AI and ML have become the order of the day. Shantanu Preetam, CTO, PayU, talks to us about its nuances in today’s context
What is the role of AI and ML in powering the success of sales?
AI, ML and other underlying technologies provide the foundational platform which enables E-commerce companies to run high volume festive sales successfully. For example, our dynamic routing algorithm chooses the most optimized route to perform a given transaction, keeps it continually improving by using historical as well as real-time data and in conjunction with dynamic scaling capability, it’s able to deal with the spike in traffic. That’s why PayU has the most stable and scalable platform in the country, preferred by brands during high volume festive season sales. It is quite important to harness and apply ML learnings qualitatively. E-commerce websites generate a vast amount of streaming data that can be stored/mined using descriptive, diagnostic, and predictive tools. Prescriptive analytics of previous years’ data can provide valuable lessons in preparing for upcoming and ongoing festive season sales.
What are the good Sales strategies in today’s difficult times when customers are decreasing?
The pandemic has accelerated the adoption of digital payments and they constitute an estimated 87% of retail payments in the country, given their contactless nature and ease of convenience. Therefore, more and more merchants are now offering digital and omni channel solutions to their customers across myriad touchpoints. In fact, at PayU we have been observing a 3x increase in traffic during ongoing festive season sales in 2020 as compared to 2019. Our technology platform & infrastructure is geared up towards meeting this increased demand for omni-channel payments, credit at point of sale and helping merchants create a digital presence. Providing merchants payment and credit solutions which suit the needs of their customers, such as E-PoS, links, digital on delivery and affordability credit solutions can help them significantly improve the customer experience and stickiness in turn guaranteeing better customer life cycles and a large number of returning customers.
AI-powered leads are often not accurate leading to wastage of time and resources. How can it be rectified in terms of technology?
False positives, false negatives and ensuring better F-score (measure of Precision & Recall) are continuous challenges of any AI/ML based system. Data and AI in themselves are not of significant use until their application is done with the right intent and purpose. The success of any AI/ML platforms highly depends upon the perfect blend of business, product, engineering, and data science teams to come together and work in tandem with each other. It’s not just the Data Science Algorithms and ML models that make the product successful but equally important are other key tenets as Data Engineering Pipeline, ML Engineering and MLOps, Application Development, User Experience and Product Management. Continuous CI/CD pipeline based Model training and model performance (manage biasing) and scalability of AI/ML-based platforms become quite paramount in ML-based systems output and enhanced accuracy.
How do you foresee the business growth of AI-enabled platforms in 2021?
Over the last few years, AI has found applications in all major sectors. Especially in light of COVID 19, there is a huge shift in consumption patterns and massive quantities of data are generated. AI, Deep Learning, ML, and data lakes/data warehouse methodologies are helping large enterprises improve efficiency and boost profitability. For smaller organizations, such advanced technologies can accelerate their growth immensely and enable businesses to mine valuable insights from data. Artificial intelligence and machine learning will also play a key role in cybersecurity to help identify threats, enable fraud preventive measures, and risk mitigation.