Defining the opportunity: AI in retail

Technology has disrupted the retail market

Technology has transformed the retail sector over the past decade. The evolution of e-commerce has led to significant structural changes to retail businesses, as many consumers have welcomed the convenience and broadening of options that ecommerce brings. And retailers have had to adapt to changing consumer behaviour. Now, it seems like there could be a new wave of technological transformation in the form of artificial intelligence.

In fact, several new strands of technology such as Artificial Intelligence (AI), Augmented Reality (AR), and Virtual Reality (VR) will provide significant upcoming opportunities for the retail industry. AI is already being used in the retail sector – for example, ASOS’s ‘Visual Search’ tool – which scans a user-uploaded photo and identifies similar looking products using AI technology. And with Google’s new ‘Circle to Search’ function, customers can identify and search based on part of an image, allowing them to look up and purchase the handbag that their favourite influencer is carrying. Tools like these could enhance the power of digital marketing strategies, keeping shoppers engaged and driving retailers’ revenues.

Demand for this technology appears strong, particularly amongst younger consumers. 76% of Gen Z’ers expect AR to improve their shopping experience, and 23% expect a robot or AI assistant to be styling them by 2040. Others are already looking to AI to provide them with bespoke styling advice, like asking ChatGPT to identify the best colour palette based on their skin tone. With 89% of retailers planning to invest in generative AI in the next 18 months, it looks like this demand could soon be met.

AI could simplify things for the retail industry

Like other businesses, retailers can use AI to improve back-office efficiency and reduce operating costs. This could include:

• Using AI software within internal chatbots to prioritise and direct requests within departments, or help employees to quickly access information from an aggregated source.
• AI as a designer e.g. in product development, brand, or online content generation and designing based on market trends and historic sales.
• Inventory and wider supply chain management e.g. awareness and management of stock levels, forecasting demand, assessing pricing, and streamlining logistics operations.
• Evaluating location options for physical stores and deciding stock allocation and placement in-store based on historic sales data.
• Collecting and translating consumer insights e.g. trading statistics, customer preference data and product reviews for internal evaluation, product development or marketing.

Despite these benefits, it will likely be the applications that help to improve customer experience and increase sales that are more noticeable.

Enhancing online retail services using AI

Retailers could help boost online shopping by upgrading online shopping platforms, using AI to support a seamless shopping experience through user-friendly websites and app interfaces. For example, retailers are looking into conversational product searches driven by generative AI, expanding on existing keyword searches to improve the efficacy of their search engines. To make platforms as accessible as possible, AI can also be used to improve closed captions or standardise audio product descriptions.

Retailers could also utilise more accurate real-time price comparison technology on their websites to better advertise value against competing brands. And improved inventory management and stock information online could facilitate quicker click and collect services for customers, also driving footfall into physical stores. Implementing these approaches would help with convenience and transparency for customers, overall improving customer satisfaction and retention while increasing the chance of repeat visits and cross-selling.

56% of Gen Z consumers want shopping to become more personalised and recent trends indicate that brands offering increasingly bespoke services are succeeding. Without requiring any additional labour, AI used within online platforms should be able to better interpret customers’ needs based on their online metadata and historical activity to better target advertisements and recommendations. Using AI could also enhance existing customer service chatbots to improve and speed up responses to basic queries, or to create a virtual personal shopping experience. In this case, product suggestions could be provided based on generative AI’s ability to understand the customer’s search terms and preferences, similar to Klarna’s ‘smoooth shopping’ tool on ChatGPT.

Try before you buy with AI  

The ability to virtually ‘try on’ garments could revolutionise customer engagement in the fashion and beauty industry and has the potential to reduce returns from online orders by 64% on average. Google is already rolling out a ‘virtual try-on’ feature which allows customers to view garments across multiple retailers on real models with different body shapes, skin tones, and hair types. This is possible through a generative AI function which emulates the fit, drape, and stretch of the clothing. Online retailers could also install similar technology on their own sites. For example, Walmart customers can now view the garments as they would fit using their own photos.

To go one step further, combining this kind of AI functionality with AR appears to be one of the most significant opportunities to personalise shopping. AR already enables consumers to visualise themselves wearing products like cosmetics, jewellery, shoes, or eyewear using their smartphone camera. AI algorithms can increase the visual accuracy of AR and at the same time analyse images to identify the right products, e.g. the right shade or formula of foundation. AI company Perfect combines AI and AR tools with a chat assistant which can provide unique skin care and make-up product recommendations and advice based on facial characteristics.

Elevating the in-store experience with AI

More than half of consumers in the UK and Europe prefer to shop in-store and, consequently, physical retail remains hugely important for retail businesses. In our Global Live-Work-Shop Survey, overall in-store experience was cited as a key driver of preference to shop offline by 25% of consumers. There are many methods for retailers to optimise their customer’s experience in stores, and it’s easy to see how AI could help brands to innovate and attract customers to their stores.

It should be possible to implement many of the applications to online retail, to the shop floor. For example, incorporating more interactive technology in stores could better engage customers, draw in footfall, and free staff to focus on customer service roles. Taco Bell is already implementing voice recognition by AI at many of their drive-thru sites, intending to free staff while improving order accuracy and reducing wait times. We could even see AI robots take over some lower value or time-consuming tasks, such as counting and identifying gaps in stock in stores.

Given the customer demand for personalisation, time spent in stores could be maximised by elevating the personal shopping offering; using AI for this would also offer a fresh perspective for customers. With better communication and analysis of customer data using AI, digital tools can enable personalised services to grow in a labour efficient way. There might be opportunities to incorporate tailored recommendations or target discounts towards those shopping in stores, based on their preferences recorded online. Utilising AI technology could also help customers to find the products that they want more quickly or give live price comparison or stock information on the shop floor.

Retailers could install AR tools or smart fitting rooms for a new and easy try-on experience. Smart fitting rooms contain tech-enabled mirrors which allow the user to visualise wearing the garments, request another size, get style recommendations, and complete a purchase. Supported by AI, this technology can analyse customer likes and dislikes and their time spent in-store. AR mirrors can also make a storefront statement, like Coach’s Soho mirror, which aimed to engage customers by inviting them to virtually ‘try on’ their handbags in the mirror as they pass by.

AI should refresh, but not takeover retail

As with all applications for AI, there are some reservations about its rapid widespread use in retail. Retailers are most concerned about data privacy and security in relation to generative AI, which cannot be compromised. We can also expect the regulations in this space, and around generative AI more broadly, to evolve.

At least in the short-term, there is potential for AI to produce biased or incorrect outcomes and therefore, implementation will require human validation. Realistically, a layer of human involvement will remain crucial in the longer-term to maintain a balanced approach to customer service.

Despite the significant technological opportunities for digital retail, there are no doubts about the importance of the physical store. Brick and mortar locations communicate a brand’s image, but also facilitate essential physical interactions with products, services, and retail staff. Retailers should use AI to complement their physical retail experience and optimise business logistics but should be careful not to compromise product quality or customer experience, which ultimately sustains the longevity of a brand.