True Fit's CTO, Raj Chandrasekaran, talks about how rich and proprietary datasets drive the most effective AI outcomes for personalization.
May 21, 2024
A recent Forbes article featured an interview with True Fit’s CTO, Raj Chandrasekaran. The article dives into the importance of rich data in enabling great AI outcomes for businesses and their customers.
Prominent AI researcher, Fei-Fei Li, highlighted the significance of diverse and high-quality datasets, explaining that "AI is only as good as the data it learns from. Without a rich diversity of data, we cannot expect AI to make well-informed decisions."
Jeff Bezos, CEO of Amazon, has said "The most important single thing is to focus obsessively on the customer. Our goal is to be earth’s most customer-centric company. If you start with the customer and work backwards, you’ll be in a good place." Amazon's success in recommendation systems, logistics optimization, and personalized shopping experiences has famously been attributed in large part to its extensive and proprietary customer data.
Artificial Intelligence (AI) continues to emerge as a critical driver for personalization. AI might be a technological tool, but that doesn’t mean it’s entirely out of touch with what humans want. That’s because AI relies on human input to deliver outputs for specific purposes. So, when AI is trained based on a quality data set, it can provide some truly intelligent outputs that deliver personalized and customized recommendations for individuals. It’s up to companies to recognize how to use AI to create personalized experiences that keep their customers coming back for more.
Understanding AI-Driven Personalization
AI-driven personalization uses algorithms to analyze extensive data sets to allow for customized interactions on an individual level. These interactions can include anything from tailored text marketing messages to personalized service recommendations when a user lands on a company home page. “Many people don’t understand how AI works or the many ways it can be used to benefit humanity,” says Raj Chandrasekaran, CTO of True Fit, an AI platform that helps online fashion retailers decode size and fit for their shoppers. “When everyone has access to essentially the same AI tools, creating new value comes down to having unique and proprietary data sets that enable AI to solve increasingly complex problems, especially as it pertains to personally relevant questions like which size is right for me in an industry with no standardized sizing systems. For us, we find that the strength of AI is its speed and capacity to digest and learn from large volumes of data, making informed predictions and decisions that help us answer critical questions for people. With True Fit, we use a combination of purchase data, customer clothing preference data, size and fit data, and other interaction data to help shoppers buy clothes online that look and feel great when they receive them.”
AI Can Only Power Personal Relevance if it has the Right Data
Rohit Seghal wrote another Forbes piece months ago entitled, “AI Needs Data More than Data Needs AI”, which highlights data as the foundation and AI the enabler. So, how exactly does a robot, the enabler of data, turn seemingly random information into unique experiences? It starts with giving it access to the rich data, the right data. AI can almost instantly analyze massive data sets and distill insights from its synthesis of complex patterns, differentiating consumer behavior, preferences, and past interactions. “In retail, trust is everything. Our unreasonable effectiveness of data is why True Fit is able to provide trustworthy size and fit recommendations at such breadth,” says Chandrasekaran.
AI’s exceptional ability for in-depth, almost immediate analysis can help businesses offer tailor-made recommendations, services, and content to individuals based on their interests and shopping patterns. “Having a high level of personalization for your online store ensures that each customer encounter is uniquely aligned with individual interests and needs, which enhances the user's engagement and satisfaction,” says Chandrasekaran. However, it’s important to note that collecting quality data takes time. “While AI can act quickly, getting the right amount of data can take years, enabling and connecting data sources and partners. In a world where AI is accessible to all, the main differentiator is unique and proprietary data. For example, True Fit’s Fashion Genome is a very special platform cultivated over many years, connecting hundreds of billions of dollars worth of anonymized purchase transactions, with over 400 million shopper profiles, and rich product data from tens of thousands of apparel and footwear brands – it didn’t grow overnight.” All of this data allows True Fit to have a rich understanding about the relationships and patterns of people to products, and products to brands, enabling AI to help people confidently purchase products in the correct size. In a very practical way, True Fit is using AI and its unique and proprietary data set, the Fashion Genome, to help solve the $2.2T global fashion industry’s number one pain point for purchasing clothes, unsure fit and sizing.
As AI technology continues to evolve, the scope of personalization possibilities for digital stores and experiences will expand. The use of AI in personalization is just scratching the surface. As businesses continue innovating, the bond between brands and consumers will strengthen through more personalized and meaningful interactions. By leveraging “data as the foundation and AI as the enabler”, businesses will better cater to their customers' individual preferences, and will no doubt enhance customer satisfaction, improve engagement, and increase loyalty, ultimately driving growth and success.
