With a large number of models and tools that help with different aspects of AI & ML development, it is pivotal to track and apply not one, but several models and decide how to trade-off between them. Selection, evaluation and tuning of one or more algorithms to use for a particular business scenario is key to any successful AI project.

In this session, Arghya explained the 3 important aspects to consider while leveraging abundant data available in the B2C space for Analytics & Data Science: identifying primary KPIs, building suitable architecture and selecting the use cases for maximum business value. He also emphasized considering the right metrics across acquisition, activation, retention, revenue and referral for effective insights as needed. Arghya concluded the session by highlighting the important & complex role played by the Data engineers besides Analysts and Data Scientists in B2C specific AI at scale initiatives.