this report, Retail Economics (and international law firm CMS) start by plotting some of the applications and implications of AI throughout the customer journey from the perspective of the customer and the retailer, using the five stages of the Retail Economics Customer Journey.
While not exhaustive, at each stage we look at the most prevalent or game-changing applications and, using the insights gleamed from our surveys, examine how ready consumers and business really are. We then take a deeper look at how businesses plan to adopt AI technologies in their organisations, the areas they will target for investment, and the key challenges they foresee.
Once the preserve of science fiction movies and books, Artificial Intelligence (AI) is not only a reality today but an increasingly common feature of life. Through voice and image recognition, natural language processing and machine learning, our smart phones and speakers are an integral part of our day-to-day. In this report we look at how AI is helping to answer questions like:
- How can a retailer ensure that a particular brand or promotion will catch the eye of a millennial shopper when browsing products and prices online?
- How do they convert awareness into a sale online or in store?
- Once a product has been purchased online, what technology is needed to ensure the quickest and most cost-effective delivery to a customer?
- What about aftersales support, how is that best provided?
- And what can a retailer learn from a purchase about a shopper’s buying habits which might help prompt further sales in the future?
What features below is extracted content from the report on a chapter which focusses on the use of AI in the first stage of the customer journey - Awareness & Influence.
Stage 1 of the Customer Journey (consumer perspective) - Awareness
Awareness is a primary battleground for any consumer brand or retailer to win in the hunt for sales and profits. There are various ways a customer can become aware of a brand, including TV or print advertising, personalised emails, recommendations from friends and family, as well as targeted online advertising. Retailers, seeking any advantage they can in an increasingly competitive marketplace, are turning to AI technologies to help them create greater customer awareness. Two of the most dominant, if still nascent, that are being used are personalisation and product recommendations.
It is generally accepted that shoppers are more likely to purchase items in-store or online from retailers which send them relevant, personalised promotions and ailored offerings. Current personalisation includes online fashion retailers serving personalised landing pages, only displaying clothing available in a customer’s ize and or preferred brands. Shop Direct’s technology allows 1.2 million versions of its very.co.uk landing page. Amazon attributes 35% of sales to its personalisation strategies (McKinsey). In the past it has been possible to personalise experiences using simple rules — now machine learning can analyse normous and seemingly disconnected sets of data deeply and quickly — and then act in real-time based on that analysis. This will take personalisation to a new level.
CMS’ consumer panel survey found that while shoppers wanted greater personalisation only 45.3% believed targeted online adverts – the most prevalent current application of personalisation – provided appropriate content to them. Nevertheless, through advances in technology personalisation will continue to be a key
tool for retailers. The survey results show the essential mantra to follow is: ‘make sure it is effective and that shoppers’ trust is not lost’. We are reminded of the legendary example of a retailer who accidentally exposed the pregnancy of a high-school teenager to her parents by sending her coupons for baby clothes and cribs.
One of the most recognised AI powered applications used today is the automated suggestion of products and services to shoppers. These AI-powered recommendation engines vary greatly in sophistication but advanced algorithms can correlate disparate data such as purchasing habits, images viewed, social media content, location or weather in real time. Retailers are already able to suggest holiday items for shoppers who recently booked an airline ticket. Adding biometric data into the mix will allow retailers to identify customers as they walk into a shop and then personalise their in-store experience. Retailers will be able to suggest garments that will fit a customer’s body shape. On page 20 we analyse how such use comes at a time when regulation, most notably GDPR, is protecting the individual’s rights around such data.
More sophisticated personalisation requires more personal data, however our survey of shoppers showed that more than half would not be comfortable sharing personal data, such as health, age, body shape and dietary habits, to enable companies to provide more targeted product recommendations. Although a key finding was that younger consumers are three times more likely to share highly sensitive data than older shoppers. Targeting younger shoppers with solutions that use sensitive data-is an obvious strategy for operators in the clothing & footwear, food & grocery, and health & beauty sectors.
Stage 1 of the Customer Journey (retailer perspective) - Influence
Hyper-personalised multichannel marketing strategies provide an opportunity to influence consumers in ways never seen before, such as using data to pull customers to a product that could genuinely enhance their wellbeing rather than pushing potentially unwanted items on them. Alternatively, future subscription services will provide products based on a customer’s behaviour rather than requiring an active purchase. Currently we are seeing AI technologies increasingly being used for multichannel marketing.
According to a global survey conducted by Forrester Consulting and commissioned by Emarsys, 54% of retail marketers are using AI-driven personalisationacross channels to drive growth in their business. The technologies will deliver multichannel marketing campaigns that seamlessly target onsumers with personalised content and experiences across websites, mobile platforms and within physical stores. In the future this may include the use of AI- ssisted facial recognition to register returning customers in a store, tracking data of a customer’s journey through a shop to optimise store layout, or optimising the unctionality and design of a site based on a user’s unique profile. In contrast to the consumer findings our survey shows that businesses have a high degree of confidence in AI’s ability to deliver accurate marketing content. But is this trust well placed? Nearly 60% of businesses trust fully automated AI-driven marketing ampaigns to deliver content to their customers. In contrast, only 45% of customers believed personalised adverts displayed to them were relevant.
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How are retailers and brands adopting AI technologies?
Companies across Britain are overall positive about AI-powered technologies and their ability to improve their businesses and interactions with consumers.
This is likely because there are a host of areas which can benefit from AI, with our research indicating that 62.5% of retailers and consumer organisations believe that achieving ‘more efficiency in the supply chain’ presents the biggest opportunity for them. Just over 53% said that realising cost savings would provide the greatest benefit followed by 46.9% who feel that ‘creating more meaningful relationships with customers’ would have the greatest impact on their operations.
When asked which AI-related technologies would have the biggest impact on the industry, nearly 70% of the organisations polled said that virtual assistants would be one of the most positively disruptive forces in the industry, followed by 59.4% who said they believed that the ‘internet of things’ would have the greatest impact. Chatbots, autonomous vehicles and dynamic pricing were the next most cited technologies. Perhaps most surprisingly were the technologies that scored the lowest. Despite the media interest, high profile technologies such as drones, virtual reality and 3D printing do not appear to be high on companies’ radars.
Identifying which area of a business to target for AI investment is a fundamental exercise for retailers to carry out. Customer engagement and enhancing the way in which goods reach consumers seem to be the top priorities. 65.6% of businesses in our survey felt that ‘sales, marketing and insight’ was the most essential area to focus on, in part because improved sophistication of AI-centric marketing strategies is resulting in a better return on investment. More than 53% of retailers said they would focus AI investment on their warehousing and distribution divisions, while 46.9% said they were keen to improve their buying and merchandising through the use of AI. Back office functions such as HR and finance do not appear to be prominent targets for investment.
Challenges of implementing AI
Shortage of AI expertise
Adopting any technology can be tricky for a business but AI technologies may additionally involve job losses and trust issues with customers. However nearly 60% of the retailers and consumer brands we spoke to said they felt that a ‘lack of specialised skills’ was the principle challenge they faced in rolling out AI within their organisations. This goes some way to explaining why 75% of organisations polled think they will use external technology partnerships to enhance their AI capabilities. The 38% that said they would develop capabilities in house will need to reflect on how to plug the apparent skills gap.
Legal and regulatory barriers
46.9% of the organisations we polled said that one of the main barriers to AI investment involved the legal
and regulatory issues related to its use. The complex patchwork of rules governing the use of AI within an organisation can be a minefield to navigate. There are
a host of laws around the use and storage of personal data while some AI-technologies, such as a dynamic pricing, may fall within the realm of competition law.
Trust and ethics
Perhaps in answer to our research around trust (see page 15), in order to properly handle the issue of data security, companies need to firstly not underestimate its importance and secondly think about hiring skilled people to help manage data ethics in an organisation. This was reflected in our survey where over 60% of companies think they will need to invest in roles managing data ethics. As AI technologies make more ‘decisions’ within organisations, there will be greater scrutiny from customers and regulators as to how these decisions are made. We believe a key component of any AI strategy will be the use of an AI Ethics Board.
AI-readiness amongst consumers is hugely variable
Businesses also need to reflect on whether AI is always called for in every instance. Just because something can be done, does that mean it should be? Our survey of consumers shows that perceptions can differ wildly by technology type and by age category. There is also significant divergence between how receptive consumers claim to be and how ready organisations perceive them to be. Consumers and retailers are not always on the same page. For example, while some businesses are investing in drone technology and autonomous in-house delivery in a bid to lower logistics costs, consumers were far more reticent about these
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