Adam Ferrari, Salsify’s executive vice president of engineering
Adam Ferrari: One of the challenges of digital shopping has been the speed and massive assortments that shoppers all over the world demand. AI is beginning to allow retailers and brands to automate and scale the repetitive tasks required to get a product to market. Some examples include the creation of product descriptions and lifestyle images that are personalized to a particular shopper profile or natural language chatbots that can answer questions about an entire product catalog at any time of day. AI is also having a big impact on data analyst workflows, allowing insights on data to be reached more quickly, which in turn will let retailers make smarter and faster merchandising decisions.
RL: ChatGPT has the potential to help retail brands replicate the same personalized advice a customer would expect to get in a traditional brick-and-mortar store. How is this possible?
Eleanya: Brands adopting a customer-first mindset can employ generative AI tools such as ChatGPT to help deliver personalized experiences that mirror, or even surpass, experiences in a brick-and-mortar store. ChatGPT can be customized and integrated into an online shopping flow in a way specific to a brand’s guidelines, products, services and promotions. Over time, ChatGPT also collects data on customer interactions, which can provide data-driven insights into customer preferences and behaviors, helping retailers deliver personalized product recommendations, protection, service and advice.
Ferrari: As a large language model (LLM) AI, ChatGPT is able to first process what a customer is asking for and then generate a humanlike response based on its training and the massive amounts of data it's been exposed to. With intelligent prompting, ChatGPT can generate contextually relevant and personalized shopping advice, answers or suggested products. And with the advent of plugins, these pre-trained models will gain access to real-time data from any source, allowing recommendations to reflect recent product releases, review trends, etc.
RL: How are AI and machine learning actively changing the game in online shopping, such as with larger cart sizes and increased conversion rates?
Eleanya: Retailers integrating AI and machine learning into their online shopping experiences can deliver customers more personalized experiences, provide improved search and product discovery, collect data to enable improved product recommendations and provide customer service pre-and post-purchase. Retailers also use data-driven insights to create tailored offers and marketing outreach to higher-converting customer segments. By improving the online shopping journey, cultivating peace of mind, and better meeting customers' unique needs, retailers see larger average order values and increased conversion rates.
Ferrari: One big benefit of AI and machine learning technology is their ability to analyze large amounts of data and generate advice and recommendations quickly in natural language that makes it easy for most people to understand and apply. Retailers are able to leverage AI’s ability to understand patterns to select and promote the right items to the right shopper and grow total order size. Imagine a world where every shopper has their own private merchandiser who creates the store just for them, and their own personal shopping concierge to help them through the buying process. LLMs are bringing this type of vision into the realm of the possible.