In conversations with retail executives back in 2010, Rama Ramakrishnan realized two things. First, while retail systems offering personalized recommendations to customers were getting a lot of attention, they often didn't provide much benefit to retailers. Second, many firms had customers who shopped only once or twice a year, so companies didn't really know much about them.
"But by carefully tracking the interactions a customer has with a retailer or an e-commerce site, we can create a detailed picture of what that person does and what they care about," says Ramakrishnan, a professor of practice at the MIT Sloan School of Management. "Once you have that, you can apply proven machine learning algorithms."
These realizations led Ramakrishnan to start CQuotient, a company whose software has become the foundation for Salesforce's popular AI e-commerce platform. “On Black Friday alone, CQuotient technology probably interacts with over a billion shoppers in a single day,” he says.
After a successful entrepreneurial career, Ramakrishnan returned to MIT Sloan in 2019, where he had earned his master's and PhD degrees in operations research in the 1990s. He teaches students not only how these amazing technologies work but also how to use them practically in the real world.
Ramakrishnan also enjoys participating in MIT executive education. “This is a great opportunity for me to share what I have learned and, just as importantly, to understand what's on the minds of these senior executives and guide them in the right direction,” he says.
For example, executives are often concerned about needing large amounts of data to train machine learning systems. He can now direct them to a variety of models that are pre-trained for specific tasks. “The ability to use these pre-trained AI models and quickly adapt them to your specific business problem is an incredible advancement,” says Ramakrishnan.