Segmentation and personalised marketing

Segmentation divides a market into groups whose differences justify a different marketing response. Personalised marketing takes that logic towards the individual, selecting content, offers or experiences from customer-level data. Both methods aim to improve relevance; both can create complexity, unfairness or intrusion when applied without discipline.

When to use it

• Match offers and experiences to materially different customer needs.
• Identify groups whose needs are underserved.
• Focus acquisition, service and product investment.
• Personalise when individual-level variation creates enough value to justify data, operational and governance cost.

Origins

Economic ideas about differentiated demand developed in the 1930s, including Edward Chamberlin’s work on product differentiation. General Motors, under Alfred P. Sloan, had already demonstrated a portfolio strategy—“a car for every purse and purpose”—in contrast with a more standardised Ford model.

Wendell Smith formalised modern market segmentation in 1956. Wind and Cardozo later defined an industrial segment in 1974 through shared characteristics relevant to response. Personalised and one-to-one marketing grew in the 1990s as customer databases, digital channels and configurable operations made individual treatment more feasible.

What it is

Segmentation identifies groups that are distinct, measurable, reachable, actionable and economically worthwhile. The goal is not to find the maximum number of clusters; it is to choose where a different offer, channel, price or message improves customer value and organisational performance.

Variables may include geography, demography, firmographics, needs, attitudes, occasions and observed behaviour. Demographic proxies are convenient but often weak explanations of choice and can encode sensitive characteristics. Behavioural data can be more direct yet still reflect unequal access, historical bias or one channel rather than durable need.

Personalisation operates at different depths: selecting a relevant message, ranking recommendations, configuring a product or setting service. Amazon recommendations, a configurable Dell computer and a custom portal illustrate different mechanisms. Individual treatment should not be presented as perfectly knowing the person.