Digital Marketing, AI, SEO, and Business Strategies
Exam 1
Q1) Performance Marketing & Direct Marketing
Awareness: Performance Marketing (PMK) 70% to reach a broader audience through social media/search ads. Direct Marketing (DMK) 30% to build initial interest in products with targeted email campaigns.
Consideration: PMK 60% to retarget potential customers, helping maintain visibility and keep the brand top-of-mind for potential customers evaluating their options. DMK 40% to deepen engagement through lead nurturing emails.
Decision: PMK 50% to focus on conversion and drive purchases. DMK 50% to encourage customers to finish transactions through personalized discounts.
Retention: PMK 30% to remind customers of the brand and focus on loyalty. DMK 70% to build loyalty and maintain a relationship through newsletters to increase repeat purchases.
Advocacy: PMK 20% referral campaigns to simplify customer advocacy. DMK 80% with referrals and offering exclusive incentives is the most effective way to turn loyal customers into advocates.
Q2) SEO and SEM Strategies: Separate Approaches
SEO and SEM strategies must be created separately because they have distinct goals and approaches.
SEO: Focuses on long-term organic traffic growth by optimizing content, site structure, and technical aspects to align with search engine algorithms. Metrics: keyword rankings, organic traffic. Relies on time and resource dedication.
SEM: Drives immediate results (visibility and conversion) through paid ads. Metrics: ROI, CPC. Requires ongoing financial investment.
By developing them independently, businesses can ensure sustainable growth, conversions, and efficient resource use.
Q3) Transformer’s Technology – Generative AI
Transformer technology is the foundation of generative AI as it helps AI models understand and process information like text or speech effectively. Transformers use a self-attention mechanism, which allows the model to focus on the most relevant parts of the input while understanding the overall context.
Two cases:
- Chatbots: Transformers enable chatbots to have natural, human-like conversations by understanding user questions and providing accurate, context-aware responses.
Example: A chatbot assisting customers with order returns or product inquiries. - Content Creation Tools: They are used to generate high-quality written or visual content tailored to specific needs.
Example: Writing articles, creating marketing copy, or generating AI-based art.
Exam 1
Q4) Advanced SEO
Mobile-Friendly & Mobile-First Indexing
- Focus on optimizing websites for mobile devices using Google’s mobile-first indexing.
- Enhances user experience and improves search rankings with responsive web designs and fast page load speeds tailored to mobile users.
Local SEO
- Optimizes a website for location-based searches by leveraging tools like Google Business Profile or Bing Places.
- Includes frequent updates to business attributes, managing reviews, and implementing schema markup for better machine understanding.
SEO & AI – Voice Searches
- Uses Natural Language Processing (NLP) to optimize for longer, conversational queries often framed as questions.
- Prepares for the prediction that 50% of searches will be voice-based by 2026, ensuring better visibility in voice-driven search results.
Advanced Content SEO: Featured Snippets
- Focuses on optimizing content to appear in featured snippets or “position zero” in search results.
- By answering common questions concisely with high-value information, companies can increase visibility and drive organic traffic.
Q5) Best AI’s
ChatGPT 4 – OpenAI
Claude 2 – Anthropic
Q6) Authors’ Rights Selling AI-Generated Content
They face challenges as copyright laws for selling AI-generated content require human authorship, and AI systems cannot hold copyright. AI-generated works fall into a legal grey area, with no clear protections.
Legal battles, like Getty Images versus Stability AI, highlight the complexities of using unlicensed materials.
Options for protection:
- Licensing AI-generated content with clear terms.
- Advocating for updated intellectual property laws.
- Ensuring content originality to avoid legal disputes.
As the law evolves, companies must stay informed and adopt transparent practices to safeguard their interests.
Q7) Attribution
Google/organic – 5
Instagram – 0
Direct – 5
YouTube – 0
Exam 2
Q1) PENTA GROWTH ESIC
1. Connect Network
ESIC uses mobile and social platforms to connect with students, alumni, and prospective students. These include tools like online portals, social media, and student networks.
Improvement: Leverage “Things” (IoT) by introducing smart campus technologies, such as app-based student navigation, classroom management tools, and AI-powered engagement systems.
2. Share Knowledge: ESIC currently provides proprietary knowledge through its courses and workshops.
Improvement: Expand into open, non-commercial knowledge sharing by offering free resources, such as open-access lectures or blog posts, to attract a wider audience and establish thought leadership.
3. Collect Inventory: ESIC collects distributed knowledge from professors, students, and external contributors. It centralizes this in databases like LMS (Learning Management Systems).
Improvement: Move towards commons-based systems by incorporating student-generated content, open-access research papers, and collaborative knowledge projects to diversify resources.
4. Enable Partners: ESIC collaborates with industry partners, offering internships and co-marketing initiatives.
Improvement: Focus on co-creation with partners by developing joint programs, research projects, or incubators to increase innovation and industry relevance.
5. Empower Users: Currently, ESIC empowers students by offering role-specific resources, like career guidance and alumni networks.
Improvement: Allow students and users to take “any role” by creating platforms where they can contribute as educators, mentors, or content creators, further driving engagement.
How to Improve Engagement Across Three Levels:
1. Attraction:
- Offer free online courses or certifications to draw in new students.
- Increase visibility through partnerships with influencers or companies to promote ESIC programs.
2. Engagement:
- Create gamified learning platforms where students earn points or badges for participation.
- Host regular interactive webinars, Q&A sessions, and student-led initiatives.
3. Retention:
- Introduce personalized AI tools for academic and career counseling.
- Build an active alumni community by fostering mentorship and networking events.
Q2) Difference Between Design Thinking & Lean Innovation
The fundamental difference between Design Thinking and Lean Innovation Management lies in their approach to innovation.
Design Thinking focuses on solutions and emphasizes understanding user needs through creativity and prototyping. It relies on human-centered insights to solve challenges and is particularly useful when conventional experience or technical knowledge cannot address the problem. Lean Innovation Management, on the other hand, prioritizes efficiency by incorporating early customer feedback, minimizing waste, and iterating rapidly. It uses Minimum Viable Products (MVPs) to test ideas and pivot as needed. While Design Thinking emphasizes exploration and empathy, Lean Innovation centers on streamlining processes and resource optimization.
Q3) Foundational AI, Fine-Tuned, and RAG-Enhanced
Foundational AI, fine-tuned, and RAG-enhanced models serve different purposes in AI applications.
1. Foundational models, like GPT-4, are pre-trained on massive datasets to perform a wide range of tasks without additional training.
2. Fine-tuned models adapt foundational models for specific use cases, such as customer service or medical diagnosis, by training them on specialized datasets.
3. RAG-enhanced models (Retrieval-Augmented Generation) combine foundational AI with external databases, allowing real-time retrieval of factual information to enhance responses. While foundational models offer general capabilities, fine-tuned models excel in specialized tasks, and RAG-enhanced models ensure up-to-date and contextually accurate outputs.