From Learning to Application, Myself – Akanksha Rastogi, with a master’s degree in economics, I have spent most of my professional career doing data analysis and insights for giant retailers and e-commerce companies. My job has always been data-driven and technical. With the recent advances in the space of Artificial Intelligence and machine learning, I had a nagging feeling to upskill, and I am very happy with my choice of Great Learning’s AIML course.
Ever since joining the course, I have been able to apply my newly acquired skills to a few problems such as:
- Predicting vendors that are likely to churn from a food aggregator’s platform. One of the most important goals of a food aggregator is to offer varied and reasonable choices to our customers by maintaining a good relationship with our vendors. We built a supervised learning model to predict the vendors at the risk of churning based on their performance on the platform, responsiveness, recent experiences, etc. We used decision tree-based supervised learning on historical data to make a prediction, allowing account managers to proactively contact the vendors and address grievances as well as provide larger platform support to help improve performance. We were able to reduce vendor churn by 5%, and these target communications also helped us confirm the key drivers of churn as well. The latter was used to bring in place better SOPs to reduce systemic drivers of vendor churn.
- Using OCR to extract key information from competitor receipts and use the generated data to then understand competitor pricing at a much more granular level than ever before. We have a lot of employees who are genuine competitor customers, and we gathered their invoices for this project. Once we had the information, we trained an OCR model to extract the information therein. We were able to structure the data and run regression models to understand the various drivers of pricing – this was used to drive strategies on how to remain competitive in the market. We were able to improve our pricing strategies in several provinces and saw better customer retention along with declined customer churn.
Projects like these have allowed my organization to scale solutions to be much more preemptive and respond at scale with precision rather than having blanket approaches that were costly and ineffective.
These projects give me personal pride and keep me motivated to bring value to my organization. Also, the opportunity to apply the concepts helped me reinforce my learning and brought me lots of hands-on nuggets of wisdom that I will carry forward with me.
I thank Great Learning for giving me a comprehensive introduction to the concepts along with the opportunity to apply them to actual problems with the projects. It was great to have mentoring sessions in which all doubts were cleared and constant encouragement and support were provided.
