This position will be responsible to mine and analyze customer and portfolio data to identify insights to increase products per customer (PPC) & revenue per customer.
This position will also be responsible to analyze and optimize ROI on marketing campaigns (including direct sales, email, digital, branch, agents,
Other responsibilities include analyzing industry related published data and statistics, and gathering statistical data on competitors to assess future trends.
Analyze data to identify emerging customer trends to drive strategic interventions at right time.
Liaison with market research teams to validate data insights and emerging trends
Develop deep knowledge of customer product needs, traffic drivers and customer behaviors, to drive customer acquisition, retention, engagement and win back initiatives.
Develop key customer insights across various customer segments & customer profiles.
Participate/lead ideation sessions to identify revenue growth opportunities
Set-up of continuous Design-of-Experiments to determine & study sensitivity due to changes in product, price or channel offerings etc.
Maximize customer share of wallet, map significant customer lifecycle events, to ensure right product mapping basis cm life events & needs.
Drive customer lifetime value, to drive right product at right life stage.
Interface with cross-functional teams to ensure timely deployment of key programs and delivery of annual revenue plans.
Financial Services the areas of consumer marketing and research
Exposure to Insurance will be a plus
Data analysis, customer segmentation and technology orientation will be critical to succeed in this role.
The candidate should possess extensive product knowledge, strong execution and multi-tasking skills with a high level of achievement orientation
Demonstrated ability to understand and analyze strategic, business and operational issues facing a large business enterprise, to work with key holders to arrive at practical solutions, to meet business objectives.
The candidate would need in-depth knowledge of Statistical Techniques and Tools like SAS, and also hands-on experience in managing and processing large customer data sets using database query tools (SQL).
Experience with diverse statistical/analytics techniques such as multivariate modeling, logistic regression, scorecards, CHAID, Clustering,HLM, forecasting (ARIMA), Factor analysis etc.
Should have exposure to advanced areas such as Text and Sentiment Analytics, Applications of Machine Learning Algorithms & Techniques (Gradient Boosting, SVM, SOM, Random Forest etc.), Big Data Environment, R, and Python.