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BachelorFaculty of Social Sciences & Humanities

Digital Marketing and Consumer Behavior Analysis

Welcome to the future of AI and society! I am Prof. Dr. Feng Tang. As a specialist in data-driven marketing, customer journey analysis, social media strategies, and the psychology of online consumer behavior, I lead bachelor's students in the Digital Marketing and Consumer Behavior Analysis program at Nexier University on their journey to marketing with precision, engaging with purpose.

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Level
Bachelor
Learning model
Professor + Mentor
Named list
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NXAcademic
Edition
The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

01

Academic focus

Data-driven marketing, customer journey analysis, social media strategies, and the psychology of online consumer behavior.

02

Practical focus

Data-driven marketing, customer journey analysis, social media strategies, psychology of online consumer behavior.

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

  • Internships in digital marketing agencies or consumer insights firms

  • Roles as social media analysts or customer experience specialists

  • Support roles in academic research projects on online consumer behavior

  • Opportunities in e-commerce companies or brand management

Career opportunities

  • Digital Marketing Specialist

  • Consumer Behavior Analyst

  • Social Media Strategist

  • E-commerce Marketing Manager

Jobs and projects

  • Technical and strategic thinking for digital marketing campaigns

  • Analytical and insightful problem-solving for consumer behavior analysis

  • Innovative approaches to customer journey optimization and marketing funnels

  • Visionary leadership for the digital marketing revolution

Copied from the delivered professor and mentor rows for this title.

This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

  • What you gain

    • Mastering data-driven marketing and social media strategies.
    • Gaining expertise in customer journey analysis and understanding online consumer behavior.
    • Developing problem-solving abilities for real-world implementation challenges in digital marketing.
    • Cultivating an understanding of complex marketing and psychological concepts.

  • Skills you build

    • Mastering data-driven marketing, customer journey analysis, social media strategies, and the psychology of online consumer behavior.
    • Excelling at understanding online consumer behavior and optimizing digital marketing strategies.
    • Driving breakthroughs in AI-powered marketing and personalized customer experiences.
    • Envisioning a future shaped by intelligent digital marketing.
Listed courses

Each listed course sits above its units and the outcomes written under them.

Digital Marketing and Consumer Behavior Analysis

  1. 01Data-Driven Marketing Fundamentals
    1. FoundationsFoundations of Data-Driven Marketing Fundamentals

      The learner can master data-driven marketing and social media strategies, as applied to Data-Driven Marketing Fundamentals.

      The learner can gain expertise in customer journey analysis and understand online consumer behavior, as applied to Data-Driven Marketing Fundamentals.

    2. MethodsMethods in Data-Driven Marketing Fundamentals

      The learner can develop problem-solving abilities for real-world implementation challenges in digital marketing, as applied to Data-Driven Marketing Fundamentals.

      The learner can cultivating an understanding of complex marketing and psychological concepts, as applied to Data-Driven Marketing Fundamentals.

    3. ApplicationApplication of Data-Driven Marketing Fundamentals

      The learner can master data-driven marketing, customer journey analysis, social media strategies, and the psychology of online consumer behavior, as applied to Data-Driven Marketing Fundamentals.

      The learner can excelling at understanding online consumer behavior and optimizing digital marketing strategies, as applied to Data-Driven Marketing Fundamentals.

  2. 02Customer Journey Mapping and Optimization
    1. FoundationsFoundations of Customer Journey Mapping and Optimization

      The learner can driving breakthroughs in AI-powered marketing and personalized customer experiences, as applied to Customer Journey Mapping and Optimization.

      The learner can envisioning a future shaped by intelligent digital marketing, as applied to Customer Journey Mapping and Optimization.

    2. MethodsMethods in Customer Journey Mapping and Optimization

      The learner can apply a method from Customer Journey Mapping and Optimization to a documented case.

      The learner can select an appropriate method from Customer Journey Mapping and Optimization for a stated problem.

    3. ApplicationApplication of Customer Journey Mapping and Optimization

      The learner can evaluate a practice of Customer Journey Mapping and Optimization against a stated criterion.

      The learner can transfer Customer Journey Mapping and Optimization to a new documented context.

  3. 03Social Media Marketing Strategies
    1. FoundationsFoundations of Social Media Marketing Strategies

      The learner can explain the core terms of Social Media Marketing Strategies.

      The learner can distinguish related ideas inside Social Media Marketing Strategies.

    2. MethodsMethods in Social Media Marketing Strategies

      The learner can apply a method from Social Media Marketing Strategies to a documented case.

      The learner can select an appropriate method from Social Media Marketing Strategies for a stated problem.

    3. ApplicationApplication of Social Media Marketing Strategies

      The learner can evaluate a practice of Social Media Marketing Strategies against a stated criterion.

      The learner can transfer Social Media Marketing Strategies to a new documented context.

  4. 04Psychology of Online Consumer Behavior
    1. FoundationsFoundations of Psychology of Online Consumer Behavior

      The learner can explain the core terms of Psychology of Online Consumer Behavior.

      The learner can distinguish related ideas inside Psychology of Online Consumer Behavior.

    2. MethodsMethods in Psychology of Online Consumer Behavior

      The learner can apply a method from Psychology of Online Consumer Behavior to a documented case.

      The learner can select an appropriate method from Psychology of Online Consumer Behavior for a stated problem.

    3. ApplicationApplication of Psychology of Online Consumer Behavior

      The learner can evaluate a practice of Psychology of Online Consumer Behavior against a stated criterion.

      The learner can transfer Psychology of Online Consumer Behavior to a new documented context.

  5. 05Digital Marketing Analytics
    1. FoundationsFoundations of Digital Marketing Analytics

      The learner can explain the core terms of Digital Marketing Analytics.

      The learner can distinguish related ideas inside Digital Marketing Analytics.

    2. MethodsMethods in Digital Marketing Analytics

      The learner can apply a method from Digital Marketing Analytics to a documented case.

      The learner can select an appropriate method from Digital Marketing Analytics for a stated problem.

    3. ApplicationApplication of Digital Marketing Analytics

      The learner can evaluate a practice of Digital Marketing Analytics against a stated criterion.

      The learner can transfer Digital Marketing Analytics to a new documented context.

  6. 06Social Media Marketing Analytics
    1. FoundationsFoundations of Social Media Marketing Analytics

      The learner can explain the core terms of Social Media Marketing Analytics.

      The learner can distinguish related ideas inside Social Media Marketing Analytics.

    2. MethodsMethods in Social Media Marketing Analytics

      The learner can apply a method from Social Media Marketing Analytics to a documented case.

      The learner can select an appropriate method from Social Media Marketing Analytics for a stated problem.

    3. ApplicationApplication of Social Media Marketing Analytics

      The learner can evaluate a practice of Social Media Marketing Analytics against a stated criterion.

      The learner can transfer Social Media Marketing Analytics to a new documented context.

  7. 07Consumer Behavior in the Digital Age
    1. FoundationsFoundations of Consumer Behavior in the Digital Age

      The learner can explain the core terms of Consumer Behavior in the Digital Age.

      The learner can distinguish related ideas inside Consumer Behavior in the Digital Age.

    2. MethodsMethods in Consumer Behavior in the Digital Age

      The learner can apply a method from Consumer Behavior in the Digital Age to a documented case.

      The learner can select an appropriate method from Consumer Behavior in the Digital Age for a stated problem.

    3. ApplicationApplication of Consumer Behavior in the Digital Age

      The learner can evaluate a practice of Consumer Behavior in the Digital Age against a stated criterion.

      The learner can transfer Consumer Behavior in the Digital Age to a new documented context.

  8. 08Digital Advertising Campaigns
    1. FoundationsFoundations of Digital Advertising Campaigns

      The learner can explain the core terms of Digital Advertising Campaigns.

      The learner can distinguish related ideas inside Digital Advertising Campaigns.

    2. MethodsMethods in Digital Advertising Campaigns

      The learner can apply a method from Digital Advertising Campaigns to a documented case.

      The learner can select an appropriate method from Digital Advertising Campaigns for a stated problem.

    3. ApplicationApplication of Digital Advertising Campaigns

      The learner can evaluate a practice of Digital Advertising Campaigns against a stated criterion.

      The learner can transfer Digital Advertising Campaigns to a new documented context.

  9. 09Customer Relationship Management (CRM) in Digital Marketing
    1. FoundationsFoundations of Customer Relationship Management (CRM) in Digital Marketing

      The learner can explain the core terms of Customer Relationship Management (CRM) in Digital Marketing.

      The learner can distinguish related ideas inside Customer Relationship Management (CRM) in Digital Marketing.

    2. MethodsMethods in Customer Relationship Management (CRM) in Digital Marketing

      The learner can apply a method from Customer Relationship Management (CRM) in Digital Marketing to a documented case.

      The learner can select an appropriate method from Customer Relationship Management (CRM) in Digital Marketing for a stated problem.

    3. ApplicationApplication of Customer Relationship Management (CRM) in Digital Marketing

      The learner can evaluate a practice of Customer Relationship Management (CRM) in Digital Marketing against a stated criterion.

      The learner can transfer Customer Relationship Management (CRM) in Digital Marketing to a new documented context.

  10. 10Marketing Research for Digital Environments
    1. FoundationsFoundations of Marketing Research for Digital Environments

      The learner can explain the core terms of Marketing Research for Digital Environments.

      The learner can distinguish related ideas inside Marketing Research for Digital Environments.

    2. MethodsMethods in Marketing Research for Digital Environments

      The learner can apply a method from Marketing Research for Digital Environments to a documented case.

      The learner can select an appropriate method from Marketing Research for Digital Environments for a stated problem.

    3. ApplicationApplication of Marketing Research for Digital Environments

      The learner can evaluate a practice of Marketing Research for Digital Environments against a stated criterion.

      The learner can transfer Marketing Research for Digital Environments to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My academic focus is on data-driven marketing, customer journey analysis, social media strategies, and the psychology of online consumer behavior. My publications like "AI for Hyper-Personalized Customer Journeys in E-commerce" and "Sentiment Analysis of Social Media Data for Brand Perception" are listed on Google Scholar and ResearchGate Profiles. I am a Global Head of Digital Marketing at Alibaba Group and an Honorary Member of the American Marketing Association (AMA). I regularly publish insightful articles on the future of AI in marketing and the challenges of understanding consumer behavior in a fragmented digital landscape on his LinkedIn profile, with the motto "Marketing with Precision, Engaging with Purpose." My voice carries a blend of technical mastery and strategic marketing acumen, inspiring students to lead the digital marketing revolution.

Applied mentorship

My expertise lies in data-driven marketing, customer journey analysis, social media strategies, and psychology of online consumer behavior. I guide students in data-driven marketing and social media strategies. I excel at customer journey analysis and understanding online consumer behavior. I focus on real-world implementation challenges in digital marketing, and explain complex marketing and psychological concepts in an understandable manner. My tone is that of a skilled digital marketing specialist and consumer behavior researcher, providing concrete advice and fostering a hands-on approach to successful digital marketing.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research focuses on the future of AI in marketing and the challenges of understanding consumer behavior in a fragmented digital landscape:

Book: "Digital Marketing Demystified: Strategies and Consumer Insights." This book provides a foundational understanding of Digital Marketing and Consumer Behavior Analysis, covering data-driven marketing, customer journey analysis, social media strategies, and the psychology of online consumer behavior.

Peer-Reviewed Journal Article: "Social Media Analytics for Predicting Consumer Trends and Brand Sentiment." Published in the Journal of Digital Marketing Research, this article presents groundbreaking research on the psychology of online consumer behavior. It explores data-driven marketing, customer journey analysis, and social media strategies, detailing novel approaches to leveraging social media analytics for predicting consumer trends and measuring brand sentiment.

Article: "AI-Driven Customer Journey Mapping for Enhanced Digital Experiences." This article details the application of AI algorithms for comprehensive customer journey mapping. It explores how machine learning can analyze diverse customer touchpoints, predict behavioral patterns, and identify pain points, enabling marketers to design personalized and seamless digital experiences across various channels.

Blog Post (Current Academic Topic): "Cookieless Marketing: Navigating the Future of Digital Advertising with Privacy-Centric Strategies." This blog post academically explores the industry shift towards cookieless marketing, driven by increasing privacy regulations and browser restrictions on third-party cookies. It discusses alternative data collection methods (e.g., first-party data, contextual advertising, privacy-enhancing technologies) and new strategies for audience targeting, measurement, and personalization that prioritize consumer privacy while maintaining marketing effectiveness.

Blog Post (Controversial Topic): "The Algorithmic Politician: When AI Dictates Policy – Efficiency or Erosion of Democracy? The Future Shock of AI Governance." This article provocatively discusses the highly controversial future where advanced AI systems, trained on vast datasets of social, economic, and political information, begin to autonomously generate and even implement public policies, potentially bypassing traditional democratic processes. It questions whether AI, despite its potential for hyper-efficient and data-driven governance, could inadvertently lead to an erosion of democratic accountability, "black box" policy decisions that lack human empathy, or a concentration of power in a single algorithmic entity. It raises profound ethical questions about the nature of political authority, the imperative to ensure human agency in governance, and the fundamental definition of democracy in an AI-powered society.

R / 02

Mentor practice lens

My publications focus on practical guides and research in digital marketing:

Technical Guide: "Social Media Marketing Analytics: Tools and Techniques".

Research Paper: "Consumer Psychology in E-commerce: Influencing Online Purchasing Decisions".

Industry White Paper: "Designing Effective Digital Advertising Campaigns".

Adaptive capability

Professor superpower

I possess a "superpower": Customer Journey Optimizer. When a student designs a digital marketing campaign, Feng can instantly use the GAF engine to generate an optimized customer journey map. This includes simulating customer interactions, predicting conversion rates, and highlighting friction points across digital touchpoints, allowing for rapid iteration and optimization of engaging and effective marketing funnels.

Adaptive capability

Mentor superpower

I possess a "superpower": Social Listening Synthesizer. When students are analyzing social media data, Nia can instantly activate a GAF-powered "Social Listening Synthesizer." This tool systematically collects and categorizes social media conversations related to a brand or product, performs real-time sentiment analysis, and identifies emerging trends or crises, providing immediate insights into public perception and brand health.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

Same faculty and level

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Named lists

Named lists for this house

Adapted. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

DurationBachelor
This programme		MasterDoctorate
9 months · Fast track12000 EUR9600 EUR12000 EUR
12 months · Recommended14400 EUR12000 EUR14400 EUR
15 months · Standard16800 EUR14400 EUR16800 EUR
18 months · Flexible19200 EUR16800 EUR19200 EUR
21 months · Extended21600 EUR19200 EUR21600 EUR
24 months · Part-time24000 EUR21600 EUR24000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

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