Advanced Customer Analytics

Start Date: Dec 15, 2020 End Date: Dec 17, 2020
Last Date for Application: December 1, 2020 Last Date for Early Bird: November 24, 2020
Programme Fee: 90000 INR

Plus, GST

Early Bird Fee: 83700 INR

Plus, GST

Over the last decade, marketing practice has gone through a radical transformation. At the heart of it is the availability of data. There is a common belief among marketing practitioners that analytics will pave the way for marketing decision making. Despite recognising the potential of analytics, there is a considerable skill gap that exists among practicing managers and recent developments in the field. While there are multiple programmes in analytics which have surfaced, most of them do not delve deeper how managers themselves can engage in data driven decision making.

The objective of our programme is to provide hands on experience in customer and marketing analytics. The programme takes a step by step approach to develop a holistic approach to elucidate the core concepts used in this emerging domain, and train managers to apply some of the advanced modelling techniques appropriate for the decision context. We start with a basic module on marketing analytics and move towards developing more advanced models of customer profitability. Thus, this course will provide managers the skill sets necessary for making a difference in the real world.

The course will train managers to build a strong proficiency in data analytics. The design of the programme is to enable managers to be able to use marketing/consumer data more proficiently, create customized models, and make more relevant data driven decisions for contexts specific to their organizations/businesses.

To train managers in marketing and consumer analytics for data driven decision making.

Day 1: Basics of Customer Analytics

Important Topics Covered in day 1: Regression Models, Basics of R programming. 

The objective of this module is to look at basics of marketing analytics. It lays the foundation by introducing a data driven understanding of well-known marketing frameworks and their linkages to strategic decision making process. Specifically, we would use regression models to examine the multi-attribute conceptualisation of products/services, and its linkages to marketing mix decisions, positioning and segmentation. In this module, we shall also introduce you to the basics of R programming environment. This will help you to develop better conceptual understanding by adopting a more hands-on approach during the coursework.

Day 2: Data Driven Decision Making: Digital Analytics 

Important Topics Covered in Day 2: Sentiment analysis, Text analytics, Google analytics. 

In continuity with the earlier module, this module focuses on more advanced models for customer decision making. Primary focus of this module is to understand digital analytics model. We start with sentiment analysis, text analysis to understand consumers through conversations they engage a digital world. Then, we move towards google analytics to show how data can be used for superior decision making.

Day 3: Advance methods for Customer Profitability

Important Topics Covered in Day 3: Customer Lifetime Value, Customer influence Value, Customer Referral Value.

While most organizations have built capabilities to access customer profitability, in most cases, the models used only focus on direct measures of profitability. In the third module, we incorporate both direct and indirect measures of customer profitability. We look at customer lifetime value, customer influence value and customer referral value. Customer influence value helps organizations to identify key opinion leaders of a product or a service in social media platforms whereas customer referral value helps a firm to understand profitability of a customer acquired through referrals. Finally, we look at how to communicate customer analytics in an organization.

The course is designed for managers and organizations willing to explore and exploit data analytics for effective decision making. Generally, the entry level, mid-level managers and entrepreneurs are suitable for this programme. 

As a part of the programme, you will do a small project, where you will apply the learnings from the course. This will help in solidifying the learnings. 

Faculty Chair

Naveen Amblee

Sourav Borah

Programme Faculty