As with many other industries, the capabilities of Generative AI are making a real impact in the retail industry, especially in the quality and scale of the customer service that retailers can deliver. Research has found that the majority of retailers are already using GenAI to boost their customer service capabilities, and this is helping them meet the ever-increasing expectations of consumers.
With these technologies becoming an essential for businesses across the sector, this blog explores the most effective ways to apply Generative AI in retail.
Read more: Explore Ciklum’s Guide to Practical Generative AI Examples
The potential of Generative AI in retail can be transformative in several different areas, thanks to its ability to automate interaction and support a vastly expanded scale of marketing and communication services.
With the right deployments in the right places, the AI benefits can include:
Large Language Models are able to access customer databases and can work out the types of support and messaging that individual customers are looking for. This is based on incredibly detailed customer data, such as online behavior, and previous purchases and returns, that enables detailed profiles of individual customers and prospects to be constructed. This wealth of data and AI analysis allows most types of customer service, from problem resolution to product recommendation, to be refined and personalized at a level that human teams simply wouldn’t have time for.
Customers want fast, stress-free and personalized service, perfectly aligned with their specific needs and preferences. When they get it, they feel more valued and will be more likely to return to the brand for more purchases in the future. This is crucial for long-term success at a time when it’s never been easier for consumers to shop around: according to Salesforce, 89% of consumers who receive a positive customer service experience are more likely to make another purchase from that brand.
In a global online marketplace, consumers expect to be able to get support in their native language. GenAI’s abilities to translate queries for customers - and for human agents dealing with them - can break down the language barriers of fast, effective customer service.
GenAI can analyze customer interactions and measure the performance of customer service agents, and satisfaction rates more widely. These insights can support better decision-making around improving service, and where automation can be applied for maximum staff efficiency and cost-effectiveness.
The same principle can be applied to product development, where accurate forecasting of consumer sentiment and trends can inform the creation of new products, and the marketing campaigns that promote them. This can be instrumental in getting the right products to the right customers before the competition.
As Generative AI in retail has taken hold, the practical use cases for the technology have spread across the sector. Many retailers are already successfully using GenAI for:
The capabilities of chatbots powered by Generative AI are improving all the time. They are increasingly able to mimic human responses, and quickly resolve more complex customer issues rather than just those that are straightforward and repetitive. Their ability to understand customer voice through Natural Language Processing, and operate 24/7, further underline their ability to satisfy customers who need help.
Generative AI massively expands the scale at which written or visual content can be produced for a retailer’s digital footprint, as it can be created on the back of user prompts which are relatively quick to put together. This can include crisp and compelling product summaries for listings, and for marketing materials like blogs and product guides.
As Generative AI can segment customers into highly specific groups, based on demographics, behavior and preferences, marketing campaigns and offers can be highly refined to have maximum resonance with individual customers. This extends to product recommendations, where GenAI can work out which products are most likely to be of interest to specific customers, maximizing the chance of a purchase while simultaneously making the customer feel valued.
Using Natural Language Processing means GenAI can analyze the detail of every customer review, including those given in the form of voice, and assess them for positivity and negativity, as well as specific emotions. This allows sentiment and performance to be more accurately measured, and for potential improvements to be identified more easily.
Conversational virtual shopping assistants mean that customers can get the personal, intuitive service they’re looking for without the need to wait for a human staff member. These virtual assistants can field common queries, suggest potential products based on customer data, resolve any issues that arise, and guide customers through every step of the sales journey.
Generative AI is increasingly being used to dovetail other AI applications. A good example of this is the ability of AI-driven chatbots to handle more complex and unique customer issues, freeing up valuable staff time to work in areas that need a human touch.
Alongside this, Generative AI in retail will continue to evolve at pace in the months and years ahead. In particular, we expect the use of multi-modal AI - where Artificial Intelligence incorporates data from multiple sources simultaneously - to become more widespread, making AI even more dynamic and intuitive. Additionally, autonomous agents, powered by advanced machine learning and algorithms, will be able to adapt to changing conditions and take more contextual actions without the need for user input.
These innovations will unlock even more efficiencies and customer service capabilities for retailers - but you may find that you need expert help to make the most of the technology. Talk to Ciklum today to find out how we can support your goals.