TECHNOLOGY
Analytics for Retail Banks Edureka
Unit Nos: 501-507, 5th Floor, Delta Block, Sigma Soft Tech Park, Varthur Road, Bangalore- 560066 - 66
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Analytics For Retail Banks

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Course at a Glance
  • Study Content (Online)
  • English Language
  • Online Doubt Support
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About Course

The Edureka Analytics for Retail Banks course is designed to provide the requisite knowledge and skills to become a data-driven marketer. It starts with fundamental concepts around the analytics lifecycle, data requirements and customer lifecycle to advanced topics around digital experiences, event-based marketing, omni-channel marketing and campaign analytics, among others.

Course Objectives

After completing the Edureka course, you will be able to: 

1. Understand the applications of data-driven marketing across the customer life cycle at retail banks. 

2. Understand the data infrastructure and the analytics set up required to carry out data-driven marketing. 

3. Understand the nuances of how incoming, outgoing and interactive channels impact data-driven programs. 

About Institute

Edureka is a live and interactive e-learning platform that is revolutionizing professional online education. Edureka offers instructor-led courses supported by online resources, along with 24/7 on-demand support. It gives professionals the flexibility to learn at their own time and location, even from their mobile devices. Edureka also provides real-life project scenarios designed and evaluated by industry experts. With its innovative course delivery backed by industry-renowned practitioners, Edureka has helped more than 250,000 professionals upgrade their skills across 80+ specially designed courses. From its inception in 2011, more than 50,000 hours of classes have been delivered on the Edureka platform. Professionals and practitioners from more than 150 countries constantly engage on the Edureka platform and each Edureka course is tailored to address industry challenges, domain changes and latest trends. Edureka is committed to arming professional learners with the right resources to excel in their careers. With a customer-first approach, Edureka focuses on the long term career aspirations of learners and safeguards them against technology changes. The Edureka family prioritizes learners’ career growth above all else, and a flat hierarchy ensures healthy collaboration with transparency and positivity. Edureka offers courses in the areas of Big Data, Programming, Professional Certifications and Marketing.

Course Structure

1. Analytics scope at a retail bank

 

Learning Objectives - In this module you will understand the scope of analytics applications at a retail bank and the underlying processes involved. You will also learn about the various activities around analytics. Develop a sound foundation of analytics frameworks. Learn about best practices in analytics and also understand latest trends around analytics.

 

Topics - Analytics objectives, Analytics data stack, Analytics lifecycle, Analytics process cycles, Analytics algorithms stack, Data visualization, Context awareness, Analytics best practices, CRISP-DM methodology. 

 

2. Marketing challenges across the retail banking customer lifecycle

 

Learning Objectives - In this module you will understand different stages of the customer lifecycle, Marketing challenges across different stages of the customer lifecycle, Best practices in managing these challenges, How to use analytics to address these challenges and Undertake a case study of a Taiwanese bank. 

 

Topics - Retail banking objectives, Customer lifecycle, Analytics applications across the customer lifecycle, Levers, Analytics objectives and trade-offs, Segment marketing, Partner agencies, ROI models

 

3. Data related Infrastructure at a retail bank

 

Learning Objectives - In this module you will understand the various types of data needed at a retail bank, Infrastructure required to manage data and learn about challenges and best practices in managing data.

 

Topics - 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.

 

4. Channel implications on data driven marketing at retail banks

 

Learning Objectives - In this module you will understand the various types of channels and their implications on data-driven marketing. Learn about customer touch-points and how they can be leveraged. Appreciate best practices around analytics and channel management.

 

Topics - Channel purposes, Types of channels, Channel throughput, Channel infrastructure, Campaign execution challenges, Omni-channel perspective, Use of social media channels.

 

5. Data-driven customer acquisition at retail banks

 

Learning Objectives - In this module you will understand how to run data-driven acquisition programs, Best practices around analytics in the acquisition space, understand the differences between prospecting and onboarding and also learn about best practices around digital onboarding. Carry out a case study of an Indonesian bank.

 

Topics - Prospecting, Onboarding, Analytics capabilities for prospect analytics, Response models, Activation strategies, Digital activation best and worst practices.

 

6. Data driven usage management at retail banks

 

Learning Objectives - In this module you will understand how to run data driven usage management programs, Explore best practices around analytics in the usage management space. Learn about challenges while implementing offers. Perform a case study of a Thai bank and Chinese bank. 

 

Topics - Analytics capabilities required, Sample usage increase programs, Offer glut, Offer fulfillment and tracking.

 

7. Data driven customer experience management at retail banks

 

Learning Objectives - In this module you will understand the customer journey and define customer experience. Learn about the benefits of having a good customer experience, How to run data-driven customer experience management programs, best practices around analytics in the customer experience management space and also understand best practices of customer experience in digital banking. 

 

Topics - 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.

 

8. Data driven upselling and Cross selling at retail banks

 

Learning Objectives - In this module you will understand how to run data driven upsell and cross sell programs. Learn about best practices of analytics in the upsell and cross sell space, tactics to increase customer penetration, approaches to Bancassurance perform a case study of an Indian bank and Chinese bank. 

 

Topics - 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.

 

9. Data driven retention and loyalty management at retail banks

 

Learning Objectives - Understand how to run data-driven retention and loyalty management programs, Approaches to building retention strategies, trends in social media marketing. Learn about best practices of analytics in the retention and loyalty management space. Undertake a case study of an Indian bank

 

Topics - 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.

 

 

10. Practical Implementation challenges for the data-driven market

 

Learning Objectives - Understand practical challenges in implementing data driven programs. Learn about basic principles driving IT infrastructure of digital banking and also you will learn how to manage these challenges. 

 

Topics - 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 Whom

The course is designed for all those who want to understand the application of analytics especially in the retail banking context.The following audiences could greatly benefit from this course:

1. Analytics Managers who are subject matter experts, leading a team of analysts. 

2. Senior professionals at Retail Banks who want to enhance their career prospects by moving into analytics.

3. Business heads and CXOs to help understand the applications of analytics.

Academic Profile
  • Online Query Support Yes
  • Online Tests Yes
  • Telephonic Query Support No
  • Video Classes Yes
  • Study Content Yes
  • Class Hand Outs Yes
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