Subject Details
Dept     : SPINE MBA
Sem      : 3
Regul    : -
Faculty : Parameshwaran M
phone  : 7708355472
E-mail  : paramesh.m.ihub@snsgroups.com
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Syllabus

UNIT
1
Introduction to Marketing Analytics and Data Sources

Definition and importance of marketing analytics - Role of analytics in marketing decision-making - Evolution of marketing analytics in the digital age - Overview of data-driven marketing - Types of marketing data - Sources of marketing data - Data collection techniques - Issues in data quality and data integration - Key marketing metrics - Ethical and legal considerations in marketing data usage - Basics of marketing dashboards and reporting - Introduction to tools like Google Analytics and Tableau.

UNIT
2
Consumer Analytics and Segmentation

Customer lifetime value (CLV) and its strategic implications - RFM (Recency, Frequency, Monetary) analysis - Customer acquisition cost (CAC) and retention rate - Market segmentation using cluster analysis - Persona development and profiling - Predictive modeling for customer churn - Measuring customer satisfaction and Net Promoter Score (NPS) - Analyzing customer journey and touchpoints - Cohort analysis for behavior tracking - Use of decision trees and logistic regression in customer profiling - Customer scoring and targeting models - Applications in loyalty program optimization

UNIT
3
Product, Pricing, and Promotion Analytics

Conjoint analysis for product feature optimization - Brand equity measurement and tracking - Product cannibalization and portfolio optimization - Price elasticity of demand and dynamic pricing - A/B testing and multivariate testing for pricing - Promotions analysis: lift, redemption rate, incremental, ROI - Attribution models in marketing campaigns - Marketing mix modeling (MMM) for channel effectiveness - Econometric models in price and sales prediction - Forecasting sales using time series models - Impact of discounts and bundling strategies - Experimentation design for product launches.

UNIT
4
Digital and Social Media Analytics

Measuring digital campaign performance - Search engine optimization (SEO) and analytics - Paid media analytics - Content performance metrics - Sentiment analysis and opinion mining from social platforms - Influencer marketing and engagement metrics - Social network analysis and virality measurement - Hashtag tracking and brand mentions - Real-time analytics for programmatic advertising - Funnel analysis: awareness to conversion - UTM parameters and campaign tracking - Tools: Hootsuite, Google Data Studio, Sprout Social.

UNIT
5
Predictive Analytics and Marketing Strategy Integration

Predictive modeling for lead scoring and conversion - Cross-selling and up-selling analytics - Basket analysis and market basket modeling - Lifetime value prediction using regression and machine learning - Churn prediction using classification models - Next-best offer recommendations using collaborative filtering - Strategic campaign planning with analytics - Integrating analytics into CRM and automation systems - Marketing strategy alignment with analytics insights - Visualization of strategic KPIs - Role of Al and ML. in advanced marketing analytics - Capstone case study: using analytics to drive marketing ROI.

Reference Book:

B1 - Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis. Pearson. (good for regression, cluster analysis, factor analysis). B2 - Fader, P. S. (2020). Customer Centricity: Focus on the Right Customers for Strategic Advantage. Wharton Digital Press. (useful for CLV, segmentation, loyalty). B3 - Lilien, G. L., Kotler, P., & Moorthy, K. S. (2017). Marketing Models. Prentice Hall. (covers mix modeling, pricing, promotion analytics).

Text Book:

T1 - Venkatesan, R., Farris, P., & Wilcox, T. R. (2019), Cutting-edge marketing analytics. Pearson Education. T2 - Winston, L. W. (2018). Marketing analytics. Wiley India

 

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