Strategy and Metrics

Segmentation

Also called market segmentation, customer segmentation, STP

Dividing a market or customer base into groups with shared traits that respond differently, so each can be marketed to in a way that suits it.

Quick facts: Segmentation

Category
Strategy and Metrics
Also called
market segmentation, customer segmentation, STP
Level
Beginner
Affects
Message relevance, ad targeting and bids, email engagement, product and pricing decisions
Where to see it
CRM and ecommerce exports, GA4 audiences, email platform segments, ad platform audiences, spreadsheets
In this article4
  1. How segmentation works
  2. Why it matters
  3. Common mistakes
  4. How to act on it

Segmentation is the practice of dividing a market or customer base into groups whose members share characteristics that make them respond in similar ways, so you can market to each group in a way that fits it. It is the first step of the STP model: segment the market, choose which segments to target, then position your offer for them.

How segmentation works

There are four classic ways to divide people, and most useful segmentations combine two or more:

  • Geographic: where people are. A Manchester plumber segments by postcode area; a national retailer might treat London separately because delivery costs and prices differ.
  • Demographic: age, life stage, income and household. For B2B the equivalent is firmographic: sector, company size, turnover and number of sites.
  • Psychographic: values, attitudes and interests. Two homeowners of the same age may choose a kitchen for entirely different reasons, one for resale value and one for cooking.
  • Behavioural: what people actually do. First-time buyers against repeat customers, people who only buy on discount, people who abandoned a basket, customers who have not ordered for a year.

Behavioural segments are usually the most useful in digital marketing, because the data already sits in your shop, CRM or analytics, and past behaviour predicts future behaviour better than demographics alone. RFM analysis, which groups customers by how recently, how often and how much they buy, is a practical place to start.

A segment earns its place only if it passes a few tests: you can measure it, it is large enough to matter, you can reach it through a channel you use, and it genuinely responds differently from the others.

Why it matters

A message written for everyone tends to land with no one. A bathroom fitter whose customers split between landlords wanting quick, hard-wearing refits and homeowners wanting a design project needs two landing pages, two sets of photos and two arguments. One generic page serves both badly.

Segmentation also controls cost. In paid advertising it lets you bid more for groups that convert and exclude those that do not. In email, sending lapsed customers a different message from recent buyers usually improves engagement and reduces unsubscribes. And it lets you choose your target market deliberately rather than by default.

For UK businesses there is a data protection side. Segmenting customers using their personal data is processing under UK GDPR, so your privacy notice should explain it, and segmenting by special category data such as health or ethnicity needs a much stronger justification. Ad platforms add their own limits on targeting by sensitive characteristics.

Common mistakes

  • Too many segments. Twelve segments with three emails each is unmanageable for a small team. Start with two to four that clearly behave differently.
  • Segments nobody uses. A segmentation that lives in a slide deck and never changes a campaign, page or offer is wasted effort.
  • Building on assumptions. Segments based on guesses about “typical customers” often fall apart against real purchase data. Check first.
  • Confusing segments with personas. A segment is a measurable group; a buyer persona is a portrait of a typical member of it. You need the segment first.
  • Never refreshing. Customers move between segments. A new buyer becomes a loyal one or a lapsed one, and your lists should keep up.

How to act on it

Begin with data you already hold. Export customers with their order history and any useful attributes, such as location or type of business. Look for natural splits: who buys most, who buys once, who arrives through which channel.

Choose two or three segments that differ meaningfully and that you can reach. For each, write down what they need, what puts them off and which message would move them. Then make one concrete change per segment, such as a separate landing page, a dedicated ad audience or an email segment, and measure the difference against what you did before.

Deciding which segments to pursue, and how to position for each, sits at the centre of the digital marketing strategy work I do with UK businesses.

Do and do not

Do

  • Start from behaviour data you already hold
  • Keep to a few segments you can actually serve
  • Make one concrete change per segment and measure it

Do not

  • Build segments from assumptions alone
  • Create more segments than you can maintain
  • Use sensitive personal data without a clear lawful basis

Questions people ask about this

What are the four main types of market segmentation?

Geographic (where customers are), demographic or firmographic (who they are, or what kind of business), psychographic (their values and attitudes) and behavioural (what they do, such as how often they buy). Most practical segmentations combine two or more, for example repeat buyers within a delivery area.

How many customer segments should a small business have?

Start with two to four. That is enough to tailor messages to groups that genuinely behave differently, without creating more campaigns and content than you can keep up with. Add more only when you can show an existing segment contains groups that respond in clearly different ways.

Is customer segmentation allowed under UK GDPR?

Generally yes, provided you have a lawful basis, often legitimate interests, and your privacy notice explains that you analyse customer data to tailor marketing. Keep the data proportionate to the purpose. Segmenting by special category data such as health or ethnicity needs explicit justification, so take advice before doing that.

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