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Leveraging Generative AI for Retail Product Descriptions


shelves in a clothing store


The retail sector is undergoing a transformation with the integration of Generative AI, streamlining processes from product design to customer engagement. This post briefly examines the utility of Generative AI in creating product descriptions and optimising retail strategies for an omni-channel approach, featuring real-world applications.


Generative AI enables retailers to automate the creation of product descriptions. This technology, when harnessed effectively, can generate detailed and varied product narratives at scale, which not only save time but can also enhance the SEO of e-commerce platforms delivering ongoing conversion improvements.


For instance, Microsoft's Azure OpenAI Service uses GPT-4 to offer copilot templates that help retailers build personalised shopping experiences. These can suggest products to customers based on natural language queries, mimicking the assistance of a store associate in a physical store. A good example can be seen with Canadian Tire Corp’s implementation of an AI shopping assistant for automotive products​ (Source)​.


McKinsey thinking highlights that gen AI can accelerate growth by analysing large amounts of data to identify unique audience segments, and driving the creation of personalised outreach, and enhancing customer experiences through hyper-personalised content​ (McKinsey & Company)​. For example, Grid Dynamics offers a Generative AI Product Design Starter Kit, which assists retailers in creating and editing product designs swiftly using textual descriptions and reference images​ (Grid Dynamics)​. This ability to rapidly prototype and customise products directly addresses customer needs, leading to more effective and personalised online shopping experiences.


Sephora, a leader in the cosmetics industry, showcases how an omni-channel strategy, underpinned by data and technology, can redefine customer experience. They've employed AI and augmented reality within their mobile app, allowing customers to 'try before they buy' with their Virtual Artist feature. This tool scans the user’s face and matches their skin tone with suitable colours and providing the option to purchase products online or find them in-store​ (ContactPigeon | Blog)​.


For retailers, the transition to AI-generated product descriptions and an omni-channel strategy is likely going to prove revolutionary from personalising the experience, increasing find-ability, improving the customer journey, increasing efficiency, to driving more sales.


However, it is going to be essential to navigate this path carefully, considering the integration with existing systems, alignment with brand voice, and ensuring that AI-generated content resonates with target customers while remaining SEO-friendly. Many, if not most, retailers are still struggling with significant legacy systems issues and the associated data quality challenges that brings. This is going to seriously slow progress when it comes to deploying generative AI at scale.

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