Feb 2015 – Apr 2017 · 2 yrs 2 mos · Bengaluru Area, India

• As the sole analytical resource on Ola's marketing team, I had the opportunity to work across digital, onsite, social, and referral marketing channels. I analyzed the value each customer acquisition channel was generating in terms of returns versus the Cost of Acquisition. During this analysis, I discovered that the channel with the highest registration volume was yielding extremely low returns, leading to the identification of fraud amounting to INR 60 million monthly. The company quickly shut down this channel and redirected the budget to more effective channels, resulting in a 2% increase in the monthly customer activation rate over the following three months.
• Developed a model to assess and act on customer sentiment by analyzing opinions from various social platforms like Twitter and Facebook. Using R, I categorized customer comments as positive, negative, or neutral and further segmented negative feedback into actionable areas such as operations, products, and marketing. These insights were then shared with the relevant teams, leading to a 30% improvement in customer sentiment, as reflected in the Customer Satisfaction Score on social media.
• Played a key role in identifying relevant customer segments for different cab categories at Ola. The company offers various cab options: Micro (hatchback at the lowest price), Mini (hatchback with WiFi at a moderate price), and Prime (Sedan and SUV with WiFi and in-cab entertainment at the highest price). I defined use cases and target customer segments for each category, utilizing logistic regression to establish relationships between booking decisions and factors such as fare, convenience (WiFi or in-cab entertainment), and Expected Time of Arrival. I also monitored how customer behavior varied by location, day, and time of day, enabling more precise targeting of customers. As a result, Ola's conversion rate increased by 1.7%, and revenue grew by 3.2%.

Feb 2014 – Jan 2015 · 11 mos · banagalore

• Collaborated with one of the world's largest pharmaceutical companies to help gain market share for a newly launched product. The company was entering the U.S. market with a new allergy drug, competing against an established product with a 20-year market presence and 95% market share, whose patent had recently expired. I analyzed the competitive landscape and identified strategies to capture market share, such as targeting new users like children, who could benefit from the drug's additional features. The company quickly implemented three of the five recommendations I provided.
• Worked with a UK-based conventional retailer to enhance their collection rate, which measures the proportion of items accepted by customers out of the total shipped. A low collection rate was negatively affecting the company's conversion rate, as products in transit that were later refused by customers were leading to inventory shortages and missed sales opportunities. Additionally, the company was incurring shipping costs for returned items. I applied K-means clustering to analyze customer behavior across different segments and products, providing tailored recommendations for each segment. These strategies led to a significant improvement in the collection rate within six months.