IIM Kozhikode Professional Certificate Program in AI Powered Marketing, Analytics and Sales

• Understanding AI-enabled digital marketing ecosystem and channel landscape

• Owned: Paid–Earned (OPE) media strategy

- Full-funnel marketing framework: awareness, acquisition, activation, retention, referral, revenue

• Omnichannel customer experience strategy

• Platform vs pipeline business models

• Marketplace and aggregator business models

• AI-assisted KPI selection, campaign goal setting, and marketing planning

AI-Powered Market & Consumer Research

• Competitor analysis, trend discovery

• Keyword research, search intent analysis

• Social listening and review mining

Data Collection & Research Tools

• Surveys, forms, analytics platforms, third-party data

• AI-based summarisation and structuring

Model Evaluation & Tool Selection

• Comparing AI models (cost, quality, speed)

• Selecting tools for research, analytics, content

Prompt Engineering Basics, Ethical & Responsible AI Usage

• Bias, hallucination, privacy

• Responsible AI in research and decisions

• Empathise, define, ideate, prototype, and test using AI support

• AI-generated personas, problem statements, JTBD, and value propositions

• Opportunity mapping, concept prioritisation, and rapid experimentation

• Prompt-assisted wireframing, messaging, and creative ideation

• Design sprints for campaigns, products, and experience innovation

• Prompt-based website development for marketing pages and microsites

• Landing page architecture for lead generation, conversions, and A/B testing

• Building websites and prototypes using AI-native tools

• UX/UI basics for conversion-oriented design

• Blog, form, CTA, lead magnet, and funnel page setup

• MCP-enabled workflows for AI-assisted build environments

• Domain, hosting, deployment, and publishing workflows

• Static and dynamic site deployment using AI-assisted setup

• Hosting choices for campaign sites, landing pages, and prototypes

• Performance optimisation, security basics, and release workflow

- Cloud thinking for marketers: storage, authentication, hosting, and scaling

- Database basics for marketers: customer data, leads, events, and campaign records

• Real-time backend concepts and marketing data storage

• Forms, events, user attributes, and conversion data capture

• API basics, webhooks, and backend integrations for marketing automation

• No-code/low-code backend setup for AI-enabled applications

AI-Powered SEO Strategy

• AI-assisted keyword research, topic clusters, and content briefs

• Search intent mapping and SERP-driven content planning

- On-page SEO: metadata, internal linking, and content optimisation

- Technical SEO basics: crawlability, indexing, site speed, and schema

Search Engine Marketing (SEM)

• Paid search fundamentals and keyword bidding strategies

- Campaign structure: campaigns, ad groups, keywords, and match types

• Quality Score, ad rank, and cost optimisation

Google Ads & Performance Marketing

• Search Ads, Display Ads, and YouTube Ads strategy

• AI-assisted ad copy creation and creative optimisation

• Audience targeting, remarketing, and segmentation

• Budget allocation, bidding strategies, and campaign optimisation

AI-Driven Optimisation & Audits

• AI-assisted SEO audits and performance improvement recommendations

• Campaign performance tracking and optimisation using AI insights

• A/B testing for ads, landing pages, and creatives

• Content marketing strategy and planning

• Content calendar design and campaign planning

• Brand storytelling frameworks

• AI-assisted copywriting for blogs, social posts, ad copy, and email sequences

- Video marketing: short-form video strategy (Reels/Shorts)

• YouTube channel growth levers

- Social platform strategy: LinkedIn, Instagram, YouTube

• Content pillars, channel planning, and creator-led distribution

• Influencer selection, evaluation criteria, and fit analysis

• Measuring influencer ROI and campaign effectiveness

• Community building for engagement and advocacy

• Social listening and sentiment analysis fundamentals

• AI-assisted community management and response generation & Social media Ads via Meta and LinkedIn

• Email list building, segmentation, and funnel design

• Welcome, nurture, drip, retention, and reactivation journeys

• AI-generated subject lines, body copy, and personalisation blocks

• Trigger-based email workflows linked to user actions and events

• Deliverability, scheduling, and campaign testing basics

• End-to-end automation across email, social, ads, CRM, sheets, and reporting

• Workflow design with triggers, actions, conditions, and AI decision steps

• Automated content generation, approvals, routing, and publishing

• Lead capture to CRM sync to follow-up to dashboard workflow design

• AI agents for repetitive marketing tasks and internal productivity

• Intro to Google Flow for orchestration-style automation

• Tracking plans, web analytics setup, events, goals, and conversions

• Dashboarding for traffic, sources, sessions, conversions, and funnel drop-offs

• UTM strategy, attribution basics, and campaign measurement

• Digital consumer decision journey

• Role of social proof and online reviews in digital behaviour

• AI-assisted anomaly spotting and insight generation from dashboards

• Consumer behaviour in digital environments and behavioural triggers

• Growth marketing fundamentals and experimentation thinking

- AARRR funnel: acquisition, activation, retention, referral, revenue

• Growth loops vs funnels

• Conversion Rate Optimisation (CRO) fundamentals

- Neuromarketing foundations: attention, emotion, memory, nudges, cognitive bias, and choice architecture

• AI-assisted testing of hooks, creatives, landing page variants, and conversion hypotheses

• Customer segmentation, personas, cohorts, and behavioural clustering

• CLV, repeat behaviour, churn signals, and retention insight generation

• RFM thinking and customer prioritisation

• Audience discovery, micro-segmentation, and personalisation logic

• AI-supported insight extraction from customer data and feedback

• Campaign performance analysis, ROI, CAC, ROAS, and budget effectiveness

• Attribution thinking, channel contribution, and reporting logic

• Corporate strategy cascade, business model innovation, and competitive positioning

• Go-to-market (GTM) strategy design and cross-functional alignment

- Revenue architecture: pricing, packaging, monetisation, and market expansion

• AI-assisted dashboard summaries and executive-level decision support

• Product usage metrics, events, funnels, retention, and feature adoption

• User journey mapping, activation metrics, and drop-off analysis

• Cohort retention and behavioural path analysis

• AI-assisted product insight generation and hypothesis creation

• Linking product analytics to marketing, growth, and lifecycle decisions

• Marketing vs Sales alignment (Marketing)

• Sales strategy and go-to-market linkage

• Sales funnel and pipeline management

- Lead qualification frameworks: BANT/MEDDIC intro

• Sales enablement systems, scripts, and playbooks

• Hybrid/remote sales effectiveness

• Leadership in sales and marketing, data-driven decision culture, and performance governance

• AI-assisted forecasting, lead scoring modelling, prioritisation, and sales insight generation

• Working with multi-model ecosystems and routing models by task

• Open AI gateway usage through Open Router

• Google AI Studio workflows and experimentation

• MCP-based usage through Antigravity for integrated execution environments

• Data analysis in Julius AI and Google Collab with Gemini-assisted coding and interpretation

• Power BI / Tableau storytelling for business decisions