Course on Analytics for Retail Banks by Edureka [Online Classes]: Register Now
Course on Analytics for Retail Banks by Edureka helps you to become a data-driven marketing expert by mastering concepts around analytics lifecycle, data infrastructure, customer lifecycle and digital trends while going through global retail banking case studies.
- Analytics scope at a retail bank: Analytics objectives, Analytics data stack, Analytics lifecycle, Analytics process cycles, Analytics algorithms stack, Data visualization, Context awareness, Analytics best practices, CRISP-DM methodology.
- Marketing challenges across the retail banking customer lifecycle: Retail banking objectives, Customer lifecycle, Analytics applications across the customer lifecycle, Levers, Analytics objectives and trade-offs, Segment marketing, Partner agencies, ROI models
- Data related Infrastructure at a retail bank: Challenges of big data, Different types of data, Data life cycle Logical data models, Data cleansing, Unstructured data processing, Single view of the customer, Single row per customer, Platform components required to process data, Requisite processes
- Channel implications on data-driven marketing at retail banks: Channel purposes, Types of channels, Channel throughput, Channel infrastructure, Campaign execution challenges, Omni-channel perspective, Use of social media channels.
- Data-driven customer acquisition at retail banks: Prospecting, Onboarding, Analytics capabilities for prospect analytics, Response models, Activation strategies, Digital activation best and worst practices.
- Data-driven usage management at retail banks: Analytics capabilities required, Sample usage increase programs, Offer glut, Offer fulfillment and tracking.
- Data-driven customer experience management at retail banks: Customer journey and analytics, Customer experience processes, Customer trust principles, Analytics capabilities required for customer experience, Analytics capabilities required for customer satisfaction, Analytics for the end customer, Personal financial management, Technology shifts, Design thinking, Testing options, Digital customer experience sensors and actuators.
- Data-driven upselling and Cross-selling at retail banks: Upselling and cross selling processes, Tactics to increase customer penetration, “Incoming call is your best bet”, Next best offer analytics, Case study: Card upgrade program, Case study: Cross selling credit cards to savings accounts, Case study: Cross Selling mutual funds to savings account customers, Cross sell between corporate and individual accounts, Bancassurance approaches.
- Data-driven retention and loyalty management at retail banks: Retention and loyalty processes, Factors affecting, Customer loyalty, Analytics capability for loyalty analytics, Attrition types and retention strategies, Case Study: Attrition model, Advocacy analytics, Social Media Marketing.
- Practical Implementation challenges for the data-driven market: McKinsey core beliefs on big data, Data privacy, IT principles for digital banking, Architecture blocks for digital banking, “Know your business”, Data preparation groundwork, “Analytics is more art than science”, Common improvement areas at banks.
For full details and online registration visit the link below.
Note: NoticeBard is associated with Edureka via an affiliate programme.
About the Author