Ecommerce merchants have always been early adopters of new technologies as they aim to meet changing customer needs, increase efficiency, and boost sales. As part of this, many have already embraced AI within their operations. However, the rapid rise of generative AI, led by chatbots such as ChatGPT, opens up transformative opportunities beyond traditional AI, bringing the ability to understand customer intent and to dynamically create one-on-one content. This will help merchants engage more deeply with their customers and automate their operations, initially in five key ways:
1 Making search hyper-relevant
According to Nosto research, 80% of consumers say they’ve left a website due to a poor onsite search experience, potentially costing brands billions in lost sales. Consumers want their search results to be much more relevant, saving them time and streamlining their product discovery journey. The large language models (LLMs) used by generative AI tools such as ChatGPT provide the ability for merchants to meet this need for hyper-relevance.
As well as understanding synonyms, common misspellings of product names and slang, LLMs can also harness advanced techniques such as vector search. This approach uses machine learning models to turn text into numerical representations known as vectors. These better understand the meaning of a search, meaning they can provide a match even if the words used in the actual query aren’t present in the product description.
Customers will be able to make much more detailed, advanced natural language searches. They might ask very specific questions such as “Blue party dresses for a 1930s themed cocktail party” and receive a fast, accurate and complete response. And, as LLMs continually learn from every interaction, they will use customer data to constantly improve the search experience.
2 Driving more efficient merchandising
Rightsizing inventory is crucial to retailer cashflow. No-one wants to be stuck with unsold Santa hats in January, for example. Equally, merchants don’t want to miss out on opportunities by not having enough inventory of the latest hot product. AI can use historical data to accurately predict future demands, enabling merchants to automate inventory management, ensuring the right volumes of the right products at the right time. Importantly, it can reduce the lag between spotting demand and making goods available online.
Over time, we will see AI identifying specific events that are happening on a local level and using this data to order relevant products, even linking directly to factory systems to increase production. It might analyze a long range weather forecast and decide that an unexpected cold snap will raise demand for scarves. Or, if there’s a Comic Con in New York, it can ensure that certain must-have products being promoted at the show are available — essentially automating some of the role currently done by human merchandisers.
3 Highlighting growth opportunities
Merchants already monitor customer behavior and use this understanding of intent to place them in specific segments and trigger pre-selected actions. However, generative AI expands the possibilities for segmenting customers, automating the process by removing manual labor, and making it more dynamic.
Rather than simply identifying broad groups that may be interested in specific products, generative AI will analyze complete datasets in real-time, spotting anomalies. From this, it can flag more granular potential opportunities to merchants and provide suggested strategy and actions around campaign creation and management, through tools such as AutoGPT, with content and ads dynamically generated via solutions such as MidJourney.
So, if a prospect shows interest in a style of walking jacket, they can be shown ultra-personalized content, including product and lifestyle images, potentially unique to them. For example, a hiker shopping from Utah could see the product displayed on a model hiking in Zion National Park. This opens up disruptive new opportunities to engage with prospects on a truly 1:1 basis, while still keeping human ecommerce marketers in the loop.
4 Automating product catalog management
A merchant might be offering hundreds of thousands of items on their site. Manually managing such a vast product catalog and sharing information online, via ads and in content campaigns, is time-consuming and leads to a high risk of errors occurring. Generative AI dramatically increases efficiency and accuracy when it comes to managing your product catalog, removing back office tasks and the risk of human error.
For example, it can be used to create automated yet compelling product descriptions, titles and other content that will appeal to prospects, based on analyzing product attributes from across the web. Generative AI can even be used to dynamically create relevant product images to supplement existing assets or choose the most relevant photo from a pool of uploaded images, whether produced by the merchant or from user-generated content (UGC).
5 Delivering personalization at scale
Personalization is not new, but again generative AI accelerates what can be done, in terms of the depth and the range of content created.
Take image personalization, which has previously been a challenge due to its complexity. With generative AI, it can be delivered at scale, potentially on a 1:1 level. Based on shopper behavior you can provide a completely tailored experience around products, content, and discounts, all dynamically created in real-time. Rather than just rotating banner images or picking from a library of visuals, merchants can generate imagery on the fly. For example, you can deliver an outdoor or city-themed image experience depending on the customer’s preferences.
This not only increases engagement and sales, but reduces costs for creating assets, as existing photography can be modified and personalized in real-time.
Generative AI is already transforming how merchants operate and engage with customers and prospects, helping deliver a compelling experience that leads to greater efficiency and higher conversion rates. However, we are still at the beginning of the AI journey, with disruptive new use cases continually emerging as LLMs become better-trained and their capabilities improve. In a fast-moving field, merchants therefore need to build up their generative AI skills and knowledge and apply the technology in key areas across their operations to drive competitive advantage moving forward.
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ABOUT THE AUTHOR
Jan Soerensen, General Manager, North America, Nosto
Jan Soerensen is the General Manager of North America at Nosto, an AI-powered Commerce Experience Platform. Jan has grown retail and SaaS companies to become leaders in their space and across international markets. He regularly comments on the state of ecommerce.