Advanced Digital Marketing + Gen AI

Advanced Digital Marketing + Gen AI is a 6-month practical training program created for students, working professionals, business owners, freelancers and aspiring marketers who want to understand how modern digital growth actually works. The program combines core digital marketing skills with responsible AI workflows so learners can plan campaigns faster, create stronger content, measure results more clearly and present their work with confidence.

This course goes beyond basic posting and promotion. Students learn how digital strategy connects with business objectives, customer journeys, marketing funnels, positioning, offers, lead generation, conversion rate optimization, analytics and retention. Every topic is taught with a practical mindset so learners understand not only what to do, but why each activity matters for brand growth, sales and measurable marketing performance.

Gen AI is included as a professional marketing assistant throughout the course. Learners practice using AI for research, audience personas, keyword ideas, content outlines, ad copy variations, creative briefs, reporting summaries, dashboard insights, campaign recommendations and workflow automation. At the same time, the course emphasizes human review, accuracy, brand voice, ethical content, privacy awareness and responsible use of AI-generated material.

Key learning outcomes:

- Understand the full digital marketing ecosystem across websites, search engines, social media, paid ads, email, WhatsApp, CRM, marketplaces, analytics and automation.

- Build research-backed marketing strategies using customer understanding, competitor analysis, search intent, social listening, offers and funnel planning.

- Create SEO, content and social media plans that support long-term visibility, brand trust, lead generation and paid campaign performance.

- Plan Google, Meta and LinkedIn campaigns with audiences, budgets, creatives, copy, landing pages, tracking and optimization logic.

- Use GA4 awareness, UTM planning, dashboards, campaign reports and AI-assisted summaries to explain performance with clarity.

- Improve landing pages, funnels, forms, CTAs, trust signals and follow-up systems to increase conversion quality.

- Build CRM, email, WhatsApp and automation workflows that improve lead nurturing, retention and sales handoff.

- Apply marketing to e-commerce, local business, service lead generation, marketplace growth and repeat customer development.

- Use Gen AI tools for research, copywriting, creative planning, analytics, reporting and productivity while maintaining quality control.

- Prepare portfolio assets, guided practical projects and a final capstone project that can be explained in interviews, freelancing discussions and client presentations.

By the end of the program, students will have a detailed understanding of advanced digital marketing execution and AI-supported marketing operations. They will be able to create campaign briefs, content calendars, SEO plans, ads plans, tracking sheets, CRO reports, automation flows and portfolio-ready marketing presentations.

Build a strong foundation in digital marketing, growth strategy, online customer journeys and responsible Gen AI use for professional marketing work.

- Digital marketing landscape: websites, search engines, social platforms, paid ads, content, email, WhatsApp, marketplaces and analytics.

- Advanced marketing mindset: business goals, funnel stages, customer journey, conversion actions, retention, lifetime value and growth loops.

- Important metrics: impressions, reach, clicks, CTR, CPC, CPM, CPL, CPA, conversion rate, ROAS, CAC, LTV, engagement and revenue contribution.

- Gen AI role in marketing: research support, campaign ideas, content drafting, creative briefs, reporting summaries and workflow acceleration.

- Prompting basics: context, role, task, target audience, constraints, examples, output format, revision instructions and quality checks.

- Marketing ethics: truthful claims, consent, privacy awareness, platform policies, copyright caution, data protection and responsible AI use.

- Brand and positioning basics: audience promise, tone of voice, value proposition, benefits, proof, objections and offer clarity.

- Campaign planning structure: objective, audience, channel, message, creative, landing page, budget, tracking, reporting and optimization plan.

- AI limitations: hallucination risk, outdated information, weak brand understanding, generic copy, bias and the need for human review.

- Labs: map a digital funnel, write AI prompts, compare manual and AI-assisted outputs and prepare a marketing objective sheet.

- Practice outcome: explain digital marketing clearly and use Gen AI as a safe assistant for planning, research and execution.

Learn how to convert business information into research-backed campaigns using customer understanding, competitor analysis and structured AI prompts.

- Market research inputs: industry type, product category, customer problem, buying behavior, demand pattern, pricing, location and seasonality.

- Audience persona creation: demographics, interests, pain points, motivation, objections, decision triggers, trust signals and communication style.

- Competitor analysis: websites, ads, offers, landing pages, social content, reviews, pricing, promises, funnels and content gaps.

- Search and social intent: informational questions, commercial comparisons, transactional searches, local intent, branded intent and content demand.

- Message mining: reviews, comments, FAQs, sales calls, support chats, testimonials and real customer words for stronger copy.

- Prompt frameworks: ask AI for persona drafts, keyword ideas, competitor summaries, copy angles, objection lists and content outlines.

- Research validation: verify claims, remove weak assumptions, check business context, compare sources and avoid relying on AI alone.

- Segmentation strategy: cold audience, warm visitors, engaged followers, abandoned leads, customers, repeat buyers and high-value segments.

- Offer planning: discounts, trials, bundles, consultations, demos, lead magnets, urgency, guarantees and proof-based conversion support.

- Labs: build persona cards, competitor research sheet, AI prompt library, keyword intent map and campaign brief notes.

- Practice outcome: prepare research-backed marketing direction with better targeting, message clarity and AI-assisted planning.

Create content strategies that support search visibility, brand trust, paid campaigns, lead generation and long-term organic growth.

- SEO fundamentals: crawling, indexing, ranking factors awareness, search intent, user experience, helpful content and website credibility.

- Keyword strategy: primary keywords, secondary keywords, long-tail questions, local keywords, branded searches and topic clusters.

- On-page SEO: title tags, meta descriptions, headings, URLs, internal links, image alt text, schema awareness and content readability.

- AI content planning: generate outlines, FAQs, hooks, examples, title options, meta ideas, social snippets and content calendars.

- Human editing workflow: fact-checking, brand voice, originality, examples, clarity, formatting, proof and avoiding generic AI content.

- Content formats: blogs, landing pages, pillar pages, comparison pages, case studies, guides, reels scripts, carousels and email content.

- Technical SEO awareness: page speed, mobile usability, broken links, redirects, duplicate pages, sitemap, robots rules and index checks.

- Local SEO: Google Business Profile, reviews, service pages, NAP consistency, location intent, calls, directions and local trust signals.

- Content distribution: repurpose blogs into ads, short videos, email, WhatsApp, LinkedIn posts and remarketing creative material.

- Labs: create keyword map, write AI-assisted content brief, edit a blog outline and plan a 30-day content calendar.

- Practice outcome: plan and improve SEO-friendly content while using AI responsibly without losing quality or accuracy.

Develop advanced social media planning skills for brand awareness, engagement, trust building, lead generation and content consistency.

- Platform roles: Instagram, Facebook, LinkedIn, YouTube, shorts, reels, community pages and platform-wise content behavior.

- Content pillars: education, entertainment, proof, product demo, behind-the-scenes, founder stories, testimonials, offers and FAQs.

- Creative strategy: hook, problem, solution, benefit, proof, CTA, visual hierarchy, caption structure and platform-native content style.

- Short-form video planning: opening hook, script, scene breakdown, captions, thumbnail, sound awareness, pacing and retention points.

- AI for content ideas: generate hooks, carousel outlines, reel scripts, captions, caption variants, hashtag ideas and topic calendars.

- Brand voice: professional, friendly, premium, educational, bold, local, youthful and consistent tone across all channels.

- Community growth: comments, DMs, polls, Q&A, stories, lives, groups, collaborations and relationship-based engagement.

- Social proof: reviews, user-generated content, influencer mentions, before-after stories, customer questions and case-study snippets.

- Content workflow: ideation, approval, design, scheduling, publishing, response handling, reporting and improvement notes.

- Labs: create content pillars, write reel scripts, plan carousel topics, prepare AI prompts and build a monthly social calendar.

- Practice outcome: design social media plans that connect brand identity, creative quality, consistency and measurable business goals.

Learn practical paid advertising across search, social, retargeting and B2B channels with campaign planning and performance review.

- Paid ads strategy: awareness, traffic, leads, sales, app installs, retargeting, retention and full-funnel budget allocation.

- Google Search Ads: campaign structure, keywords, match types, negative keywords, ad assets, quality score concepts and search intent.

- Meta Ads: campaign objective, ad set, audience, placements, creatives, optimization event, pixel awareness and campaign testing.

- LinkedIn Ads: B2B targeting, job role, industry, company size, lead forms, content offers and high-value lead planning.

- Audience strategy: core audience, custom audience, lookalike audience, remarketing, exclusions, audience overlap and funnel segmentation.

- Creative testing: headline, hook, image, video, CTA, offer, testimonial, format, landing page match and fatigue monitoring.

- Budget and bidding: daily budget, lifetime budget, testing phase, learning phase, scaling decisions, cost control and bid strategy awareness.

- AI ad support: generate ad copy variations, keyword themes, creative briefs, landing page ideas and optimization hypotheses.

- Optimization rhythm: search terms review, performance breakdowns, audience review, creative refresh, landing page diagnosis and spend decisions.

- Labs: build Google and Meta campaign structures, write ad copy sets, create targeting plan and prepare optimization checklist.

- Practice outcome: launch and evaluate paid campaigns with stronger strategy, cleaner structure and better cost-control thinking.

Build a measurement system that helps marketers understand traffic, conversions, lead quality, revenue contribution and improvement areas.

- Tracking mindset: identify actions that matter such as form submits, calls, WhatsApp clicks, purchases, bookings, downloads and signups.

- UTM planning: source, medium, campaign, content, term, naming discipline, reporting clarity and avoiding messy campaign data.

- GA4 awareness: events, conversions, traffic acquisition, engagement, landing pages, explorations and limitations of platform reporting.

- Tag management: container basics, triggers, variables, preview mode, publishing discipline, documentation and quality checks.

- Pixels and tags: Meta pixel, Google tag, event matching, conversion API awareness, browser limitations and data quality signals.

- Attribution basics: last click, first touch, assisted conversions, platform bias, multi-touch awareness and decision-making limitations.

- Dashboard design: spend, impressions, clicks, leads, sales, CPL, CPA, ROAS, conversion rate, channel comparison and trend notes.

- AI for reporting: summarize campaign data, identify patterns, create insights, draft recommendations and generate client-friendly summaries.

- Data quality errors: duplicate events, broken UTMs, wrong conversion action, spam leads, bot traffic and disconnected CRM data.

- Labs: create UTM sheet, event map, GA4 report outline, dashboard template and AI-assisted monthly performance summary.

- Practice outcome: use data properly to explain campaign performance, diagnose problems and recommend next actions confidently.

Learn how landing page quality, messaging, user experience and conversion design influence every marketing campaign result.

- Funnel structure: awareness page, lead magnet, service page, product page, checkout, thank-you page, remarketing and follow-up sequence.

- Landing page essentials: message match, headline, benefits, proof, CTA, form, visual hierarchy, FAQ, trust badges and mobile layout.

- Conversion actions: form submission, WhatsApp click, phone call, demo booking, purchase, consultation, download and store visit awareness.

- Copywriting for CRO: problem, promise, proof, offer, urgency, objection handling, risk reversal and one clear action.

- Form strategy: required fields, lead quality questions, validation, CRM fields, spam protection and shorter mobile-friendly forms.

- Page speed awareness: image optimization, scripts, hosting, tracking tags, plugins, mobile load time and impact on paid campaign cost.

- A/B testing: headline, CTA, offer, proof section, layout, form length, creative-message match and proper test documentation.

- AI support for CRO: generate headline variants, FAQ answers, objection lists, page audits, test ideas and conversion copy suggestions.

- Lead quality review: source, intent, form answers, follow-up response, sales feedback and mismatch between promise and delivery.

- Labs: audit a landing page, write AI-assisted hero copy, create CRO checklist and design a funnel map for a sample business.

- Practice outcome: improve performance by fixing funnel and landing page issues before increasing advertising budget.

Learn automation and retention workflows that connect marketing campaigns with CRM, email, WhatsApp, sales follow-up and repeat business.

- CRM fundamentals: lead source, lead status, owner, pipeline stage, follow-up date, notes, tags and marketing-to-sales handoff.

- Lead nurturing: welcome message, education sequence, objection handling, proof, demo booking, offer reminder and reactivation flow.

- Email marketing: subject lines, preview text, segmentation, personalization, deliverability, unsubscribe rules and list hygiene.

- WhatsApp marketing: opt-in, templates, quick replies, catalog links, broadcast discipline, support handoff and follow-up timing.

- Automation flows: lead response, abandoned cart, post-purchase, review request, repeat purchase, event reminders and win-back campaigns.

- Segmentation: new leads, qualified leads, high-intent visitors, inactive users, customers, repeat buyers and high-value customers.

- AI support: write follow-up scripts, email variations, WhatsApp responses, CRM notes, lead summaries and campaign sequence ideas.

- Sales alignment: lead scoring awareness, response time, qualification questions, rejection reasons, close rate and feedback loops.

- Retention metrics: open rate awareness, click rate, reply rate, conversion rate, retention revenue, churn and repeat purchase rate.

- Labs: create CRM pipeline, write email and WhatsApp flows, design lead-nurture automation and prepare response templates.

- Practice outcome: build follow-up systems that improve lead conversion and reduce wasted marketing spend.

Understand how to create campaign strategies for e-commerce, service businesses, marketplaces, lead generation and measurable sales growth.

- E-commerce funnel: product discovery, product page visit, add to cart, checkout, payment, delivery experience, reviews and repeat purchase.

- Product page optimization: titles, images, descriptions, trust points, size guide, pricing, offers, reviews, FAQs and return policy clarity.

- Catalog and shopping awareness: product feed basics, categories, attributes, pricing, stock, creative assets and data accuracy.

- Marketplace marketing: Amazon and Flipkart awareness, product listing quality, sponsored products, reviews, keywords, pricing and conversion rate.

- Lead generation funnel: landing page, form questions, call tracking, WhatsApp response, CRM pipeline, qualification and sales handoff.

- Local business growth: Google Business Profile, local ads, reviews, calls, maps visibility, local landing pages and nearby intent.

- Remarketing strategy: product viewers, cart abandoners, website visitors, engaged users, lead form starters and customer reactivation.

- AI support: product description variants, offer ideas, marketplace listing drafts, lead form questions and campaign performance summaries.

- Profitability metrics: gross margin awareness, AOV, ROAS, repeat purchase, refunds, return cost, lead quality and sale conversion rate.

- Labs: plan e-commerce campaign, audit product page, design lead-generation funnel and create marketplace listing improvement notes.

- Practice outcome: create practical growth plans for stores, service brands and marketplaces with stronger conversion thinking.

Build practical Gen AI workflows that help marketers work faster while keeping quality, accuracy, brand voice and business context in control.

- AI tool categories: chat assistants, image generators, video tools, transcription tools, design assistants, analytics assistants and automation tools.

- Prompt engineering: define role, context, audience, goal, constraints, tone, examples, output format and revision instruction clearly.

- AI for copywriting: ad copy, headlines, captions, email drafts, WhatsApp messages, landing page copy, blog outlines and CTA variants.

- AI for creatives: mood boards, visual concepts, storyboard ideas, thumbnail directions, product angles and creative brief development.

- AI for analytics: summarize data, identify trends, compare metrics, draft insights, create recommendations and prepare presentation notes.

- AI for content repurposing: convert blogs into reels, carousels, email, social posts, ad angles, FAQs and short scripts.

- AI automation awareness: spreadsheet workflows, CRM notes, report summaries, template generation, content calendars and repetitive task support.

- Quality control: fact-checking, plagiarism awareness, brand tone review, legal claim review, privacy checks and avoiding sensitive data exposure.

- Prompt library building: research prompts, ad prompts, content prompts, reporting prompts, CRO prompts and client communication prompts.

- Labs: create marketing prompt library, improve poor AI output, build content repurposing workflow and draft an AI-assisted campaign report.

- Practice outcome: use Gen AI as a professional marketing assistant without losing human strategy, accuracy and brand judgment.

Learn advanced brand-building methods that support digital performance, improve trust and create long-term audience relationships.

- Brand strategy: mission, promise, audience, positioning, tone, visual consistency, differentiation and customer trust-building.

- Storytelling: founder story, customer transformation, problem-solution narrative, behind-the-scenes content and proof-led communication.

- Influencer marketing: creator selection, audience fit, collaboration brief, deliverables, usage rights awareness, tracking links and reporting.

- Community marketing: groups, broadcast channels, comment engagement, customer advocacy, events, webinars and education-led growth.

- Reputation management: reviews, ratings, testimonials, complaint handling, response templates, social listening and trust recovery.

- Personal branding: LinkedIn content, expertise posts, case studies, point of view, authority building and consistent professional presence.

- Partnerships: co-marketing, affiliate awareness, local collaborations, webinar partners, content swaps and referral systems.

- AI support: generate collaboration briefs, creator shortlists, story angles, testimonial scripts and community content ideas.

- Brand metrics: engagement quality, saves, shares, comments, sentiment, follower quality, branded search, referral traffic and repeat audience touchpoints.

- Labs: prepare brand voice sheet, influencer brief, community plan, reputation response script and personal branding content calendar.

- Practice outcome: combine brand trust and community growth with measurable digital marketing campaigns.

Complete the program with a practical capstone that demonstrates strategy, research, execution planning, AI workflow, reporting and career-ready explanation.

- Capstone selection: choose a business case such as e-commerce store, local service, institute, SaaS product, fashion brand or lead-generation business.

- Strategy document: business objective, audience research, competitor insights, funnel map, offer plan, channel selection and KPI targets.

- Campaign assets: search ads, social ads, content calendar, AI prompt library, landing page suggestions, email and WhatsApp follow-up scripts.

- Tracking plan: UTM structure, conversion event map, dashboard layout, reporting frequency, lead quality review and attribution notes.

- SEO and content plan: keyword map, blog topics, social content, short-form video ideas, local SEO notes and repurposing workflow.

- Paid ads plan: Google, Meta and LinkedIn awareness, audiences, budgets, creatives, copy variants, optimization checklist and testing roadmap.

- CRO audit: landing page review, CTA clarity, trust signals, form quality, page speed notes and conversion improvement recommendations.

- AI workflow documentation: prompts used, outputs improved, human edits, validation notes, brand voice checks and responsible use statement.

- Interview preparation: marketing metrics, funnel questions, campaign structure, AI use cases, reporting explanation and scenario-based questions.

- Final presentation: explain campaign logic, show assets, present dashboard idea, discuss risks and defend recommendations professionally.

- Practice outcome: deliver a portfolio-ready Advanced Digital Marketing + Gen AI capstone and confidently explain strategy, execution and results.