Digital Analytics

Objectives

Today, many businesses are digital or trying to be, turning all the services that are linked to them a source of data of an extreme dimension. With multiple touchpoints in a customer journey, it’s vital for organizations to invest in analytics to understand and even predict the behaviour of users in digital platforms. This information is a source of knowledge that can be a critical factor for the organization’s success.

In a quick changing and dynamic world, having the knowledge and the tools to transform company businesses is critical for success. This theoretical and practical course will guide students through the essential knowledge and ability to use the tools to apply Digital Analytics in organizations and projects of different types.

The main objective of this course is the (A) application of quantitative methodologies to the data generated and its (B) integration with other sources of data by websites, web applications, mobile applications and other digital platforms. Furthermore, to (C) explore how these analyses and knowledge can be incorporated in the decision processes to growth revenue and ROI.

General characterization

Code

400082

Credits

7.5

Responsible teacher

Bruno Filipe Santos Amaral

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

Degree in Business Management, Information Management, Engineering, Economics or Marketing.

Bibliography

Altamente recomendado
- Avinash Kaushik (2010) "Web Analytics 2.0: The Art of Online Accountability and Science of Customer
Centricity". Wiley publishing, inc.
- Brent Dykes (2011) "Web Analytics Action Hero: Using Analysis to Gain Insight and Optimize Your Business".
Peachpit
- Google Analytics Breakthrough: From Zero to Business Impact by Feras Alhlou (Goodreads Author), Shiraz
Asif, Eric Fettman
- George S. Nelson (2018) "The Analytics Lifecycle Toolkit". John Wiley & Sons, Wiley and SAS Business
collection.

Outros títulos sugeridos
- Mobile App Analytics by Wolfgang Beer (2016), Publisher: O'Reilly Media, Inc.
- Hunt, Ben (2011) "Convert!: Designing Web Sites to Increase Traffic and Conversion?. Wiley publishing, inc.
- Davenport, Thomas H.; Harris, Jeanne G.; Morison, Robert (2010) "Analytics at Work: Smarter Decisions,
Better Results". Harvard Business School Publishing Corporation
- Brian Clifton (2012) "Advanced Web Metrics with Google Analytics, 3nd Edition". John Wiley & Sons
- Alistair Croll and Benjamin Yoskovitz (2013) "Lean Analytics: Use Data to Build a Better Startup Faster".
O'Reilly
- Eric Siegel (2016) "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die". Wiley
publishing, inc.
- Anil Maheshwari (2021) "Data Analytics Made Accessible: 2021 edition" (Kindle Edition). Amazon Digital
Services LLC

Teaching method

Theoretical classes to introduce the main concepts of Digital Analytics.
Presentation and demonstration to introduce key concepts and practical situations.
Practical classes to explore and use Digital Analytics and do exercises.
Development of group project to experience a real world assignment.
Final evaluation to validate the knowledge.

Evaluation method

The evaluation will be based on the class participation and attendance, a group project and also a formal final examination.

The group project must be done in groups of 4 students. Each project should have a maximum of 25 pages and 7000 words excluded appendix.

The formal final examination will include questions covering all subjects addressed during the term. It will include theoretical questions that represent about 60% and practical ones that represents 40% of the points. To pass a minimum of 9.5 out of 20 points must be obtained in the final exam and in the group project.

Final grade calculation (both for 1st and 2nd Period):
a)   50% group project (minimum 9.5)
b)   50% exam (minimum 9.5)
c)   +5% plus for class engagement

Class engagement is measured by a mix of class attendance, measuring the attendance both presential and remote, and an intermediate exercise that will be shared and automatic evaluated on Moodle to be released in the trimester break. Measurement of class attendance will be done with an external tool that students must submit in every lesson. Zoom attendance and NOVA IMS App are not considered for this purpose.

Subject matter

1. Overview of digital analytics
- 1.1. The evolution of analytics
- 1.2. Key changes to Digital Analytics
- 1.3. Digital Analytics in an Era of Digital Transformation
- 1.4. Change: yes we can!
- 1.5. The ESE(P) methodology

2. The awesome world of clickstream analytics
- 2.1. Main metrics demystified
- 2.2. Measuring the omni-channel world
- 2.3. Comparing metrics on different Analytics tools
- 2.4. Core technology concepts and the Web
- 2.5. Practical applications

3. Google Analytics as a day-to-day tool
- 3.1. Introduction to Google Analytics
- 3.2. Evolution to Google Analytics 4
- 3.3. Data dimensions and metrics
- 3.4. Audience
- 3.5. Acquisition
- 3.6. Content analysis
- 3.7. Benchmarking
- 3.8. Account and property configuration

4. Analytics Framework
- 4.1. Analytics Thinking
- 4.2. Objectives definition
- 4.3. How to build a measurement strategy?
- 4.4. Reporting and dashboard tools
- 4.5. Practical applications

5. Advanced usage of analytics tools
- 5.1. Data Enrichment
- 5.2. Segmentation
- 5.3. The importance of Goals
- 5.4. Funnel analysis
- 5.5. E-commerce measurement and analysis
- 5.6. Data Layer and the use of Tag Managers
- 5.7. Experimentation
- 5.8. Reporting and Dashboards
- 5.9. Multi-channel Funnels

6. Marketing metrics and Funnel Conversion
- 6.1. Definition of cost and pricing models (Advertising)
- 6.2. Measuring other channels
- 6.3. Practical examples
- 6.4. Funnels: from attention to conversion
- 6.5. The role of landing pages
- 6.6. Anatomy of a landing page and importance for conversion
- 6.7. Analysis of the client / campaign situation

Programs

Programs where the course is taught: