• Examined broadband shifting journey funnel, identified drop-off reasons, and suggested improvements, leading to 10% decrease in churn• Studied user behavior across channels and established a pattern to adopt for nudging customers from prepaid to postpaid, leading to approx. 1,000 additional postpaid conversions per month• Determined specific user cohorts to focus on for increasing leads generated via the app, resulting in nearly 7,000 new leads daily• Identified customer queries and recommended enhancements on selected app pages, resulting in 15% reduction in calls to call center

• Tracked and compared the performance of digital campaigns aimed at enhancing brand awareness across different channels—including social media, display ads, and paid search—using key performance indicators such as ROAS, CTR, and CPA• Built a dashboard to analyse performance impact of reducing assigned credit limits• Discovered the cause of payment delays among non-member customers who use creditcards, utilizing credit bureau data and decision tree algorithms• Examined customer transaction data to model credit riskAnalyze customer transaction data to add incremental value to existing credit card policy in Member base Create Tableau dashboards, for a Fintech client, to understand conversion rate of stages in customer journey and decline reasons, across various channels and score bands

• Conducted customer segmentation to generate a target list of 3,000 customers for an Australian online retailer; generated annual incremental revenue of $4 million across all business segments• Employed text mining techniques to analyse customer feedback• Utilised log-log regression and the demand-profit curve to determine price elasticityof materials for an American industrial distributor, assessing potential incremental sales

• Utilised market basket analysis with the Apriori algorithm, association rules, and interactive network graphs to optimize cross-selling and up-selling strategies for products

• Employed descriptive analytics to assess project performance, focusing on analysing ticket inflow distribution and turnaround times• Applied text analytics to gauge the sentiment of ticket requests and proposed solutions to mitigate the influx• Utilised predictive analytics for resource management, considering factors such as ticket priority, backlog, and meeting service level agreement targets