Course Code: MKT542
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Synopsis

To understand the customer decision journey (CDJ) and to improve customer experiences at various touch points is essential in marketing, and the CDJ has quite different features in the digital age. Digital marketing analytics is a very important tool to serve this purpose. This course lays out the foundation by explaining the theories and strategies of digital marketing analytics and further introduces the practical methods of applying digital data to the real business issues. The standard process of conducting digital marketing analytics is emphasised. This course compares the traditional and digital channels and focuses on the different measures to examine the effectiveness of the digital marketing campaigns. It also includes the new technology trend and challenges faced when making use of new media data.
Level: 5
Credit Units: 5
Presentation Pattern: EVERY REGULAR SEMESTER

Topics

  • Three-step Marketing Model and ZMOT
  • CDJ - Customer Decision Journey
  • The evolvement of CDJ in digital age
  • MAP - Marketing Analytics Planning
  • Marketing analytics tools
  • Web data collection, analysis and visualization
  • Digital marketing research
  • Digital customer profiling
  • How digital waves change traditional channels
  • Digital channels and the different metrics to measure effectiveness
  • Case: E-commerce platforms and their CDJ
  • Challenges of new media data

Learning Outcome

  • Appraise the customer decision journey in the digital era.
  • Construct customer profiles.
  • Propose a digital marketing analytics plan.
  • Design integrated digital marketing campaigns that fit in each stage of the customer decision journey
  • Collect and examine new media data with marketing analytics tools.
  • Analyse and visualise data with marketing analytics tools.
  • Evaluate the effectiveness of different digital marketing channels.
  • Choose marketing analytics tools to utilize big data.
  • Compose digital marketing strategy to effectively target and interact with consumers.
  • Design marketing analytics plans to monitor and evaluate the effectiveness of marketing campaigns.
  • Demonstrate proficiency in communication.
  • Demonstrate proficiency in group works.
Part-time Programmes / CET Courses

Date and Duration

DayDateWeekTime
Saturday14/2/2026512:00-15:00
Saturday21/2/2026612:00-15:00
Saturday28/2/2026712:00-15:00
Saturday
7/3/2026812:00-15:00
Saturday14/3/2026912:00-15:00
*Monday23/3/20261119:00-22:00


Target Audience

Executive interested in digital marketing.

 

Relevance of Course to employment/upskilling/reskilling

The Digital Marketing Analytics course is highly relevant to employment as it equips learners with the analytical competencies required for data-driven decision-making in contemporary marketing roles. Learners develop the ability to interpret digital marketing data, evaluate campaign performance, and translate analytical insights into actionable marketing strategies, skills that are increasingly demanded across digital, performance, and growth marketing positions.

For working professionals, the course supports upskilling by strengthening their capability to apply analytics tools, metrics, and frameworks to optimise marketing effectiveness. Learners enhance their proficiency in measuring customer behaviour, campaign outcomes, and marketing return on investment, enabling more informed planning, execution, and evaluation within their existing roles.

The course also enables reskilling for individuals seeking to transition into analytics-focused or data-oriented marketing roles. By combining foundational analytical concepts with practical applications in digital marketing contexts, the course provides learners from non-analytics backgrounds with a structured pathway to build analytical confidence and reposition themselves for roles that require stronger data literacy and performance measurement skills.


Admissions pre-requisite

Refer to graduate CET admissions and also include Admission Eligibility Criteria for Graduate CET Modular Courses (Admission Eligibility Criteria for Graduate CET Modular Courses).

 

Schedule

TimeAgenda
Seminar 1Via Zoom/Face to Face
12:00 - 14:00Three-step Marketing Model and ZMOT
14:00-14:20Break
14:20 - 15:00CDJ - Customer Decision Journey
Seminar 2Via Zoom/Face to Face
12:00 - 14:00The evolvement of CDJ in digital age
14:00-14:20Break
14:20 - 15:00MAP - Marketing Analytics Planning
Seminar 3Via Zoom/Face to Face
12:00 - 14:00Marketing analytics tools
14:00-14:20Break
14:20 - 15:00Web data collection, analysis and visualization
Seminar 4Via Zoom/Face to Face
12:00 - 14:00Digital marketing research
14:00-14:20Break
14:20 - 15:00Leveraging on the power of brand story-telling on digital platforms
Seminar 5Via Zoom/Face to Face
12:00 - 14:00How digital waves change traditional channels
14:00-14:20Break
14:20 - 15:00Digital channels and the different metrics to measure effectiveness
Seminar 6Via Zoom/Face to Face
19:00 - 20:00Case: E-commerce platforms and their CDJ
20:00-20:20Break
20:20 - 21:00Challenges of new media data

 

Assessments

Assignments, Online Test, Others, Written Exam, PARTICIPATION

 

Trainer info

Dr Andrew Chew holds a Doctorate in Business Administration from SUSS and an MBA in Marketing from NTU. He brings over three decades of Fortune 500 marketing and leadership experience to the classroom, combining rigorous academic credentials with practical industry insights. An AI educator with MIT Sloan AI certification, he has trained 1000+ adult learners and marketing professionals. Dr. Chew's learner-centric methodology emphasizes real business scenarios and immediate practical application. His expertise spans digital marketing analytics, AI implementation, and data-driven marketing strategy, making complex concepts accessible and immediately applicable to professional practice.

 

 

Course Completion requirements

Participants are required to achieve at least 75% attendance and pass any prescribed examinations/assessments or submit any course/project work (if any) under the course requirement.

  • Participants are required to complete all surveys and feedbacks related to the course
  • The course fees are reviewed annually and may be revised. The University reserves the right to adjust the course fees without prior notice.
  • Singapore University of Social Sciences reserves the right to amend and/or revise the above schedule without prior notice

 

Course Fees, payment and refund policy

 International Participants Singapore Citizens (below 40yrs), Permanent Residents Singapore Citizens (40yrs and above) SkillsFuture Mid - Career Enhanced Subsidy1Enhanced Training Support for SMEs2 (Singaporean and PRs)
Course Fees (A) $3,168.00 $2,640.00 $2,640.00 $2,640.00
SSG Grant (70%) (B)  $1,848.00 $1,848.00 $1,848.00
Nett Course fees (A) - (B) = (C) $3,168.00 $792.00 $792.00 $792.00
9% GST on Nett course fees (D) $285.12 $71.28 $71.28 $71.28
Total nett course fees payable including GST (C) + (D) $3,453.12 $863.28 $863.28 $863.28
Less additional funding if eligible under various schemes (F) $-   $-   $528.00 $528.00
Total nett course fees payable including GST, after additional funding form the various schemes (E) - (f) = (H) $3,453.12 $863.28 $335.28 $335.28
1 Mid-Career Enhanced Subsidy: Singaporeans aged 40 and above may enjoy subsidies up to 90% of the course fees.
2 Enhanced Training Support for SMEs: SME-sponsored employees (Singapore citizens and PRs) aged 21 and above may enjoy subsidies up to 90% of the course fees.

For the various payment mode, please refer here.
For the refund policy, please refer here. 

 

For clarification, please contact the SUSS Academy via the following:
Telephone: +65 6248 0263
Email: [email protected]