Wayfair, an American e-commerce company based in Boston, Massachusetts that sells furniture and home goods online is going through a bit of generative AI makeover. There is no stopping.
Recently, the company has partnered with Google Cloud and has been working closely with them to optimise their operations on the platform. “What’s great about Google is the focus on AI, ML, and generative AI,” said Fiona Tan, CTO at Wayfair, in an exclusive interview with AIM.
“We can run Google’s models, like Gemini, but also third-party models like Claude, which can outperform others in specific cases.”
Interestingly, Wayfair has a separate partnership with OpenAI as well.
The company’s move to become fully cloud-native means they’re ready to embrace new models as they evolve. “If something doesn’t work today, we can try again in a couple of weeks, and it might be vastly better,” she noted.
Currently, Wayfair has over 22 million active customers and offers more than 30 million products from over 20,000 suppliers in the US, Canada, Germany, Ireland, and the UK.
What about India? Rohit Kaila, Wayfair India’s head of technology, sees an opportunity for AI, especially generative AI, to bridge the gap in a country so rich in diversity.
“This presents a significant opportunity for us to leverage AI, particularly generative AI, to adapt to local nuances,” Kaila said.
Now, if you think about handling something as large as a catalog like Flipkart’s across an organisation, the AI tools available today are far superior, enabling much faster turnaround times and vastly improved user experiences.
“Previously, companies would group customers into five or six categories and tailor experiences for each. Today, generative AI enables Wayfair and others to craft personal shopping journeys for each customer—every time they click,” he stated.
Pioneering AI-First Search
Wayfair claimed that it has always been at the forefront of using AI and machine learning to transform e-commerce search to help customers find and connect with products. “In e-commerce, AI and ML are broadly integrated into several areas. Search functionality is a key one, helping to understand customer intent and match products to search queries,” shared Tan.
Beyond search, AI is revolutionising performance marketing, where it fine-tunes spending and ensures ads reach the right audience.
Tan believes with generative AI entering the industry now, the potential has grown even bigger. She said that AI can dive deep into customer sentiment and use that knowledge to refine product offerings based on vast amounts of data.
Wayfair has been leveraging AI and ML for quite some time, particularly for decision-making, predictions, and optimisations.
According to Tan, Wayfair first applied these technologies in marketing. “Given how much we invest in customer acquisition, it was critical to ensure our spending was optimised. We started by building models that helped us identify which channels drove the most traffic, maximising returns on our advertising investments.”
Other than marketing, helping customers navigate a massive inventory of non-brand-specific items is a challenge.
Tan believes that shopping for home goods presents unique challenges compared to more straightforward purchases like batteries. Often, customers find it difficult to articulate exactly what they are looking for, making it harder for e-commerce platforms to deliver accurate search results. Wayfair also faces additional hurdles due to the often incomplete or limited data that suppliers provide about their products.
For example, when receiving a chair, vital information like dimensions, adjustability, or back support may be missing or insufficiently detailed. This is where AI steps in to enhance the search experience by identifying and extracting critical product attributes.
Wayfair employs advanced multimodal models, which integrate both text and image data, to tackle this problem. While initially developing many of these models internally, the company has now expanded its approach by leveraging generative AI and LLMs trained on extensive internet data. These models are particularly effective in interpreting product features from images and descriptions, enabling a more nuanced understanding of each product.
By combining visual and textual inputs, Wayfair can unlock new AI capabilities for product matching and recommendations, offering customers a more tailored and effective search experience.
Wayfair vs the World
Wayfair is not alone. It’s competitors are also betting big on generative AI, In an exclusive interaction with AIM, Lowe’s India AI and Analtycis head Amit Kapur said that the company has deployed over 40-50 AI models in production, and they were one of the early adopters of generative AI, where it partnered with OpenAI pre-ChatGPt era.
Wayfair is not alone in leveraging AI to transform e-commerce. Lowe’s, a Fortune 50 home improvement retailer, has deployed over 40-50 AI models across its platform to enhance customer experience and operations, alongside building an omnichannel order management system internally.
Not many know, Lowe’s were one of the first to partner with OpenAI, that is even before ChatGPT launch in November 2022, where the data and AI team successfully fine-tuned its GPT-3.5 model to improve product data accuracy, reducing friction in online searches and boosting error detection rates by up to 60%, leading to a smoother and more efficient shopping experience.
In 2022, IKEA introduced IKEA Kreativ, an AI-driven tool that lets customers design and visualise their living spaces in lifelike 3D from any device. Combining IKEA’s home expertise with advanced spatial computing and machine learning, it’s a game-changer for personalised interior design.
Even Target and Walmart have adapted AI to offer a better shopping experience to customers.
The ecommerce platforms have turned to AI navigating the dynamic AI landscape, real-world applications and more.
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