8.1 Marketing analysis

Price elasticity of demand measures the percentage change in quantity demanded divided by the percentage change in price. Income and promotional elasticity use the same logic with a different driver.

Elasticity helps predict how revenue, demand or response may change, but the estimate depends on time period, segment, substitutes and data quality.

If price rises 10% and quantity demanded falls 20%, PED is −2: demand is elastic in that context, so price may reduce total revenue.

Elasticity is not constant across every price or customer group, and correlation in a dataset does not prove the driver caused the change.

Product development involves generating, testing and refining an offer before and after launch. It connects customer need, technical feasibility, cost, risk and the marketing mix.

Testing can reveal usability or demand problems before full commitment, while iterative development can improve fit but delay revenue and consume resources.

A meal-kit firm can prototype packaging, test preparation time with target users and revise the product before scaling production.

A new feature is not innovation unless it creates useful value and can be delivered reliably.

A sales forecast estimates future sales volume or revenue using historical data, market research, trends, seasonal patterns, prices and managerial assumptions.

Forecasts inform capacity, staffing, finance and inventory. Their quality depends on the data, model, time horizon and ability to update when conditions change.

A retailer may combine last year’s seasonal pattern with a planned price change and a competitor’s launch rather than extend a trend blindly.

A precise forecast is not necessarily accurate; uncertainty should be shown and alternative scenarios considered.