the changing role of Information Technology (IT) and Artificial Intelligence (AI) in marketing

Cambridge A‑Level Business 9609 – Comprehensive Revision Notes

1. Business & Its Environment (AS‑Level)

1.1 Enterprise, Factors of Production & Business Types

• Enterprise – the initiative to combine the factors of production to create goods or services for profit.
• Factors of Production
  • Land (natural resources)
  • Labour (human effort & skills)
  • Capital (machinery, equipment, finance)
  • Enterprise (risk‑taking, innovation)
• Economic Sectors
  • Primary – extraction of raw materials (e.g., farming, mining)
  • Secondary – manufacturing & construction
  • Tertiary – services (retail, banking)
  • Quaternary – knowledge‑based services (IT, research)
• Ownership & Legal Forms
  • Sole trader – unlimited liability, simple set‑up.
  • Partnership – shared liability, partnership agreement.
  • Limited company (Ltd) – limited liability, separate legal entity.
  • Public limited company (PLC) – shares traded on a stock exchange.
  • Franchise – contractual right to use brand & systems.
  • Co‑operative – owned & democratically controlled by members.

1.2 Business Plans, Size & Growth

• Business Plan – a written document outlining:
  • Business idea & objectives
  • Market analysis (STP)
  • Marketing mix (4 Ps)
  • Operations & organisational structure
  • Financial projections (cash‑flow, break‑even)
• Measuring Size
  • Turnover, number of employees, market share, asset value.
  • Advantages of small firms – flexibility, closer customer contact.
  • Disadvantages – limited finance, economies of scale.
• Growth Strategies
  • Organic growth – increased sales, new products, market penetration.
  • External growth – mergers, acquisitions, joint ventures, strategic alliances.

1.3 Objectives, Stakeholders & the Business Environment

• Business Objectives
  • Profit‑maximisation, market‑share, growth, survival.
  • Social objectives – CSR, sustainability, employee welfare.
  • SMART criteria – Specific, Measurable, Achievable, Relevant, Time‑bound.
• Stakeholder Analysis
  • Internal – owners, managers, employees.
  • External – customers, suppliers, lenders, government, community, trade unions.
  • Influence‑interest matrix to prioritise actions.
• PESTLE Analysis

  Factor	Key Questions
  Political	Government stability, trade policies, tax rates
  Economic	Inflation, exchange rates, consumer confidence
  Social	Demographics, lifestyle trends, cultural attitudes
  Technological	Innovation speed, R&D, automation
  Legal	Employment law, health & safety, consumer protection
  Environmental	Climate change, waste legislation, sustainability pressures

  Example: Brexit (Political) → new tariffs (Economic) & supply‑chain risk (Environmental).

• Porter’s Five Forces
  • Threat of new entrants
  • Bargaining power of suppliers
  • Bargaining power of buyers
  • Threat of substitutes
  • Rivalry among existing competitors
• SWOT Analysis
  • Strengths & Weaknesses – internal.
  • Opportunities & Threats – external.
• Strategic Tools (A‑Level)
  • Ansoff Matrix – Market Penetration, Market Development, Product Development, Diversification.
  • BCG (Boston) Matrix – Stars, Cash Cows, Question Marks, Dogs.
  • Blue‑Ocean Strategy – creating uncontested market space.
• Corporate Social Responsibility (CSR) & Sustainability
  • Triple Bottom Line – People, Planet, Profit.
  • Examples: Tesco “Little Helps”, Unilever Sustainable Living Plan.
• International Trade & Globalisation
  • Entry modes – exporting, licensing, franchising, joint venture, wholly‑owned subsidiary.
  • Barriers – tariffs, quotas, non‑tariff barriers, exchange‑rate risk.

2. Human Resource Management (AS‑Level)

2.1 Workforce Planning & Employment Law

• Workforce Planning – forecasting demand for labour, analysing supply, identifying gaps.
• Turnover – voluntary vs. involuntary; costs of recruitment & training.
• Employment Law (UK)
  • Contracts of employment, minimum wage, working time regulations.
  • Equality Act – prohibits discrimination on protected characteristics.
  • Health & safety duties, data‑protection (GDPR).

2.2 Recruitment, Selection & Redundancy

• Recruitment Process
  1. Job analysis & specification.
  2. Advertising – internal (postings, intranet) vs. external (job boards, agencies).
  3. Application forms & CVs.
• Selection Techniques
  • Screening – shortlisting, psychometric tests.
  • Interviews – structured, unstructured, competency‑based.
  • Assessment centres – role‑plays, group exercises, presentations.
  • Background checks – references, DBS checks.
• Redundancy vs. Dismissal
  • Redundancy – role no longer required; must be genuine, fair selection, consultation.
  • Dismissing for misconduct – fair reason, procedural fairness, notice period.

2.3 Training, Development & Welfare

• Training Types
  • Induction – introduction to policies & culture.
  • On‑the‑job – coaching, mentoring, job rotation.
  • Off‑the‑job – classroom courses, e‑learning, conferences.
• Career Development – appraisal systems, succession planning, professional qualifications.
• Employee Welfare & Morale
  • Work‑life balance initiatives, health programmes, employee assistance schemes.
  • Motivation impact on productivity and turnover.

2.4 Trade Unions & Industrial Relations

• Trade Union Functions – collective bargaining, representation, industrial action.
• Collective Agreements – negotiated terms on pay, hours, conditions.
• Industrial Action – strikes, lock‑outs; legal requirements for notice.

2.5 Motivation Theories & Management Styles

• Content Theories
  • Maslow’s Hierarchy of Needs.
  • Herzberg’s Two‑Factor Theory (Hygiene vs. Motivators).
  • McClelland’s Need for Achievement, Power, Affiliation.
  • Vroom’s Expectancy Theory – expectancy, instrumentality, valence.
• Process Theories – Equity Theory, Goal‑Setting Theory.
• Management Styles
  • Autocratic – decisions by manager only.
  • Democratic – staff involvement in decision‑making.
  • Laissez‑faire – minimal direction.
  • McGregor’s Theory X (authoritarian) & Theory Y (participative).
  • Mintzberg’s Managerial Roles – interpersonal, informational, decisional.

2.6 Emerging Technology in HRM (A‑Level)

• AI‑driven recruitment – CV screening algorithms, predictive analytics for fit.
• People analytics – turnover prediction, talent‑pipeline modelling.
• Learning Management Systems (LMS) & VR training for immersive skill development.
• Robotic Process Automation (RPA) – automates routine HR admin.

3. Marketing – Core Concepts (8.1) and the Changing Role of IT & AI (8.2)

3.1 Core Marketing Concepts (AS‑Level – 8.1)

• Market Segmentation, Targeting & Positioning (STP)
  • Segmentation bases – demographic, geographic, psychographic, behavioural.
  • Targeting – criteria for selecting viable segments.
  • Positioning – creating a distinct place in the consumer’s mind; positioning maps (e.g., price vs. quality).
• Elasticity of Demand

  Formula: \[E_d = \frac{\%\Delta Q_d}{\%\Delta P}\]
  • |E_d| > 1 = elastic; |E_d| < 1 = inelastic; |E_d| = 1 = unit‑elastic.

• Product Life‑Cycle (PLC) – Introduction, Growth, Maturity, Decline.
• Boston (BCG) Matrix – Stars, Cash Cows, Question Marks, Dogs (portfolio analysis).
• Sales Forecasting Techniques
  • Qualitative – Delphi method, market research, expert opinion.
  • Quantitative – time‑series (moving average, exponential smoothing), causal models (regression).
• Marketing Plan Structure
  1. Executive summary
  2. Situation analysis (STP, SWOT, PESTLE)
  3. Marketing objectives (SMART)
  4. Strategic choices – the 4 Ps
  5. Budget, implementation timetable & control mechanisms
• International Marketing
  • Standardisation vs. localisation.
  • Adapting the 4 Ps to cultural, legal and economic differences.

3.2 The Changing Role of Information Technology (IT) & Artificial Intelligence (AI) in Marketing (8.2)

3.2.1 Historical Evolution

Period	Key IT/AI Developments	Marketing Impact
Traditional IT (pre‑2000)	Database management, basic market research, e‑mail blasts	Batch communication; limited data insight
Internet Era (2000‑2010)	Websites, SEO, PPC, early social media (MySpace, Facebook)	First wave of digital advertising & two‑way interaction
Mobile & Cloud Era (2010‑2020)	Smart‑phone apps, cloud‑based CRM, real‑time analytics, omnichannel	Location‑based offers, seamless online‑offline experience
AI Era (2020‑present)	Machine learning, NLP, computer vision, reinforcement learning, generative AI	Predictive targeting, hyper‑personalisation, autonomous campaign optimisation

3.2.2 AI‑Enabled Tools & Techniques

• Machine Learning (Supervised & Unsupervised)
  • Predictive models – demand forecasting, churn prediction.
  • Clustering – behavioural segmentation (e.g., k‑means, hierarchical).
• Natural Language Processing (NLP)
  • Chatbots (Dialogflow, ChatGPT), sentiment analysis, AI‑generated copy.
• Computer Vision
  • Visual search, image‑based recommendations (Pinterest Lens, Amazon StyleSnap).
• Reinforcement Learning
  • Real‑time bidding in programmatic advertising.
• Robotic Process Automation (RPA)
  • Automates repetitive marketing tasks – email scheduling, data entry, report generation.
• Generative AI
  • Creates assets at scale – images (DALL·E), video (Runway), copy (ChatGPT).

3.2.3 Impact on the Marketing Mix (4 Ps)

Marketing Mix Element	Traditional IT Approach	AI‑Enhanced Approach
Product	Feature‑based design, periodic surveys.	AI analyses usage data & sentiment to suggest feature upgrades; rapid prototyping via generative design.
Price	Cost‑plus or competitor‑based pricing.	Dynamic pricing algorithms adjust in real time using demand elasticity, inventory levels, competitor prices.
Place (Distribution)	Channel selection based on historical sales.	Predictive routing optimises inventory placement; AI‑driven last‑mile delivery (autonomous drones, robots).
Promotion	Mass‑media ads, scheduled email blasts.	Personalised content recommendations, AI‑generated ad copy, automated A/B testing & budget re‑allocation.

3.2.4 AI in Segmentation, Targeting & Personalisation

• Behavioural clustering – unsupervised learning groups customers by purchase patterns, site navigation, IoT data.
• Predictive personas – models forecast future buying intent, enabling proactive outreach.
• Real‑time segment updates – streaming data (click‑stream, wearables) continuously refines segments.
• Recommendation engines – collaborative filtering, matrix factorisation, deep learning (e.g., Netflix, Amazon).
• Dynamic website content – AI tailors layout, product displays and offers to each visitor.
• Chatbots & virtual assistants – 24/7 support, upsell suggestions, sentiment‑aware responses.

3.2.5 Data Analytics & Decision‑Making

• Predictive analytics – example multiple‑regression model:
  \[\hat{Y}= \beta_0 + \beta_1X_1 + \dots + \beta_nX_n\] where \(X_i\) represent marketing variables (advertising spend, price, seasonality).
• Prescriptive analytics – optimisation (linear programming) recommends the optimal allocation of the marketing budget across the 4 Ps.
• Real‑time dashboards – cloud data warehouses (Snowflake, BigQuery) visualise KPIs such as Customer Acquisition Cost (CAC), Customer Lifetime Value (CLV), conversion rates.

3.2.6 Ethical & Legal Considerations

• Data privacy – GDPR, CCPA: obtain explicit consent, enable data‑subject rights, maintain records of processing.
• Algorithmic bias – test models for discrimination (gender, ethnicity) and adjust training data or weighting.
• Transparency – disclose AI‑generated content; provide a “human‑in‑the‑loop” where required.
• Intellectual property – clarify ownership of AI‑created assets.

3.2.7 Future Trends

• Edge AI – on‑device inference for instant personalisation without cloud latency.
• Voice‑first interfaces – smart speakers reshape search & commerce (“Alexa, order coffee”).
• Metaverse marketing – immersive brand experiences powered by AI avatars and virtual showrooms.
• AI‑driven sustainability – optimisation of supply‑chain emissions, carbon‑footprint dashboards.

4. Operations Management – Linking Production, Quality & Technology (A‑Level)

4.1 Location Decision‑Making

• Factors – market proximity, transport costs, labour availability, government incentives, infrastructure.
• Tools – centre‑of‑gravity model, break‑even analysis for site selection, cost‑benefit analysis.

4.2 Scale of Production

• Economies of scale – fixed‑cost dilution, specialised labour, bulk buying.
• Diseconomies of scale – coordination problems, bureaucracy.
• Capacity planning – forecasting demand, capacity utilisation rate, flexibility.

4.3 Quality Management

• Approaches – Total Quality Management (TQM), Six Sigma (DMAIC), ISO 9001.
• Statistical Process Control (SPC) charts – X‑bar, R‑chart, control limits.

4.4 Technology & Process Innovation

• Enterprise Resource Planning (ERP) integrates finance, HR and operations data.
• Lean tools – 5S, Kaizen, value‑stream mapping.
• Computer‑Aided Production – CNC machining, industrial robotics, additive manufacturing (3D printing).

4.5 Capacity Planning & Forecasting (CPA)

• Network diagram – activity sequencing, critical path, float.
• Simulation software (Arena, Simul8) to test demand scenarios and resource utilisation.

5. Finance & Accounting – Interpreting Numbers for Strategic Decisions (A‑Level)

5.1 Core Financial Statements

Statement	Purpose	Main Components
Profit & Loss (Income) Statement	Shows profitability over a period.	Revenue, Cost of Goods Sold, Gross Profit, Operating Expenses, Net Profit.
Balance Sheet	Snapshot of financial position at a point in time.	Assets (current & non‑current), Liabilities (current & long‑term), Owner’s Equity.
Cash‑Flow Statement	Tracks cash inflows & outflows.	Operating, Investing, Financing activities.

5.2 Ratio Analysis (Key Performance Indicators)

Ratio	Formula	Interpretation
Gross Profit Margin	\(\frac{Gross\ Profit}{Revenue}\times100\)	Shows efficiency of production & pricing.
Current Ratio	\(\frac{Current\ Assets}{Current\ Liabilities}\)	Indicates short‑term liquidity.
Return on Capital Employed (ROCE)	\(\frac{Operating\ Profit}{Capital\ Employed}\times100\)	Measures profitability relative to long‑term funds.
Net Profit Margin	\(\frac{Net\ Profit}{Revenue}\times100\)	Overall profitability after all expenses.
Debt‑to‑Equity Ratio	\(\frac{Total\ Debt}{Total\ Equity}\)	Degree of financial leverage.

5.3 Break‑Even & Investment Appraisal

• Break‑Even Analysis
  • Break‑Even Point (units) = \(\frac{Fixed\ Costs}{\text{Price per unit} - \text{Variable cost per unit}}\)
  • Margin of Safety = \(\frac{Actual\ Sales - Break‑Even\ Sales}{Actual\ Sales}\times100\)
• Investment Appraisal Techniques
  • Payback period – time to recover initial outlay.
  • Net Present Value (NPV) – \(\displaystyle NPV = \sum_{t=0}^{n}\frac{C_t}{(1+r)^t}\)
  • Internal Rate of Return (IRR) – discount rate that makes NPV = 0.
  • Accounting Rate of Return (ARR) – average profit / initial investment.