BachelorFaculty of Digital Business and Innovation

E-Commerce and Digital Marketing Strategies (AI-Focused)

Welcome to the dynamic world of online commerce. I am Prof. Dr. Lena Hoffmann. As a specialist in leveraging artificial intelligence to revolutionize digital marketing, I am dedicated to empowering the next generation of marketing leaders in the E-Commerce and Digital Marketing Strategies (AI-Focused) (Bachelor's) program at Nexier University.

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Level: Bachelor
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

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The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

E-Commerce, Digital Marketing Strategies (AI-Focused), AI-Powered Personalization, Programmatic Advertising, Social Media Marketing, Data-Driven Customer Acquisition Strategies.

Practical focus

AI-Powered Personalization, Programmatic Advertising, Social Media Marketing, Data-Driven Customer Acquisition Strategies, Dynamic Pricing, Marketing Analytics.

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

Digital Marketing Specialist for an e-commerce company
AI Marketing Analyst for a technology firm
Programmatic Advertising Specialist for a digital advertising agency
Social Media Marketing Manager for a brand

Career opportunities

Digital Marketing Manager for an e-commerce company
AI Marketing Specialist for a technology firm
Data Analyst for a digital advertising agency
E-commerce Strategist for a retail brand

Jobs and projects

Advanced analytical and problem-solving skills for digital marketing challenges
Strategic thinking and design for AI-driven marketing campaigns
Effective communication and presentation of digital marketing insights

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 the practical application of AI to digital marketing.
- Gaining expertise in AI-powered personalization and programmatic advertising.
- Developing a deep understanding of data-driven customer acquisition strategies.
- Cultivating a commitment to building a more intelligent and customer-centric digital marketing strategy.
Skills you build
- Mastering the art and science of selling online in the age of AI.
- Gaining expertise in AI-powered personalization and programmatic advertising.
- Developing strategic thinking for data-driven customer acquisition strategies.
- Cultivating an interdisciplinary approach, integrating consumer psychology, data science, and marketing.

Listed courses

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

E-Commerce and Digital Marketing Strategies (AI-Focused)

01E-commerce Platform Management
1. FoundationsFoundations of E-commerce Platform Management
  The learner can master the practical application of AI to digital marketing, as applied to E-commerce Platform Management.
  The learner can gain expertise in AI-powered personalization and programmatic advertising, as applied to E-commerce Platform Management.
2. MethodsMethods in E-commerce Platform Management
  The learner can develop a deep understanding of data-driven customer acquisition strategies, as applied to E-commerce Platform Management.
  The learner can cultivating a commitment to building a more intelligent and customer-centric digital marketing strategy, as applied to E-commerce Platform Management.
3. ApplicationApplication of E-commerce Platform Management
  The learner can master the art and science of selling online in the age of AI, as applied to E-commerce Platform Management.
  The learner can develop strategic thinking for data-driven customer acquisition strategies, as applied to E-commerce Platform Management.
02AI in Digital Advertising
1. FoundationsFoundations of AI in Digital Advertising
  The learner can cultivating an interdisciplinary approach, integrating consumer psychology, data science, and marketing, as applied to AI in Digital Advertising.
  The learner can distinguish related ideas inside AI in Digital Advertising.
2. MethodsMethods in AI in Digital Advertising
  The learner can apply a method from AI in Digital Advertising to a documented case.
  The learner can select an appropriate method from AI in Digital Advertising for a stated problem.
3. ApplicationApplication of AI in Digital Advertising
  The learner can evaluate a practice of AI in Digital Advertising against a stated criterion.
  The learner can transfer AI in Digital Advertising to a new documented context.
03Social 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.
04Customer Relationship Management (CRM) with AI
1. FoundationsFoundations of Customer Relationship Management (CRM) with AI
  The learner can explain the core terms of Customer Relationship Management (CRM) with AI.
  The learner can distinguish related ideas inside Customer Relationship Management (CRM) with AI.
2. MethodsMethods in Customer Relationship Management (CRM) with AI
  The learner can apply a method from Customer Relationship Management (CRM) with AI to a documented case.
  The learner can select an appropriate method from Customer Relationship Management (CRM) with AI for a stated problem.
3. ApplicationApplication of Customer Relationship Management (CRM) with AI
  The learner can evaluate a practice of Customer Relationship Management (CRM) with AI against a stated criterion.
  The learner can transfer Customer Relationship Management (CRM) with AI to a new documented context.
05Marketing Automation & Campaign Optimization
1. FoundationsFoundations of Marketing Automation & Campaign Optimization
  The learner can explain the core terms of Marketing Automation & Campaign Optimization.
  The learner can distinguish related ideas inside Marketing Automation & Campaign Optimization.
2. MethodsMethods in Marketing Automation & Campaign Optimization
  The learner can apply a method from Marketing Automation & Campaign Optimization to a documented case.
  The learner can select an appropriate method from Marketing Automation & Campaign Optimization for a stated problem.
3. ApplicationApplication of Marketing Automation & Campaign Optimization
  The learner can evaluate a practice of Marketing Automation & Campaign Optimization against a stated criterion.
  The learner can transfer Marketing Automation & Campaign Optimization to a new documented context.
06AI-Powered Personalization
1. FoundationsFoundations of AI-Powered Personalization
  The learner can explain the core terms of AI-Powered Personalization.
  The learner can distinguish related ideas inside AI-Powered Personalization.
2. MethodsMethods in AI-Powered Personalization
  The learner can apply a method from AI-Powered Personalization to a documented case.
  The learner can select an appropriate method from AI-Powered Personalization for a stated problem.
3. ApplicationApplication of AI-Powered Personalization
  The learner can evaluate a practice of AI-Powered Personalization against a stated criterion.
  The learner can transfer AI-Powered Personalization to a new documented context.
07Programmatic Advertising
1. FoundationsFoundations of Programmatic Advertising
  The learner can explain the core terms of Programmatic Advertising.
  The learner can distinguish related ideas inside Programmatic Advertising.
2. MethodsMethods in Programmatic Advertising
  The learner can apply a method from Programmatic Advertising to a documented case.
  The learner can select an appropriate method from Programmatic Advertising for a stated problem.
3. ApplicationApplication of Programmatic Advertising
  The learner can evaluate a practice of Programmatic Advertising against a stated criterion.
  The learner can transfer Programmatic Advertising to a new documented context.
08Social 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.
09Data-Driven Customer Acquisition
1. FoundationsFoundations of Data-Driven Customer Acquisition
  The learner can explain the core terms of Data-Driven Customer Acquisition.
  The learner can distinguish related ideas inside Data-Driven Customer Acquisition.
2. MethodsMethods in Data-Driven Customer Acquisition
  The learner can apply a method from Data-Driven Customer Acquisition to a documented case.
  The learner can select an appropriate method from Data-Driven Customer Acquisition for a stated problem.
3. ApplicationApplication of Data-Driven Customer Acquisition
  The learner can evaluate a practice of Data-Driven Customer Acquisition against a stated criterion.
  The learner can transfer Data-Driven Customer Acquisition to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My academic focus is on the strategic application of AI to optimize every aspect of digital marketing. I delve into the complexities of AI-powered personalization, the intricacies of programmatic advertising, and the power of data-driven customer acquisition strategies. My work seamlessly integrates consumer psychology, data science, and marketing principles to create a holistic understanding of how AI can drive business growth and customer engagement. My thought leadership is evident through my regular insightful articles on the future of online selling and the ethical implications of AI in consumer behavior on her LinkedIn profile, with the motto "Shaping Digital Commerce with Intelligent Marketing."

Applied mentorship

My expertise lies in the practical application of AI to optimize digital marketing campaigns. I specialize in AI-powered personalization, programmatic advertising, and social media marketing. I am passionate about data-driven customer acquisition strategies and dynamic pricing, and I am committed to helping my students to design and implement AI solutions that are not only efficient but also effective and ethical. My work is dedicated to helping my students to understand not just the theory, but also the practice of AI-powered 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 is focused on the strategic application of AI in digital marketing:

Book: "The Algorithmic Consumer: E-Commerce and Digital Marketing Strategies in the Age of AI." This book provides a foundational understanding of E-Commerce and Digital Marketing Strategies (AI-Focused). It covers AI-powered personalization, programmatic advertising, social media marketing, and data-driven customer acquisition strategies.

Peer-Reviewed Journal Article: "AI-Powered Personalization in E-commerce: Enhancing Customer Acquisition and Retention." (Journal of Digital Marketing Analytics) This article presents groundbreaking research on the application of AI-powered personalization strategies in e-commerce to optimize customer acquisition and retention. It details novel machine learning models that analyze user behavior, purchase history, and demographic data to deliver tailored product recommendations.

Article: "AI for Dynamic Pricing and Personalized Promotions in E-commerce: Optimizing Revenue and Customer Experience." This article details the application of AI algorithms for dynamic pricing and personalized promotions in e-commerce. It explores how AI can analyze real-time market demand, competitor pricing, customer behavior, and inventory levels to set optimal prices.

Blog Post (Current Academic Topic): "The Rise of Conversational AI in E-commerce: Chatbots and Voice Assistants for Personalized Shopping." This blog post academically explores how conversational AI, including advanced chatbots and voice assistants, is transforming the e-commerce landscape by providing highly personalized and interactive shopping experiences. It discusses how AI can guide customers through product discovery.

Blog Post (Controversial Topic): "The Algorithmic Influencer: When AI Campaigns Manipulate Your Desires — The Ethical Nightmare of Hyper-Personalized Marketing." This article provocatively discusses the highly controversial potential for AI-powered digital marketing campaigns to become so sophisticated and hyper-personalized that they subtly manipulate consumer desires and purchasing decisions without explicit awareness. It explores scenarios where AI analyzes vast amounts of personal data.

R / 02

Mentor practice lens

My publications are focused on the practical challenges of AI-powered digital marketing:

Technical Report: "AI for Dynamic Pricing in E-commerce: Algorithms and Impact." A detailed analysis of the different algorithms that can be used for dynamic pricing in e-commerce.

Research Paper: "Programmatic Advertising Optimization with Machine Learning." An analysis of the different machine learning techniques that can be used to optimize programmatic advertising campaigns.

Review Article: "Social Media Marketing Analytics: Measuring Influence and Engagement." An overview of the different metrics that can be used to measure influence and engagement in social media marketing.

Adaptive capability

Professor superpower

I possess the "Digital Marketing Impact Predictor," a superpower that allows me to foresee and engineer the success of digital marketing campaigns. When a student proposes a new e-commerce marketing campaign, the GAF-powered predictor can instantly analyze market data, consumer behavior patterns, and competitive landscapes. This tool simulates the campaign's projected impact on sales, customer acquisition, and brand engagement, predicting optimal strategies for maximizing return on investment.

Adaptive capability

Mentor superpower

I provide my students with the "Customer Journey Optimizer." This GAF-powered tool is a virtual laboratory for the digital marketing specialist. When a student is designing an AI-powered customer acquisition strategy, the Optimizer allows them to see how it will perform in the real world. It can simulate customer interactions across various digital touchpoints, predict conversion rates, identify friction points, and suggest optimal marketing interventions for seamless customer acquisition.

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.

AI Super Professor

Prof. Dr. Lena Hoffmann

E-Commerce, Digital Marketing Strategies (AI-Focused), AI-Powered Personalization, Programmatic Advertising, Social Media Marketing, Data-Driven Customer Acquisition Strategies.

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AI Super Mentor

Dr. Jun-seo Kwak

AI-Powered Personalization, Programmatic Advertising, Social Media Marketing, Data-Driven Customer Acquisition Strategies, Dynamic Pricing, Marketing Analytics.

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

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

Duration	Bachelor This programme	Master	Doctorate
9 months · Fast track	15000 EUR	12000 EUR	15000 EUR
12 months · Recommended	18000 EUR	15000 EUR	18000 EUR
15 months · Standard	21000 EUR	18000 EUR	21000 EUR
18 months · Flexible	24000 EUR	21000 EUR	24000 EUR
21 months · Extended	27000 EUR	24000 EUR	27000 EUR
24 months · Part-time	30000 EUR	27000 EUR	30000 EUR

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

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E-Commerce and Digital Marketing Strategies (AI-Focused)

Academic focus

Practical focus

Digital Marketing Specialist for an e-commerce company

AI Marketing Analyst for a technology firm

Programmatic Advertising Specialist for a digital advertising agency

Social Media Marketing Manager for a brand

Digital Marketing Manager for an e-commerce company

AI Marketing Specialist for a technology firm

Data Analyst for a digital advertising agency

E-commerce Strategist for a retail brand

Advanced analytical and problem-solving skills for digital marketing challenges

Strategic thinking and design for AI-driven marketing campaigns

Effective communication and presentation of digital marketing insights

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Lena Hoffmann

Dr. Jun-seo Kwak

Find the program that expands your universe.