JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY HYDERABAD

Course Objectives :

• Students must demonstrate knowledge of collecting and managing the relevant data of web and Social media analytics, identify the social business analytics and analyzing mobile data analytics with respect to publishers, operators and e-mail marketing.

Course Outcomes:

• 1. Understand the basic concepts of Web and Social Analytics.
• 2. Explain the process of collecting relevant data.
• 3. Identify the common business objectives.
• 4. Understand the concepts of mobile analytics.
• 5. Explain the concepts of mobile customer experience.
• 6. Analyze the mobile analytics for publisher, operator and email marketing.

UNIT - I

Social Network Data: Introduction: What Are Network Data? , Structural and Composition Variables, Modes, Affiliation Variables, Boundary Specification and Sampling, What Is Your Population?, Sampling, Types of Networks, One-Mode Networks, Two-Mode Networks, Ego-centered and Special Dyadic Networks, Network Data, Measurement and Collection, Measurement, Collection, Longitudinal Data Collection, Measurement Validity, Reliability, Accuracy, Error

UNIT - II

Rethinking Web Analytics: Meet Web Analytics 2.0, The What: Clickstream, The How Much: Multiple Outcomes Analysis, The Why: Experimentation and Testing. The Awesome World of Click Stream Analysis: Metrics, Standard Metrics Revisited: Eight Critical Web Metrics, Visits and Visitors, Time on Page and Time on Site, Bounce Rate, Exit Rate, Conversion Rate, Engagement, Web Metrics Demystified, Four Attributes of Great Metrics, Example of a Great Web Metric, Strategically-aligned Tactics for Impactful Web Metrics, Diagnosing the Root Cause of a Metric’s Performance—Conversion, Leveraging Custom Reporting, Starting with Macro Insights

UNIT - III

The Key to Glory: Measuring Success: Focus on the “Critical Few”, Five Examples of Actionable Outcome KPIs, Task Completion Rate, Share of Search, Visitor Loyalty and Recency, RSS/Feed Subscribers, % of Valuable Exits, Moving Beyond Conversion Rates, Cart and Checkout Abandonment, Days and Visits to Purchase, Average Order Value, Primary Purpose (Identify the Convertible), Measuring Macro and Micro Conversions, Examples of Macro and Micro Conversions, Quantifying Economic Value, Measuring Success for a Non-ecommerce Website, Visitor Loyalty, Visitor Recency, Length of Visit, Depth of Visit, Measuring B2B Websites.

UNIT - IV

Emerging Analytics: Social, Mobile, and Video: Measuring the New Social Web: The Data Challenge, The Content Democracy Evolution, The Twitter Revolution, Analyzing Offline Customer Experiences (Applications), Analyzing Mobile Customer Experiences, Mobile Data Collection: Options, Mobile Reporting and Analysis, Measuring the Success of Blogs, Raw Author Contribution, Holistic Audience Growth, Citations and Ripple Index, Cost of Blogging, Benefit (ROI) from Blogging, Quantifying the Impact of Twitter, Growth in Number of Followers, Message Amplification, Click-

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R19 M.TECH WEB TECH./ INF TECH.

Through Rates and Conversions, Conversation Rate, Emerging Twitter Metrics, Analyzing Performance of Videos, Data Collection for Videos, Key Video Metrics and Analysis, Advanced Video Analysis.

UNIT - V

Mobile Analytics: How Mobile Is Different than Other Digital Channels Understanding the Current Mobile Market Landscape, Growth in Smartphone Adoption, The Battle Between iOS and Android, The Explosion of Global Mobile Web Traffic, The Introduction of Mobile Advertising, Identifying What Is Next for Mobile Marketing, Increased Use of Apple Passbook, Improvements in Facebook’s Mobile Functionality, Expansion of Location-Based Technologies, Increased Strength of Mobile Measurement, The Current State of Measuring Mobile, Marketing Activities, Mobile Device Reporting, Audience/Visitor Metrics, Mobile App Performance, The Future State of Measuring Mobile Marketing, Activities

Text Books:

• 1. Stanley Wasserman, Katherine Faust, “Social Network Analysis: Methods And Applications” Cambridge University Press. (Chapter -1)
• 2. Avinash Kaushik, Web Analytics 2.0, The Art of Online Accountability & Science of Customer Centricity, Wiley Publishing, Inc., (Chapter-2, Chapter-3 & chapter-4)
• 3. Chuck Hemann, Ken Burbary, Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World, Que Publishing, (Chapter-5)

References:

• 1. Social, Web and Mobile Analytics (IBM ICE Publication)
• 2. Robert A. Hanneman and Mark Riddle, “Introduction to social network methods”, University of California, 2005.
• 3. Jure Leskovec, Stanford Univ. Anand Rajaraman, Milliway Labs, Jeffrey D. Ullman, “Mining of Massive Datasets”, Cambridge University Press, 2 edition, 2014.
• 4. Wasserman, S., & Faust, K, “Social Network Analysis: Methods and Applications”, Cambridge University Press; 1 edition, 1994. Page 28 of 52 R19 M.TECH WEB TECH./ INF TECH. M. Tech. (IT/ WT) I Year – II Semester Common to IT and WT