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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.
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
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.
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.
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.
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.
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.
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.
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.
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.
A total Hands Down!!! Teaching 5/5, Tech Support 5/5, Quality of education 5/5. This is by far 1 stop solution for your studies. I took Python course and was amazed by the teaching. Amazing teachers and course material. 24x7 support for even small queries now that's what I call a pure dedication. I love the whole edureka team. You just got a permanent customer Edureka. Thank you for all the small and big things you did for me. A special thanks to sales team for going out of the way to help me understand the course module and providing me with wonderful offers ;) Cheers:)
I have taken 3 courses (Hadoop development, Python and Spark) in last one year. It was an excellent learning experience, most of the instructors were very interactive and having extensive industry knowledge. The support team is highly professional, always ready to assist you and let you chose your classes based on your own availability. The Learning Management System(LMS) is great. and good thing is that you would get Lifetime access to all the course that you have registered. Apart from courses and instructors, Edureka support is excellent as they provide quick resolution to any issues(example VM setup. cluster connectivity issues and etc) . If you are looking for Big Data related courses then Edureka is the right place.
I'm currently enrolled in a lot of courses offered at Edureka, so I'm attending live classes and using their study materials, course projects, have access to support staff and teachers. I can confidently say Edureka staff is very hard working and committed to help students which is reliable. Course instructors are experienced candidates from industry who know what they are teaching. Course materials are pretty comprehensive and students need to work very hard to finish course projects, pass the project interviews and gain certification. I say, it is worth it.
I have done Spring Framework and Hadoop framework training from Edureka. I am very happy with the training and help they are providing.The sessions were very informative. The instructors are highly knowledgeable.They provide a set of videos from a previous session, so you can watch the course before you participate. This way you can get the most out of the course.Excellent Customer Service starting with signing up of the course. I really appreciate Edureka Support team. They are really doing a fantastic job. All my queries were answered properly and promptly.You get recording of the classes, presentations and labs in LMS. And good feature is you have lifetime access to LMS of course you have taken, so you can refer, revise any topic when you want.I can safely say Edureka is one of the best training company.
Edureka aptly named, gives the students a Eureka" Moment during the course. Learning is a world to explore and Edureka provides us with the navigation maps. I never for a minute felt that I am doing this course online away from the faculty and the staff."
Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best.