In the eCommerce landscape, Artificial Intelligence (AI) is reshaping the game. This blog series explores how AI’s intelligent algorithms are revolutionizing online businesses, from personalized product recommendations to efficient inventory management. Join us for insights on leveraging AI to enhance the digital shopping experience and overall success in eCommerce.
Generative AI has pushed into nearly every corner of the B2B tech landscape, forever transforming ecommerce and the buyer’s journey. Innovations like ChatGPT can become a valuable tool for ecommerce sites by generating product descriptions, personalizing recommendations and creating visual content. It’s already happening, with instances appearing across some of the most popular and well-trafficked sites, apps and tools.
However, trusting generative AI on ecommerce sites comes with risks. Marketers and ecommerce managers need to be cognizant that Generative Pre-Training Transformer (GPT)-driven interactions are highly dependent on data quality when guiding consumers through a positive, engaging, personalized buying experience.
Consider the following preparation steps needed to bring generative AI into ecommerce, in order to deliver a competitive advantage and ensure ideal customer-buying experiences.
OpenAI introduced a new generation of advanced Large Language Models (LLMs) that do not require data scientists. Rather, engineers with the skill to design and create effective prompts are behind the technology’s ability to produce a conversational experience that leads customers to a specific outcome. Prompt engineering involves understanding how GPT works, what data it was trained on and applying its strengths for a better customer experience. Since coding skills aren’t necessary, it’s more accessible to marketers.
GPT has gained notoriety for its ability to generate copy with only the slightest of prompts. Marketing teams can take advantage of this capability to accelerate content generation. Yet if the underlying data is incorrect, incomplete or of poor quality, the AI-generated content will be the same. This follows the traditional garbage in/garbage out dictum of computing. For generative AI to work, it’s critical that all underlying data driving the model is fully correct prior to generating new content. Otherwise, the customer experience will be negative.
One of the fundamental issues ecommerce businesses struggle with is being able to engage consumers on a human level. For many organizations, this is often due to product and catalog complexity, with too many products that don’t easily align with natural buyer discovery behaviors. Shoppers often come from different geographies, backgrounds and knowledge levels, and have different purchase criteria. Meanwhile, consumers expect an ecommerce site to quickly understand their wants and needs, and not require them to be a domain expert to search for a product. Using LLMs, ChatGPT can help ecommerce businesses engage each consumer individually, using the terminology and human-like language that best suits their requirements.
For LLMs to provide business value, they must be used as part of a larger technology solution. With messy, inconsistent and unstructured product data being pulled into ecommerce sites from product information management (PIM) systems or other data sources, LLMs can’t fix those underlining issues. GPT can generate text and provide conversational responses that could be inaccurate or nonsensical. These responses, called “hallucinations,” are a byproduct of the way LLMs are created from source data, and are almost unavoidable.
Fundamentally, LLMs do not know what is true and what is false; they simply know what sequence of words are most likely to be chained together (“canoe” and “paddle” and “lake,” for example). For ecommerce sites to use LLMs to the fullest in delivering meaningful and accurate advice during the buyer journey, care and attention should be paid to creating an ecosystem that supports every step of the product discovery process.
With the right elements in place – language framework, data and operations, context, and ecosystem – ecommerce and marketing leaders are in an ideal position to make the most effective and productive use of generative AI. The data becomes more useful and can provide accurate insights into customer interactions. In turn this can drive higher ROI on ecommerce campaigns and can also inform product innovation.
We are at the dawn of a new age of generative AI and LLMs. This technology holds great promise for consumers and businesses alike in transforming the buying experience. Yet realizing this opportunity requires preparation and a full understanding of the limitations of generative AI within ecommerce.
Jonathan Taylor is CTO of Zoovu
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