What is Marketing?

Marketing is simply communication between a business and potential customers to create and encourage sales. It's everywhere around you - from TV adverts and billboards to social media posts and email campaigns.

Businesses can target different markets like fashion, electronics, travel, or beauty. The purpose of marketing is identifying, anticipating, and satisfying customers' requirements profitably. Think of it as figuring out what people want before they even know they want it.

There are different ways customers and businesses connect: retail (physical shops), e-tail (online), and m-commerce (mobile). You've probably used C2C platforms like eBay or Vinted without realising you're part of consumer-to-consumer marketing.

Quick Tip: Marketing objectives typically focus on sales growth, increasing market share, building customer loyalty, or launching new products - these are measurable goals businesses can track.

Market Types and Growth

Mass markets target most people with fast-moving consumer goods, whilst niche markets focus on smaller groups with bespoke products. Think McDonald's versus a local artisan bakery.

Market size determines potential customers, but what about the future? A saturated market is crowded with competitors. Companies might have a monopoly (whole market) or operate in an oligopoly (few main players dominating).

Product diversification helps increase market share and customers. Market growth is calculated as: change ÷ original × 100. Your market share = revenue ÷ full market value × 100.

Both internal influences (mission statements, operations) and external influences (competition, economy, consumer income, demographic changes) affect marketing objectives. Smart businesses consider all these factors when planning their strategy.

Remember: A wide product portfolio means having lots of different products to appeal to various customer segments.

Understanding Markets Through Research

Market research helps businesses understand consumer needs, identify trends, and analyse competitors. It answers crucial questions: who will buy your products? What sets you apart? Will customers have concerns?

There are two main types of data: qualitative (opinions, feelings) and quantitative (numerical statistics). Both give valuable insights but serve different purposes.

Primary research is first-hand feedback you collect yourself through focus groups, questionnaires, or prototype testing. Secondary research uses existing data like government reports, newspapers, or social media analytics that someone else collected.

Your sample size matters - it determines how reliable your results are. You need enough people to represent your target market accurately.

Key Insight: Primary research gives you competitive advantage and relevancy, whilst secondary research is quicker and cheaper to obtain.

Research Methods: Pros and Cons

Primary research offers competitive advantage, relevancy, and up-to-date insights, but it's time-consuming and costly. Secondary research is quicker and cheaper but might lack competitive advantage or be outdated.

Quantitative data is easy to process with wider samples and precise results. However, it doesn't explain the "why" behind customer behaviour. Qualitative data gives in-depth results and explains motivations, but uses smaller sample sizes and can be harder to analyse.

Sampling methods include random sampling (choosing a small representative group) and stratified random sampling (selecting segments of your target market first, then randomly picking from each segment).

Results may be biased depending on your sample, and smaller samples might give inaccurate results that are too close to individual opinions rather than broader trends.

Pro Tip: The best research combines both quantitative and qualitative methods to get complete insights into customer behaviour.

Confidence Levels and Business Decisions

A confidence level shows the probability that your data is correct (e.g., 80%). A confidence interval gives the range of outcomes for a given probability - essentially your margin of error.

Wider intervals mean lower confidence levels, so any results are just estimates. However, this helps make more effective business decisions with 95% being the standard confidence level.

For companies like LEGO, being a PLC (Public Limited Company) versus LTD (Private Limited Company) affects decision-making. PLCs worry about share value, AGMs, and financial transparency, whilst LTDs have more privacy.

LEGO's 2023 revenue showed 2% growth despite challenges from recession and COVID-19. Market research data helps predict sales and plan for the future through smart capital management.

Reality Check: Even successful companies like LEGO face challenges - understanding market data helps them adapt and survive difficult periods.

Interpreting Data and Forecasting

Correlation shows relationships between two factors - but remember, correlation doesn't mean cause and effect. External factors like economy, seasonality, cultural changes, and income all affect sales.

Businesses need to forecast sales to make smart decisions about investment, plan for the future, and manage available resources. PESTLE factors (Political, Economic, Social, Technological, Legal, Environmental) all influence marketing success.

Strong positive correlation means data points are close together, giving you more confidence. Weak correlation means points are far apart, making decisions riskier. Always consider external factors that might cause correlations.

Extrapolation uses existing data to forecast the future. It provides faster communication and easier forecasting, but can create false security if you ignore changing fashions, lifestyles, or external factors.

Warning: Technology helps gather data faster, but don't let it give you false confidence - always consider what might change in the future.

Technology and Data Analysis

Technology makes data gathering faster and communication easier, enabling targeted marketing messages. However, it can be biased and create false security if you rely on it too heavily.

Understanding correlation strength helps evaluate relationships. Close positive correlations suggest strong relationships, whilst scattered data points indicate weak correlations that make decisions riskier.

Successful forecasting depends on how much data you have and considering external factors. Negative correlation means factors move in opposite directions - like when prices increase but demand decreases due to unemployment.

External factors often cause correlations - economic booms or recessions can explain why certain relationships exist. Smart businesses always consider these broader influences when interpreting their data.

Key Point: Strong correlations give you confidence in decision-making, but always question whether external factors might be influencing the relationship.

Price Elasticity of Demand

Price elasticity of demand measures how significantly demand changes when prices change. It's hugely important for businesses setting prices and predicting customer reactions.

Price elastic products (like fast fashion, supermarket goods, restaurants) see big demand changes with small price adjustments. These markets usually have lots of similar competitors, so customers easily switch.

Price inelastic products (like iPhones, luxury brands, property) don't see much demand change despite price increases. This happens due to brand loyalty, few substitutes, or products being necessities.

The calculation is: % change in demand ÷ % change in price. If the answer is greater than 1, the product is price elastic. If less than 1, it's price inelastic.

Business Reality: Understanding price elasticity helps businesses anticipate customer reactions and set optimal prices for maximum revenue.

Calculating Price Elasticity

When price elasticity is greater than 1, customers are sensitive to price changes. When it's less than 1, customers aren't very sensitive to price changes.

For price elastic products, the percentage change in demand is greater than the percentage change in price. This means small price increases can cause big drops in sales.

Here's a real example: Mince pies increased from £3.00 to £3.80 (27% increase), whilst demand fell from 1,385,204 to 1,024,456 units (26% decrease). The elasticity coefficient is 0.96, making it close to elastic.

Always ignore the negative sign in your calculations - we're interested in the size of the relationship, not whether it's positive or negative.

Calculation Tip: Practice with real examples like this mince pie calculation to understand how businesses use price elasticity in decision-making.

Using Price Elasticity in Business

If your product is price elastic, customers are sensitive to price, so be careful setting prices and use sales promotions effectively. Small price cuts can lead to big increases in sales.

A British Airways example: ticket prices increased 42% (from £3,426 to £4,850) whilst sales dropped 8%. The elasticity coefficient of 0.19 shows it's price inelastic - customers still buy despite higher prices.

Factors affecting price elasticity include brand strength and loyalty, availability of similar products, whether it's a necessity, and whether reasonable substitutes exist. The more choice customers have, the more elastic demand becomes.

Understanding these factors helps businesses make smart pricing decisions. Apple can charge premium prices because of strong brand loyalty and limited substitutes, whilst restaurants must be more careful due to fierce competition.

Strategic Insight: Strong brands like Apple create price inelastic demand through marketing that builds loyalty - this is why marketing objectives often focus on brand building.