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Segmentation

How can segmentation support strategic choice or positioning?

AccessibleStrategicIndividual3 min read

Contents

Use customer groups to gain competitive advantage.

Market segmentation groups customers or prospects whose needs or behaviour are similar enough to support a distinct strategy. Demographic and firmographic categories can be practical, but needs-based segmentation seeks the deeper differences that shape choice, value and service requirements.

When to use it

Identify customer groups whose differences should change the offer, channel, service or message.

Choose which groups the organisation can serve distinctively and profitably.

Avoid treating a large or familiar account category as if every member wants the same thing.

Refresh market understanding when behaviour, technology or needs change.

Origins

Businesses have always differentiated among customers, but segmentation became a formal marketing concept as mass markets expanded. Wendell R. Smith’s 1956 article “Product Differentiation and Market Segmentation as Alternative Marketing Strategies” gave the field its defining formulation. He contrasted differentiation across a broad market with carving out a segment whose distinct preferences warranted a tailored offer, while showing that the two strategies can reinforce one another.

What it is

Demographic consumer variables include age, household or life stage; firmographic variables include size, industry and location. These characteristics make groups identifiable and reachable, but they do not necessarily explain why customers choose.

Needs, attitudes, jobs and behaviours can provide stronger strategic insight. A large business customer may demand a stripped-down low-cost offer or extensive technical support; size alone cannot distinguish the two.

Research should therefore ask not only what customers say they prefer but what problem they are solving, what trade-offs they make and what evidence appears in behaviour. Self-report is valuable but incomplete, especially for status, habit or sensitive motives.

Needs-based work often combines interviews and observation with survey analysis. Researchers may ask respondents to rate several statements, use factor analysis to identify related attributes and then use cluster analysis to group similar response patterns. With 200 interviews and many variables, validation is essential: algorithms will produce clusters even when the segments are unstable or strategically meaningless.

Useful segments should be:

distinct in needs or response;

measurable and large enough for the decision;

reachable through a viable route;

stable enough to act on but monitored for change; and

compatible with a differentiated, economically sound response.

Developments of the model

Plotting segment attractiveness against the supplier’s ability to compete can support selection. A large “price fighter” segment may be unattractive if margins are poor, while a smaller group may justify investment because the company has a strong fit.

Quality fanatics

Segments that prioritise superior performance and are willing to recognise and pay for it may be attractive when the supplier can prove distinctive quality.

Traditionalists

Segments that value familiarity, continuity or trusted relationships require a different proposition from novelty-seeking groups.

Low

A low score on attractiveness or competitive position is a warning to deselect, redesign or gather better evidence; it is not a judgement about the customers themselves.

Needs-based segmentation is difficult in business-to-business markets because several people influence a purchase and the decision unit changes by situation. Digital personalisation can narrow groups dramatically, but more granularity is not automatically better. Privacy, discrimination, operational complexity and measurement error increase as segments become smaller.

How to use it

Nivea Sun, owned by Beiersdorf, used attitudes to examine the UK sun-care market and identified five groups:

Concerned consumers: understand sun damage, prefer high protection and place little value on tanning.

Sun avoiders: avoid sunbathing and view protection as effort, but may adopt products that are easy to use.

Conscientious sun lovers: enjoy sun exposure while selecting recognised brands and protection suited to themselves or family.

Careless tanners: value tanning but use insufficient protection and purchase protection inconsistently.

Naive beauty conscious: value a tan and recognise the idea of protection but lack confidence in selecting the appropriate factor.

The company prioritised conscientious sun lovers, naive beauty-conscious consumers and concerned consumers because of their category involvement, while treating the other groups as secondary. Demographic differences existed within the attitudinal segments, showing that needs and physical descriptors can be combined.

The analysis informed fast-acting and easy-to-apply product development and helped communications teams frame relevant messages. It supplemented rather than invalidated Nivea’s differentiated range of lotions, sprays, sensitive-skin, children’s, aftercare and self-tanning products.

Use the case as a method, not a current market taxonomy. Validate health-related claims with current public-health evidence, avoid implying that unsafe exposure is an acceptable preference to exploit, and re-estimate segments as knowledge and behaviour change.

Some things to think about

Start with the customer decision and gather demographic, behavioural, psychographic and needs evidence. A segment only creates advantage if the organisation responds differently and customers value the difference.

In B2B settings, segment the buying situation and decision unit as well as the company. Firm size and industry may provide reach, while needs, procurement behaviour and use context explain response.

Top practical tip

Name each segment from the evidence, write the distinct job and trade-offs, and specify the action that changes. If two groups receive the same proposition and economics, they may not need to be separate strategic segments.

Top pitfall

Do not mistake a statistically neat cluster or memorable label for a real market. Test stability, reach, response and economics on new data, and avoid labels that stereotype or expose sensitive groups.