ADD ON COURSE (2021-22)
Customer Analytics
Course Facilitator: Dr. Jose Varghese
(josevarghese@fisat.ac.in)
Introduction:
Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management.
Course Objectives:
- Create a single, accurate view of a customer to make decisions about how best to
acquire and retain customers.
- Gather deeper understandings of customers’ buying habits and lifestyle preferences
Course Outcomes:
At the end of the course, the student will be able to:-
CO 1: Acquire knowledge related to the various terminologies and techniques associated with customer analytics
CO 2: understand the segmentation process
CO 3: Analyze how the markets prices are determined
CO – PO Mapping:
| CO/PO |
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
| CO1 |
3 |
2 |
1 |
2 |
2 |
| CO2 |
3 |
2 |
1 |
3 |
2 |
| CO3 |
3 |
2 |
1 |
3 |
2 |
Course Delivery Methods:
|
Lecture
Mode |
Problems |
Video
Sessions |
Assignment |
| CO 1 |
√ |
√ |
√ |
√ |
| CO 2 |
√ |
√ |
√ |
√ |
| CO 3 |
√ |
√ |
√ |
√ |
Eligibility:
Student should score 50% (30 marks) & 80% attendance to be eligible for the certification.
Syllabus: (Total Hours Required – 30)
Module 1- Marketing Management Process and Customer Analytics
The Marketing Management Process and its link to Customer Analytics and Customer Insights – Correlation – Simple linear regression – Trend – seasonality- Exponential smoothing
Module 2 – Pricing
Non-linear pricing strategies for profit maximization – price skimming and sales – optimal pricing – price bundling – demand curve and the willingness to pay
Module – 3 – Customer Insights
Conjoint analysis – product attributes and levels – full profile conjoint analysis – choice based conjoint analysis – random utility theory
Module 4 – Customer value
Lifetime customer value, – relation between spending, customer acquisition and customer retention – Market basket analysis – RFM analysis
Module 5 – Market Segmentation
Cluster analysis – collaborative filtering – classification trees for segmentation – Application of Customer Analytics in Advertising, Retailing and Internet & Social Marketing
References:
- Winston, Wayne L. (2014), Marketing Analytics: Data-Driven Techniques with Microsoft Excel, 1st ed. Wiley.
- Winston, Wayne L. (2014), Marketing Analytics: Data-Driven Techniques with Microsoft Excel, 1st ed. Wiley.
- Malhotra, Naresh (2015), Marketing Research – An Applied Orientation, 7th ed., Pearson EducationVandana Ahuja. Digital Marketing. Oxford University Press India, 2015
- Damian Ryan. Understanding Digital Marketing: Marketing Strategies for Engaging the Digital Generation (3rd Edition). Kogan Page Publishers, 2014.